{ "@context": "https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld", "@type": "dcat:Catalog", "conformsTo": "https://project-open-data.cio.gov/v1.1/schema", "describedBy": "https://project-open-data.cio.gov/v1.1/schema/catalog.json", "dataset": [ { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=58a541efc59545e6b7137f961d7de883", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::terrain", "title": "Terrain", "description": "

This dynamic World Elevation Terrain service provides numeric values representing ground surface heights, based on a digital terrain model (DTM). The ground heights are based on multiple sources. Heights are orthometric (sea level = 0), and water bodies that are above sea level have approximated nominal water heights.

What can you do with this layer?

Use for Visualization: This layer is generally not optimal for direct visualization. By default, 32 bit floating point values are returned, resulting in higher bandwidth requirements. Therefore, usage should be limited to applications requiring elevation data values. Alternatively, client applications can select from numerous additional functions, applied on the server, that return rendered data. For visualizations such as multi-directional hillshade, hillshade, elevation tinted hillshade, and slope, consider using the appropriate server-side function defined on this service.

Use for Analysis: Yes. This layer provides data as floating point elevation values suitable for use in analysis.

Note: This image services\ncombine data from different sources and resample the data dynamically to the\nrequested projection, extent and pixel size. For analyses using ArcGIS Desktop,\nyou can filter a dataset, specify the projection, extent and cell size using\nthe Make\nImage Server Layer geoprocessing tool.

Server Functions: This layer has server functions defined for the following\nelevation derivatives. In ArcGIS desktop, server function can be invoked from\nLayer Properties - Processing Templates.

\n\n


Data Sources and Coverage: This layer is compiled from a variety of best\navailable sources from several data providers. To see the coverage and extents of\nvarious datasets comprising this service in an interactive map, see Elevation Coverage Map.


Mosaic Method: This image service uses a default mosaic method of "By Attribute”, using Field 'Best' and target of 0. Each of the rasters has been attributed with ‘Best’ field value that is generally a function of the pixel size such that higher resolution datasets are displayed at higher priority. Other mosaic methods can be set, but care should be taken as the order of the rasters may change. Where required, queries can also be set to display only specific datasets such as only NED or the lock raster mosaic rule used to lock to a specific dataset.

Accuracy: The accuracy of these services will vary as a function of location and data source. Please refer to the metadata available in the services, and follow the links to the original sources for further details. An estimate of CE90 and LE90 are included as attributes, where available.

This layer allows query, identify, and export image requests. The layer is restricted to a 5,000 x 5,000 pixel limit in a single request.

This layer is part of a larger collection of elevation layers that you can use to perform a variety of mapping analysis tasks.
", "keyword": [ "DEM", "Elevation", "land", "topography", "esri_elevation", "world_elevation", "world elevation", "DTM", "slope", "aspect", "multidirectional", "multi-directional", "hillshade", "bare earth" ], "issued": "2013-07-04T19:32:39.000Z", "modified": "2024-04-05T03:21:55.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_elevation", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0000,180.0000,85.0511", "license": "This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::terrain" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://elevation.arcgis.com/arcgis/rest/services/WorldElevation/Terrain/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=831615388b7f42799542489f12b94602", "landingPage": "https://agriculture.africageoportal.com/apps/esri::water-balance-app", "title": "Water Balance App", "description": "

Click anywhere on earth to see how the water balance is changing over time. This app is based on data from GLDAS version 2.1, which uses weather observations like temperature, humidity, and rainfall to run the Noah land surface model. This model estimates how much of the rain becomes runoff, how much evaporates, and how much infiltrates into the soil. These output variables, calculated every three hours, are aggregated into monthly averages, giving us a record of the hydrologic cycle going all the way back to January 2000. 

Because the model is run with 0.25 degree spatial resolution (~30 km), these data should only be used for regional analysis. A specific farm or other small area might experience very different conditions than the region around it, especially because human influences like irrigation are not included.

This app can also be seen as a useful template for sharing other climate datasets. If you would like to customize it for your own organization, or use it as a starting point for your own scientific application, the source code is available on github for anyone to use. 

", "keyword": [ "GLDAS", "NASA", "hydrology", "earth observations", "landscape", "climate", "weather" ], "issued": "2017-09-28T18:12:28.000Z", "modified": "2026-10-27T17:38:19.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_hydro", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.0000,-89.9900,179.0000,89.9900", "license": "

 This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/esri::water-balance-app" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/waterbalance/" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d9944082e3c6421098464b1016fbae58", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::crop-and-pasture-phenology-start-max-and-end-of-season-global-1-km-fao-asis", "title": "Crop and Pasture Phenology - Start, Max and End of Season (Global - 1 km) - FAO ASIS", "description": "
Crop/Pasture Phenology is a set of reference datasets developed and used by ASIS, consisting of two global products: Stages (Start/Maximum/End) of Season and Progress of Season.
 
Phenology is defined as the study of the timing of recurring biological cycles and their connection to the climate. Changes in the vegetation phenology, including the start of season, the length of the season as well as the end of season impacts the ecosystem functioning such as carbon storage, water holding capacity and agricultural productivity.
 
Crop/pasture phenology maps depict the progress of the seasons. It is based on the long-term average of vegetation phenology for each pixel (In ASIS, Cropland/Grassland masks are applied. Pixel with at least 5% covered by the class are defined as a cropland/grassland pixel). This simplification implies that the crop/pasture phenology is static and therefore the growing seasons progress at a constant rate each year. The progress of growing seasons are described by three major phases: Start of Season (SOS), Maximum of Season (MOS) and End of Season (EOS).
 
Phenomenon Mapped: Crop and Pasture Phenology - Start, Max and End of Season
Units: non
Pixel Type: 32-bit Signed Integer
Last Updated: 2017
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: Reference layer, updated as needed.  
 
Start of Season (SOS) indicates the early stage of crop/grass emergence, defined as the date when the rising NDVI-curve cuts the threshold NDVIs: NDVIs=NDVImins + Ts.(NDVImax – NDVImins)
NDVImax is the NDVI at the maximum of the cycle, NDVImins is the minimum before this maximum and threshold Ts is fixed to 0.25 for all land cover types. SOS is searched leftwards from NDVImax to NDVImins.
 
Maximum of Season (MOS) indicates when crop/grass foliage is fully developed, defined as the date when the NDVI is at its maximum value.
 
End of Season (EOS) indicates when crop/grass has reached physiological maturity, defined as the date when the descending NDVI-curve crosses NDVIe, This date does not necessarily correspond to the harvest period. NDVIe=NDVImine + Te.(NDVImax – NDVimine)
 
NDVImax is the NDVI at the maximum of the cycle, NDVImine is the minimum after this maximum and threshold Te is set to 0.75 for cropland and to 0.25 for all other land. EOS is searched rightwards from NDVImax to NDVImine.
 
Map legend label and pixel value mapping (half open intervals): <October Y-1 : (-36)-(-6); November - December Y-1: (-6)-0; January - February: 0-6; March - April: 6-12; May - June: 12-18; July - August: 18-24; September - October: 24-30; November - December: 30-36; January - February Y+1: 36-42; >March Y+1 42-72:
 
Map flags: no seasons/no season 2: 251; no cropland/no grassland: 254
 
Global ASIS covers two crop/pasture seasons. Some countries have three or four crop seasons within a crop year. For these countries, Global ASIS cannot properly capture the crop phenology between the first and the last season (e.g. for a country has four crop seasons, the crop phenology of the 2nd and 3rd season).
 
Explore this and related data in this web application.
 
Checke the full metadata here: https://www.fao.org/giews/earthobservation/access.jsp?lang=en 
 
More information please visit FAO GIEWS Earth Observation website
 
", "keyword": [ "ASIS", "crop phenology", "crop growing season", "crop calendar", "start of season", "Maximum of Seaso", "End of season", "FAO GIEWS", "1 km resolution", "Global extent", "EO-based crop monitoring", "crop growing stage" ], "issued": "2022-05-02T04:13:46.000Z", "modified": "2026-09-08T14:27:33.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::crop-and-pasture-phenology-start-max-and-end-of-season-global-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/PHE/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6e15791ba4ca444bb609eaaf0c672a43", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::mozambique-flood-rapid-remote-sensing-assessment-february-2024", "title": "Mozambique flood rapid remote sensing assessment - February 2024", "description": "

In Mozambique, the 2022–⁠2023 rainy season brought with it above average rainfall, flash flooding and events that have led to the destruction of infrastructure and loss of lives. Between 7 and 11 February 2023, heavy rains of up to 100 mm in 24 hours hit the southern region of the country, causing widespread flooding in Maputo City and Maputo region. On 25 February, tropical storm Freddy made landfall, as a moderate tropical storm, over Mozambique. The Data in Emergencies team at the Food and Agriculture Organization of the United Nations (FAO) examined the satellite images from an extended time period, starting in February, including both the days when tropical cyclone Freddy was present and after to understand the impact. This StoryMap provides an assessment of the potential impacts of those floods on agriculture and livelihoods in Mozambique.

", "keyword": [ "DIEM StoryMap" ], "issued": "2023-03-01T11:48:16.000Z", "modified": "2026-09-04T13:38:41.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::mozambique-flood-rapid-remote-sensing-assessment-february-2024" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/6e15791ba4ca444bb609eaaf0c672a43" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=1aface7bffc14ddd96915c3996ef8d96", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::impact-potentiel-des-inondations-au-tchad-2023", "title": "Impact potentiel des inondations au Tchad, 2023", "description": "

La saison des pluies 2023 au Tchad a été marquée par des précipitations supérieures à la moyenne et des inondations soudaines, qui ont déjà eu un impact sur la production agricole. L'équipe de Données en situations d'urgence (DIEM) de l'Organisation des Nations Unies pour l'alimentation et l'agriculture (FAO) a, depuis le début de la saison des pluies, examiné régulièrement des images satellite et déclenché cette évaluation détaillée au vu de l'étendue des inondations et des terres cultivées touchées. Cette StoryMap présente l'impact potentiel des inondations sur la production agricole et les moyens d'existence au Tchad.

", "keyword": [ "DIEM StoryMap", "DIEM-FAMILY:432243b53cfd4c72bef22cc6ca3cf792" ], "issued": "2023-09-18T12:49:21.000Z", "modified": "2026-09-04T13:21:14.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::impact-potentiel-des-inondations-au-tchad-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/1aface7bffc14ddd96915c3996ef8d96" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d114a3b6113b437eb7f61dc701c02a76", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::weighted-mean-vegetation-health-index-global-dekadal-1-km-fao-asis", "title": "Weighted Mean Vegetation Health Index (Global - Dekadal - 1 km ) - FAO ASIS", "description": "
The Weighted Mean Vegetation Health Index (Mean VHI) allows the user to assess the severity of the drought from the start of the growing season, examining the vegetation health and the influence of temperature on plant conditions.
 
Two quick-look indicators in ASIS: Agricultural Stress Index (ASI) and Drought Intensity are both based on Weighted Mean-VHI dataset.
It is an average of the dekadal VHI values over the crop growing season (from the start until the last dekad of analysis), weighted by crop coefficients (Kc), assigned to VHI values at the dekads corresponding to the Start of the Season (SOS), Maximum of the Season (MOS) and End of the Season (EOS). Crop coefficient is applied for the purpose of reflecting the crop’s water sensitivity at different phenology stages.
 
Phenomenon Mapped: Weighted Mean Vegetation Health Index
Units: non
Time Interval: 10-day
Time Extent: 1984-Present
Cell Size: 1 km
Pixel Type: 32-bit Signed Integer
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: 10-days + 3-4 days lag
 
Explore this and related data in this web application.
 
More information please visit FAO GIEWS Earth Observation website
 
 
", "keyword": [ "FAO GIEWS", "ASIS", "Global extent", "EO-based crop monitoring", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Seasonal Indictor", "weighted mean Vegetation Health Index", "Agricultural Stress Index", "dekadal (10 days) time series" ], "issued": "2022-05-02T04:09:32.000Z", "modified": "2026-11-03T03:23:04.844Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::weighted-mean-vegetation-health-index-global-dekadal-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/MVHI_D/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=afd124844ba84da69c2c533d4af10a58", "landingPage": "https://agriculture.africageoportal.com/content/esri::land-cover-classification-sentinel-2", "title": "Land Cover Classification (Sentinel-2)", "description": "

Land cover describes the surface of the earth. Land cover maps are useful in urban planning, resource management, change detection, agriculture, and a variety of other applications in which information related to earth surface is required. Land cover classification is a complex exercise and is hard to capture using traditional means. Deep learning models are highly capable of learning these complex semantics, giving superior results.
 

Using the model

Follow the guide to use the model. Before using this model, ensure that the supported deep learning libraries are installed. For more details, check Deep Learning Libraries Installer for ArcGIS.

Fine-tuning the model

This model can be fine-tuned using the Train Deep Learning Model tool. Follow the guide to fine-tune this model.
 

Input

Raster, mosaic dataset, or image service. (Preferred cell size is 10 meters.)
Note: This model is trained to work on Sentinel-2 Imagery datasets which are in WGS 1984 Web Mercator (auxiliary sphere) coordinate system (WKID 3857).
 
Output

Classified raster with the same classes as in Corine Land Cover (CLC) 2018. 

Applicable geographies
This model is expected to work well in Europe and the United States.

Model architecture
This model uses the UNet model architecture implemented in ArcGIS API for Python.
 
Accuracy metrics

This model has an overall accuracy of 82.41% with Level-1C imagery and 84.0% with Level-2A imagery, for CLC class level 2 classification (15 classes). The table below summarizes the precision, recall and F1-score of the model on the validation dataset.

 

ClassLevel-2A ImageryLevel-1C Imagery
PrecisionRecallF1 ScorePrecisionRecallF1 Score
Urban fabric0.810.830.820.820.840.83
Industrial, commercial and transport units0.740.650.690.730.660.7
Mine, dump and construction sites0.630.520.570.690.550.61
Artificial, non-agricultural vegetated areas0.700.460.550.670.470.55
Arable land0.860.900.880.860.890.87
Permanent crops0.760.730.740.750.710.73
Pastures0.750.710.730.740.710.73
Heterogeneous agricultural areas0.610.560.580.620.510.56
Forests0.880.930.900.880.920.9
Scrub and/or herbaceous vegetation associations0.740.690.720.730.670.7
Open spaces with little or no vegetation0.870.840.850.850.820.84
Inland wetlands0.810.780.800.820.770.79
Maritime wetlands0.740.760.750.870.890.88
Inland waters0.940.920.930.940.910.92
Marine waters0.980.990.980.970.980.98

 

This model has an overall accuracy of 90.79% with Level-2A imagery for CLC class level 1 classification (5 classes). The table below summarizes the precision, recall and F1-score of the model on the validation dataset.
 
ClassPrecisionRecallF1 Score
Artificial surfaces0.850.810.83
Agricultural areas0.900.910.91
Forest and semi natural areas0.910.920.92
Wetlands0.770.700.73
Water bodies0.960.970.96
 
Training data
This model has been trained on the Corine Land Cover (CLC) 2018 with the same Sentinel 2 scenes that were used to produce the database. Scene IDs for the imagery were available in the metadata of the dataset.


Sample results
Here are a few results from the model. To view more, see this story.


 


 

", "keyword": [ "land cover", "deep learning", "dlpk", "living atlas", "sentinel", "corine" ], "issued": "2021-02-17T07:21:35.000Z", "modified": "2026-09-01T07:11:48.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_analytics", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-125.4371,25.0695,42.4688,65.1465", "license": "

 This work is licensed under the Esri Master License Agreement

View Summary | View Terms of Use

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/content/esri::land-cover-classification-sentinel-2" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ddfce15a8ccd4c8c88fb125cb4f23cc9", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::world-surface-water", "title": "World Surface Water", "description": "
Water bodies are a key element in the landscape. This layer provides a global map of large water bodies for use in landscape-scale analysis.

Dataset Summary

This layer provides access to a 250m cell-sized raster of surface water created by extracting pixels coded as water in the Global Lithological Map and the Global Landcover Map. The layer was created by Esri in 2014.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. 

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started see the Living Atlas Discussion Group.

The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.
", "keyword": [ "landscape6", "esri_landscape", "landscape", "water" ], "issued": "2014-12-03T19:05:34.000Z", "modified": "2020-08-27T00:01:21.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0000,180.0000,89.0000", "license": "This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::world-surface-water" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Surface_Water/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=99b62cad21e74285b41bf4c1ca9b6922", "landingPage": "https://agriculture.africageoportal.com/maps/esri::monthly-evapotranspiration", "title": "Monthly Evapotranspiration", "description": "
Most of us understand the hydrologic cycle in terms of the visible paths that water can take such as rainstorms, rivers, waterfalls and lakes. However, an even larger volume of water flows through the air all around us in two invisible paths: evaporation and transpiration. These two paths together are referred to as evapotranpsiration (ET), and claim 61% of all terrestrial precipitation. Solar radiation, air temperature, wind speed, soil moisture, and land cover all affect the rate of evapotranspiration, which is a major driver of the global water cycle, and key component of most catchments' water budget. This map contains a historical record showing the volume of water lost to evapotranspiration during each month from March 2000 to the present (NASA sometimes has a lag of several months in generating the data). 
 
Dataset Summary
The GLDAS Evapotranspiration layer is a time-enabled image service that shows total actual evapotranspiration monthly from 2000 to the present, measured in millimeters of water loss. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. 
 

What can you do with this layer?
This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales. 

Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.
 

Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.
 

 
 
", "keyword": [ "GLDAS", "NOAH", "NASA", "ET", "earth observations" ], "issued": "2014-06-27T03:25:31.000Z", "modified": "2026-06-30T14:29:26.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_observations", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-11.3513,21.7453,64.9977", "license": "This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/maps/esri::monthly-evapotranspiration" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=01fa55f171eb48a7ac9c460c0339e6c1", "landingPage": "https://agriculture.africageoportal.com/maps/esri::monthly-precipitation", "title": "Monthly Precipitation", "description": "
Precipitation is water released from clouds in the form of rain, sleet, snow, or hail. It is the primary source of recharge to the planet's fresh water supplies. This map contains a historical record showing the volume of precipitation that fell during each month from March 2000 to the present. Snow and hail are reported in terms of snow water equivalent - the amount of water that will be produced when they melt.
 
Dataset Summary
The GLDAS Precipitation layer is a time-enabled image service that shows average monthly precipitation from 2000 to the present, measured in millimeters. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-1). The model is run with 3-hourly time steps and aggregated into monthly averages. 

 

What can you do with this layer?
This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales.

Time: This is a time-enabled layer. It shows the total evaporative loss during the map's time extent, or if time animation is disabled, a time range can be set using the layer's multidimensional settings. The map shows the sum of all months in the time extent. Minimum temporal resolution is one month; maximum is one year.

Variables: This layer has two variables: rainfall and snowfall. By default the two are summed, but you can view either by itself using the multidimensional filter. You must disable time animation on the layer before using its multidimensional filter.

Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.

 
", "keyword": [ "NOAH", "NASA", "GLDAS", "Precip", "Rain", "Ranfall", "snow", "Snowfall", "earth observations" ], "issued": "2015-06-24T00:55:17.000Z", "modified": "2026-06-30T14:27:02.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_observations", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-82.5861,180.0000,88.0753", "license": "This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/maps/esri::monthly-precipitation" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=706f312ecc13497e917ff72792276e8b", "landingPage": "https://agriculture.africageoportal.com/datasets/NASA::burn-scar-corrected-reflectance-viirs-noaa-20", "title": "Burn Scar - Corrected Reflectance (VIIRS / NOAA-20)", "description": "
Visualization Overview
This visualization represents a global \"false color\" band combination (Red = M11, Green = I2, Blue = I1) of data collected by the VIIRS instrument on NOAA’s Joint Polar Satellite System (JPSS-1) satellite, which was renamed to NOAA-20 once on orbit. The intended use of the imagery is for distinguishing burn scars from naturally low vegetation or bare soil and enhancing floods.  At its highest resolution, this visualization represents the underlying data scaled to a resolution of 250m per pixel at the equator.
 
The VIIRS Corrected Reflectance product retains visible aerosols for a natural-looking visualization, though gross atmospheric effects (e.g. Rayleigh scattering) have been removed. The following guidelines will aid in understanding this visualization.  See here for additional information on how this \"false color\" band combination highlights these physical characteristics of the Earth.
Multi-Spectral Bands
The following table lists the VIIRS bands that are utilized to create this visualization.  See here for a full description of all VIIRS bands.

 

Band

Description

Wavelength (µm)

Resolution (m)

I1

Visible / Reflective (Red)

 

0.60 - 0.68 

375

 

I2

Near IR (Green)

0.85 - 0.88

 

375

 

M11

Shortwave IR

 

2.23 - 2.28

 

750

 

Temporal Coverage and Limitations of Use

By default, this layer will display the imagery currently available for today’s date.  The update frequency is a \"daily composite\" that is assembled from hundreds of individual data files.  When viewing imagery for “today,” you may notice that only a portion of the map has imagery.  This is because the visualization is continually updated as the satellite collects more data.  To view imagery over time, you can update the layer properties to enable time animation and configure time settings.  Vintage: currently, this layer is available from present back to April 25th, 2020.  In the coming months, this will be extended to the start of the mission (November 18th, 2017).
 
Source: NASA Global Imagery Browse Services (GIBS), NASA Worldview, & NASA LANCE
This visualization is provided through the NASA Global Imagery Browse Services (GIBS), which are a set of standard services to deliver global, full-resolution satellite imagery for hundreds of NASA Earth science datasets and science parameters.  Through its services, and the NASA Worldview client, GIBS enables interactive exploration of NASA's Earth imagery for a broad range of users.  The data and imagery are generated within 3 hours of acquisition through the NASA LANCE capability.
 
Esri and NASA Collaborative Services
This visualization is made available through an ArcGIS image service hosted on Esri servers and facilitates access to a NASA GIBS service endpoint. For each image service request, the Esri server issues multiple requests to the GIBS service, processes and assembles the responses, and returns a proper mosaic image to the user.  Processing occurs on-the-fly for each and every request to ensure that any update to the GIBS imagery is immediately available to the user.  As such, availability of this visualization is dependent on both the Esri and the NASA GIBS services.
", "keyword": [ "GIBS", "NASA", "NOAA-20", "JPSS-1", "VIIRS", "Burn Scar", "fires", "false color", "near real-time" ], "issued": "2020-12-10T12:49:14.000Z", "modified": "2026-11-11T16:01:34.568Z", "publisher": { "name": "NASA Global Imagery Browse Services (GIBS)" }, "contactPoint": { "@type": "vcard:Contact", "fn": "NASA_Earthdata", "hasEmail": "mailto:hq-smd-esri-software-support@mail.nasa.gov" }, "accessLevel": "public", "spatial": "-180.0000,-89.9500,180.0000,89.9500", "license": "
NASA Earth Science Data and Information Policy

We ask that users include the following acknowledgement in written or oral presentations referencing this visualization product:

We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Observing System Data and Information System (EOSDIS).
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/NASA::burn-scar-corrected-reflectance-viirs-noaa-20" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://modis.arcgis.com/arcgis/rest/services/VIIRS/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=cb9b8147275c4b7c91b6492e68b018a5", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::crop-and-pasture-phenology-progress-of-season-global-1-km-fao-asis", "title": "Crop and Pasture Phenology - Progress of Season (Global - 1 km) - FAO ASIS", "description": "
Crop/Pasture Phenology is a set of reference datasets developed and used by ASIS, consisting of two global products: Start/Maximum/End of Season and Progress of Season.
 
Phenology is defined as the study of the timing of recurring biological cycles and their connection to the climate. Changes in the vegetation phenology, including the start of season, the length of the season as well as the end of season impacts the ecosystem functioning such as carbon storage, water holding capacity and agricultural productivity.
 
Phenomenon Mapped: Crop and Pasture Phenology - Progress of Season (dekadal)
Units: Percentage
Pixel Type: 32-bit Signed Integer
Last updated: 2017
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: Reference layer, updated as needed. 
 
Compliment to ASIS Crop/pasture growing seasons (Start of season, Maximum of season and End of Season) maps, Progress of Season (POS) maps depict the development of crops/pastures during the growing season. For any dekad (a 10-day period), the map indicates how far the season has progressed, represented by a value between 0 and 100 percent (i.e. 50 percent is the mid-point of the growing season). The seasons’ progress is based on the long-term average of vegetation phenology for each pixel. This simplification implies that the crop/pasture phenology is static and, therefore, the growing seasons progress at a constant rate each year.
 
The “seasonal progress” is expressed in relative terms via a fixed set of “POS images”. For any dekad in the year, they indicate for each pixel how the season has progressed. That can be a value between 0 and 100 percent (i.e. 50 percent is the mid-point of the growing season).
 
The definition of a dekad:
 
o Each month has three dekads: dekad 1 (day 1-10), dekad 2 (day 11-20), dekad 3 (day 21-end of month). o The number of days the dekad represents is variable for each last dekad of the month. o Since the phenology is derived from dekadal temporally smoothed and gap filled NDVI data, these dekads represent +- the middle day of their period. o The best practice is to link each dekad value with its associated date (e.g. Dekad 1 = January 5th/6th, dekad 3 = January 26th,…). Then you can convert these dates into Julian days.
 
Phenology digital values to physical values:
 
o In order to deal with growing seasons surpassing the calendar year (e.g. SOS December) the phenology data is stored in a range of 108 dekads. The digital values in images follow the 1-108 dekad range. There is an offset of 36 dekads in order to express them with the target year as reference.
o Dekad 37-72 represents the dekad 1-36 (January – December) of the target year. Values lower than 36 indicate SOS phenology < January and values higher than 72 indicate EOS phenology > December.
 
Global ASIS covers two crop/pasture seasons. Some countries have three or four crop seasons within a crop year. For these countries, Global ASIS cannot properly capture the crop phenology between the first and the last season (e.g. for a country has four crop seasons, the crop phenology of the 2nd and 3rd season).
 
Explore this and related data in this web application.
 
More information please visit FAO GIEWS Earth Observation website
 
", "keyword": [ "ASIS", "crop phenology", "crop calendar", "crop growing season", "FAO GIEWS", "EO-based crop monitoring", "crop monitoring", "crop growing stage" ], "issued": "2022-05-02T04:18:39.000Z", "modified": "2026-06-05T12:20:09.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::crop-and-pasture-phenology-progress-of-season-global-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/PRO/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=deeb08e37c474f069ae7a95ba5d1e97e", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-condition-index-global-monthly-1-km-fao-asis", "title": "Vegetation Condition Index (Global - Monthly -1 km) - FAO ASIS", "description": "
The Vegetation Condition Index (VCI) evaluates the current vegetation health in comparison to the historical trends. The VCI relates current dekadal Normalized Difference Vegetation Index (NDVI) to its long-term minimum and maximum, normalized by the historical range of NDVI values for the same dekad. The VCI was designed to separate the weather-related component of the NDVI from the ecological element. 𝑉𝐶𝐼𝑖=(𝑁𝐷𝑉𝐼𝑖−𝑁𝐷𝑉𝐼𝑚𝑖𝑛) / (𝑁𝐷𝑉𝐼𝑚𝑎𝑥−𝑁𝐷𝑉𝐼𝑚𝑖𝑛).
 

Phenomenon Mapped: Vegetation Condition Index

Units: None

Time Interval: 1-month

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: Monthly + 3-4 days lag


 

Together with Temperature Condition Index (TCI), Vegetation Condition Index (VCI) is used to calculate Vegetation Health Index (VHI) using formula: VHI=0.5VCI+0.5TCI
 
 
In ASIS, VCI is computed in two temporal granularities: dekadal and monthly. The dekadal/monthly VCI raster layer published is further updated in the following 5 dekads (improve data precision, remove cloud pixel etc.).
 
Flags of raster file: 251=missing, 252=cloud, 253=snow, 254=sea, 255=background
 
 
Explore this and related data in this web application.
 
 
More information please visit FAO GIEWS Earth Observation website
 
 
", "keyword": [ "FAO GIEWS", "ASIS", "Global extent", "1 km resolution", "Near real time", "10 days", "EO-based crop monitoring", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Non-seasonal Indictor", "Vegetation Condition Index", "VCI", "NDVI", "NDVI Anomaly", "monthly time series" ], "issued": "2022-05-02T04:24:21.000Z", "modified": "2026-06-05T12:16:44.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-condition-index-global-monthly-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/VCI_M/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=dd1ddf044a7f4d28972cd7644aceaddc", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-condition-index-global-dekadal-1-km-fao-asis", "title": "Vegetation Condition Index (Global - Dekadal - 1 km ) - FAO ASIS", "description": "
The Vegetation Condition Index (VCI) evaluates the current vegetation health in comparison to the historical trends. The VCI relates current dekadal Normalized Difference Vegetation Index (NDVI) to its long-term minimum and maximum, normalized by the historical range of NDVI values for the same dekad. The VCI was designed to separate the weather-related component of the NDVI from the ecological element. 𝑉𝐶𝐼𝑖=(𝑁𝐷𝑉𝐼𝑖−𝑁𝐷𝑉𝐼𝑚𝑖𝑛) / (𝑁𝐷𝑉𝐼𝑚𝑎𝑥−𝑁𝐷𝑉𝐼𝑚𝑖𝑛)
 

Phenomenon Mapped: Vegetation Condition Index

Units: None

Time Interval: 10-day

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: 10-day + 3-4 days lag

 
Together with Temperature Condition Index (TCI), Vegetation Condition Index (VCI) is used to calculate Vegetation Health Index (VHI) using formula: VHI=0.5VCI+0.5TCI
 
In ASIS, VCI is computed in two temporal granularities: dekadal and monthly. The dekadal/monthly VCI raster layer published is further updated in the following 5 dekads (improve data precision, remove cloud pixel etc.).
 
Flags of raster file: 251=missing, 252=cloud, 253=snow, 254=sea, 255=background
 
Explore this and related data in this web application
 
 
More information please visit FAO GIEWS Earth Observation website
 
 
", "keyword": [ "ASIS", "Agricultural drought", "Vegetation Condition Index", "FAO GIEWS", "1 km resolution", "Near real time", "EO-based crop monitoring", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Non-seasonal Indictor", "NDVI Anomaly", "NDVI", "dekadal (10 days) time series" ], "issued": "2022-05-02T04:23:27.000Z", "modified": "2026-11-03T05:20:59.142Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-condition-index-global-dekadal-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/VCI_D/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=2bda7de8825d46f895e2486dc0ad733f", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::weighted-mean-vegetation-health-index-annual-update", "title": "Weighted Mean Vegetation Health Index (Annual Update)", "description": "

The Annual Weighted Mean Vegetation Health Index (Weighted Mean\nVHI) allows the user to assess the overall severity of drought for an entire\ngrowing season, examining the vegetation health and the influence of\ntemperature on plant conditions. The Annual Weighted\nMean VHI takes into account the sensitivity of a crop to water stress over its\ngrowing season, and calculates the temporal impact of moisture deficits and\ntemperature over the complete growing season.

Phenomenon Mapped: Weighted Mean Vegetation Health Index

Units: non

Time Interval: 1-year

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: Annual, 5th of July for the previous crop year

Mean VHI Annual Summary is processed at the end of crop season. It allows the user to assess the overall severity of drought for an entire growing season. 

Two quick-look indicators in ASIS: Agricultural Stress Index (ASI) and Drought Intensity are both based on Weighted Mean-VHI dataset.

Explore this and related data in this web application.

More information\nplease visit FAO GIEWS Earth Observation website

", "keyword": [ "ASIS", "agricultural drought", "vegetation health index", "food security", "early warning", "weighted mean Vegetation Health Index", "Seasonal Indictor", "annual time series", "Global extent", "FAO GIEWS", "NDVI Anomaly" ], "issued": "2022-05-02T04:08:39.000Z", "modified": "2026-06-05T12:09:47.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::weighted-mean-vegetation-health-index-annual-update" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/MVHI_A/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7b2558cf40334a309a7dd2ad99f50318", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::agricultural-stress-index-global-annual-1-km-fao-asis", "title": "Agricultural Stress Index (Global - Annual - 1 km ) - FAO ASIS", "description": "

The Agricultural\nStress Index (ASI) is a quick-look indicator that facilitates the early\nidentification of cropped land with a high likelihood of water stress\n(drought). ASI related products (maps, spatial aggregation based on\nadministrative unit) are processed by FAO GIEWS (Global Information and Early\nWarning System on Food and Agriculture) every 10 days.

ASI Annual Summary\nis processed at the end of crop season, globally defined as 30 June. It depicts the percentage of arable\nland, within an administrative area, that has been affected by drought\nconditions over the entire cropping season. It differs from ASI dekadal product\n(10-days), which is based on conditions from the start of the season up to the\ncurrent dekad.

Phenomenon Mapped: Agricultural Stress Index 

Units: Percent

Time Interval: 1-year

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture\nOrganization of the United Nations

Update Cycle: Annual, 5th of July for the previous crop year

The Index is based on the integration of the Vegetation\nHealth Index (VHI) in two dimensions that are critical in the assessment of a\ndrought event in agriculture: temporal and spatial. The first step of the ASI\ncalculation is a temporal averaging of the VHI, assessing the intensity and\nduration of dry periods occurring during the crop cycle at the pixel level;\nthis calculation includes the use of crop coefficients, which introduces\nsensitivity of a crop to water stress during each phenological phase. The\nsecond step determines the spatial extent of drought events by calculating the\npercentage of pixels in arable areas with a VHI value below 35 percent (this\nvalue was identified as a critical threshold in assessing the extent of drought\nin previous research by Kogan, 1995). Each administrative area is classified\naccording to the percentage of the affected area to facilitate the quick\ninterpretation of results.

This index is computed in two\ntemporal granularities: Near Real Time (10 days) and Annual Summary. Historic Drought Frequency dataset is also computed based\non the entire ASI Annual Summary datasets (1984-2021).


Explore this and related data in this web application.

More information please\nvisit FAO GIEWS Earth Observation\nwebsite

\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n


\n\n
", "keyword": [ "ASIS", "Agricultural drought", "crop monitoring", "food security", "Early warning", "FAO GIEWS", "Global extent", "Near real time", "Annual data", "EO-based crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Seasonal Indictor", "Agricultural Stress Index", "Severe drought" ], "issued": "2022-05-02T03:48:00.000Z", "modified": "2026-06-05T12:08:49.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::agricultural-stress-index-global-annual-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/ASI_A/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6198ef41d55646d3a37aec0b1e65357e", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::drought-intensity-global-annual-1-km-fao-asis", "title": "Drought Intensity (Global - Annual - 1 km) - FAO ASIS", "description": "
Complementary to Agricultural Stress Index (ASI) which detects the severe and extreme drought, Drought Intensity is another quick-look indicator in ASIS that facilitates the early understanding of the intensity of the drought. It is an indicator introduced in 2018.

Agricultural droughts are classified by their intensity and are categorized into four classes: Extreme, Severe, Moderate or Mild. The intensity of drought in ASIS is calculated through the weighted Mean Vegetation Health Index, indicating that the poorer the vegetation health the more severe the drought.

Phenomenon Mapped: Drought Intensity
Units: non
Time Interval: 1-year
Time Extent: 1984-Present
Cell Size: 1 km
Pixel Type: 32-bit Signed Integer
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: Annual, 5th of July for the previous crop year

The Annual summary of Drought Intensity is processed at the end of crop season. It allows the user to assess the overall intensity of drought for an entire growing season. It differs from Drought Intensity dekadal product, which is based on conditions from the start of the season up to the current dekad.

Important note: Map legend value= Pixel physical value * multiplier (100), except 251: off season, 252: no data, 253: no season and 254: no crop land, 255: water.

Explore this and related data in this web application.

More information\nplease visit FAO GIEWS Earth Observation website

", "keyword": [ "ASIS", "agricultural drought", "drought intensity", "crop monitoring", "food security", "early warning", "FAO GIEWS", "Global extent", "1 km resolution", "Near real time", "EO-based crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "annual time series" ], "issued": "2022-05-02T03:54:59.000Z", "modified": "2026-06-05T12:07:36.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::drought-intensity-global-annual-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/DI_A/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=3288ac0d56fe415db846770782a4da45", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::drought-intensity-global-dekadal-1-km-fao-asis", "title": "Drought Intensity (Global - Dekadal - 1 km) - FAO ASIS", "description": "
Complementary to Agricultural Stress Index (ASI) which detects the severe and extreme drought, Drought Intensity is another quick-look indicator in ASIS that facilitates the early understanding of the intensity of the drought. 
 
Agricultural droughts are classified by their intensity and are categorized into four classes: Extreme, Severe, Moderate or Mild. The intensity of drought in ASIS is calculated through the weighted Mean Vegetation Health Index, indicating that the poorer the vegetation health the more severe the drought. 
 
Phenomenon Mapped: Drought Intensity
Units: None
Time Interval: 10-day
Time Extent: 2010-Present
Cell Size: 1 km
Pixel Type: 32-bit Signed Integer
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: 10-days + 3-4 days lag
 
Drought Intensity dekadal product is processed based on the conditions from the start of the season up to the current dekad. If differs from Drought Intensity Annual product which describes the drought conditions over the entire crop season.
 
Important note: Map legend value= Pixel physical value * multiplier (100), except 251: off season, 252: no data, 253: no season and 254: no crop land, 255: water
 
Explore this and related data in this web application.
 
More information please visit FAO GIEWS Earth Observation website
 
 
", "keyword": [ "ASIS", "agricultural drought", "drought intensity", "near real time", "early warning", "food security", "FAO GIEWS", "Global extent", "1 km resolution", "Near real time", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Seasonal Indictor", "dekadal (10 days) time series" ], "issued": "2022-05-02T03:56:30.000Z", "modified": "2026-11-03T03:23:05.017Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::drought-intensity-global-dekadal-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/DI_D/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=dd6297fa2d6d462a8f85e769b7cf4805", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-health-index-global-dekadal-1-km-fao-asis", "title": "Vegetation Health Index (Global - Dekadal - 1 km) - FAO ASIS", "description": "
The Vegetation Health Index (VHI) illustrates the severity of drought based on the vegetation health and the influence of temperature on plant conditions. The VHI is a composite index and the elementary indicator used to compute the seasonal drought indicators in ASIS: Agricultural Stress Index (ASI), Drought Intensity and Weighted Mean Vegetation Health Index (Mean VHI).

If the index is below 40, different levels of vegetation stress, losses of crop and pasture production might be expected; if the index is above 60 (favorable condition) plentiful production might be expected. VHI is very useful for an advanced prediction of crop losses.

Phenomenon Mapped: Vegetation Health Index

Units: None

Time Interval: 10-day

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: 10-days + 3-4 days lag

 
VHI combines both the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI). The TCI is calculated using a similar equation to the VCI, but relates the current temperature to the long-term maximum and minimum, as it is assumed that higher temperatures tend to cause a deterioration in vegetation conditions. A decrease in the VHI would, for example, indicate relatively poor vegetation conditions and warmer temperatures, signifying stressed vegetation conditions, and over a longer period would be indicative of drought.
 
In ASIS, VHI is computed in two temporal granularities: dekadal and monthly. The dekadal/monthly VHI raster layer published is further updated in the following 5 dekads (improve data precision, remove cloud pixel etc.).
 
Flags of raster file: 251=missing, 252=cloud, 253=snow, 254=sea, 255=background
 
Explore this and related data in this web application
 
 
More information please visit FAO GIEWS Earth Observation website.
 
 
", "keyword": [ "FAO GIEWS", "Global extent", "1 km resolution", "Near real time", "EO-based crop monitoring", "ASIS", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Non-seasonal Indictor", "Vegetation Health Index", "VHI", "NDVI Anomaly", "dekadal (10 days) time series" ], "issued": "2022-05-02T04:25:36.000Z", "modified": "2026-11-03T03:23:05.019Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-health-index-global-dekadal-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/VHI_D/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=71a7a03a60e44734adf8c2bab91600f5", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::historic-drought-frequency-global-1-km-fao-asis", "title": "Historic Drought Frequency (Global - 1 km) - FAO ASIS", "description": "
Historic Agricultural Drought Frequency Maps depict the frequency of severe drought in areas where 30 percent/50 percent of the cropland/grassland has been affected. The historical frequency of severe droughts (as defined by ASI) is based on the entire ASI times series (1984-2024).
 
Phenomenon Mapped: Historic Drought Frequency
Units: Frequency (percentage)
Time Interval: Multi-annual
Time Extent: 1984-2024
Cell Size: 1 km
Pixel Type: 32-bit Signed Integer
Data Projection: WGS 1984
Mosaic Projection: WGS 1984 Web Mercator
Source: Food and Agriculture Organization of the United Nations
Update Cycle: Annual, 5th of July for the previous crop year
 
Formula: The number of years when land affected>30 percent/50 percent occurred/(2023-1984+1) *100
 
Pixel value ranges from 0-100 (unit: percentage). Flag: 252: no data; 253: no season; 254: no cropland/grassland.
 
Explore this and related data in this web application.
 
More information please visit FAO GIEWS Earth Observation website
 
", "keyword": [ "ASIS", "FAO GIEWS", "1 km resolution", "Global extent", "EO-based crop monitoring", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Seasonal Indictor", "Historic Drought Frequency", "Agricultural Stress Index" ], "issued": "2022-05-02T04:07:43.000Z", "modified": "2026-06-05T09:55:30.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::historic-drought-frequency-global-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/HDF/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=570e8c8c7cc14b5bb1b2e027ddf34bac", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-health-index-global-monthly-1-km-fao-asis", "title": "Vegetation Health Index (Global - Monthly - 1 km) - FAO ASIS", "description": "
The Vegetation Health Index (VHI) illustrates the severity of drought based on the vegetation health and the influence of temperature on plant conditions. The VHI is a composite index and the elementary indicator used to compute the seasonal drought indicators in ASIS: Agricultural Stress Index (ASI), Drought Intensity and Weighted Mean Vegetation Health Index (Mean VHI).

If the index is below 40, different levels of vegetation stress, losses of crop and pasture production might be expected; if the index is above 60 (favorable condition) plentiful production might be expected. VHI is very useful for an advanced prediction of crop losses.

Phenomenon Mapped: Vegetation Health Index

Units: None

Time Interval: 1 month

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: Monthly + 3-4 days lag

 

VHI combines both the Vegetation Condition Index (VCI) and the Temperature Condition Index (TCI). The TCI is calculated using a similar equation to the VCI, but relates the current temperature to the long-term maximum and minimum, as it is assumed that higher temperatures tend to cause a deterioration in vegetation conditions. A decrease in the VHI would, for example, indicate relatively poor vegetation conditions and warmer temperatures, signifying stressed vegetation conditions, and over a longer period would be indicative of drought.
 

 
In ASIS, VHI is computed in two temporal granularities: decadal (10-day) and monthly. The decadal/monthly VHI raster layer published is further updated in the following 5 dekads (improve data precision, remove cloud pixel etc.).
 
Flags of raster file: 251=missing, 252=cloud, 253=snow, 254=sea, 255=background
 
Explore this and related data in this web application
 
 
More information please visit FAO GIEWS Earth Observation website. 
 
", "keyword": [ "Agricultural drought", "ASIS", "Agricultral drought monitoring", "Vegetation Health Index", "VHI", "Global extent", "Near real time", "FAO GIEWS", "EO-based crop monitoring", "EO-based agricultural drought monitoring", "Non-seasonal Indictor", "monthly time series" ], "issued": "2022-05-02T04:26:30.000Z", "modified": "2026-06-05T09:54:10.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::vegetation-health-index-global-monthly-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/VHI_M/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=bca45971e87e46c182fbd048d3aee4ff", "landingPage": "https://agriculture.africageoportal.com/datasets/hqfao::agricultural-stress-index-near-real-time-global-dekadal-1-km-fao-asis", "title": "Agricultural Stress Index near real time (Global - Dekadal - 1 km ) - FAO ASIS", "description": "
Agricultural Stress Index (ASI) is a quick-look indicator that facilitates the early identification of cropped land with a high likelihood of water stress (drought). It depicts the percentage of arable land, within an administrative area, that has been affected by drought conditions from the start of the season up to the current dekad. It differs from ASI Annual product which describes the drought conditions over the entire crop season.

Phenomenon Mapped: Agricultural Stress Index 

Units: Percent

Time Interval: 10-day

Time Extent: 1984-Present

Cell Size: 1 km

Pixel Type: 32-bit Signed Integer

Data Projection: WGS 1984

Mosaic Projection: WGS 1984 Web Mercator

Source: Food and Agriculture Organization of the United Nations

Update Cycle: 10-days + 3-4 days lag

 

The Index is based on the integration of the Vegetation Health Index (VHI) in two dimensions that are critical in the assessment of a drought event in agriculture: temporal and spatial. The first step of the ASI calculation is a temporal averaging of the VHI, assessing the intensity and duration of dry periods occurring during the crop cycle at the pixel level; this calculation includes the use of crop coefficients, which introduces sensitivity of a crop to water stress during each phenological phase. The second step determines the spatial extent of drought events by calculating the percentage of pixels in arable areas with a VHI value below 35 percent (this value was identified as a critical threshold in assessing the extent of drought in previous research by Kogan, 1995). Each administrative area is classified according to the percentage of the affected area to facilitate the quick interpretation of results.
 
This index is computed in two temporal granularities: Near Real Time (10 days) and Annual Summary. Historic Drought Frequency dataset is also computed based on the entire ASI Annual Summary datasets (1984-2024).
 
 
Explore this and related data in this web application.
 
More information please visit FAO GIEWS Earth Observation website
 
 
 
", "keyword": [ "ASIS", "Agricultural Stress", "Dekadal Estimates", "Agricultural drought", "food security", "early warning", "FAO GIEWS", "Global extent", "1 km resolution", "Near real time", "10 days", "EO-based crop monitoring", "crop monitoring", "EO-based agricultural drought monitoring", "Agricultural drought monitoring", "Seasonal Indictor" ], "issued": "2022-05-02T03:52:57.000Z", "modified": "2026-11-03T05:59:36.141Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "giews_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "-180.0000,-56.0057,180.0000,75.0045", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/hqfao::agricultural-stress-index-near-real-time-global-dekadal-1-km-fao-asis" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://asis-esri.fao.org/image/rest/services/ASI_D/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=9b1cefacf7be47ab93c2dab2e2f24d68", "landingPage": "https://agriculture.africageoportal.com/datasets/9b1cefacf7be47ab93c2dab2e2f24d68", "title": "{{name}}", "description": "{{description}}", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:43:28.000Z", "modified": "{{modified:toISO}}", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/9b1cefacf7be47ab93c2dab2e2f24d68" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=0e71d0e63c494d75b2bc897b7515f89a", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-chemistry-mature-support", "title": "World Soils Harmonized World Soil Database - Chemistry (Mature Support)", "description": "Important Note: This item is in mature support as of April 2024 and will be retired in December 2026. Please use the following layers as replacements: World Soils 250m pH, World Soils 250m Cation Exchange Capacity, World Soils 250m Nitrogen, World Soils 250m Organic Carbon Density, World Soils 250m Organic Carbon Stocks, World Soils 250m Soil Organic Carbon. Esri recommends updating your maps and apps to use the new version.
   
Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.

The mineral composition of underlying rock, the amount and type of organic material from plants and climatic and other environmental factors affect the chemistry of the soil. Chemical composition and processes determine how and what type of soil forms at a given location and what type of agriculture the areas wil support.

Dataset Summary

This layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes related to the chemistry of soil derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).

Fields for topsoil (0-30 cm) and subsoil (30-100 cm) are available for each of these soil chemistry attributes:
  • Organic Carbon - % weight
  • Calcium Carbonate - % weight
  • Gypsum - % weight
  • Salinity - Electrical Conductivity - dS/m
  • pH
Additionally, 4 class description fields were added by Esri based on the document Harmonized World Soil Database Version 1.2 for use in web map pop-ups:
  • pH Class Description
  • Calcium Carbonate Class Description
  • Gypsum Class Description
  • Salinity - Electrical Conductivity - Class Description
The layer is symbolized with the Topsoil pH field.

The document Harmonized World Soil Database Version 1.2 provides more detail on the soil chemistry attributes contained in this layer.

Other attributes contained in this layer include:
  • Soil Mapping Unit Name - the name of the spatially dominant major soil group
  • Soil Mapping Unit Symbol - a two letter code for labeling the spatially dominant major soil group in thematic maps
  • Data Source - the HWSD is an aggregation of datasets. The data sources are the European Soil Database (ESDB), the 1:1 million soil map of China (CHINA), the Soil and Terrain Database Program (SOTWIS), and the Digital Soil Map of the World (DSMW).
  • Percentage of Mapping Unit covered by dominant component
More information on the Harmonized World Soil Database is available here.

Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:


The authors of this data set request that projects using these data include the following citation:

FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. 

The source data for this layer are available here. 

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:
The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.
", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:43:32.000Z", "modified": "2024-04-26T03:44:44.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0001,180.0000,89.0000", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-chemistry-mature-support" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Soils_HWSD_Chemistry/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=85e74e0afd044ebba2d113ae1e95d6bb", "landingPage": "https://agriculture.africageoportal.com/datasets/85e74e0afd044ebba2d113ae1e95d6bb", "title": "{{name}}", "description": "{{description}}", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:43:40.000Z", "modified": "{{modified:toISO}}", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/85e74e0afd044ebba2d113ae1e95d6bb" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=af37c984900c48618b158352fb41da4d", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-general-mature-support", "title": "World Soils Harmonized World Soil Database - General (Mature Support)", "description": "Important Note: This item is in mature support as of April 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.
   
Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.

Dataset Summary

This layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes describing the basic properties of soil derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).

Attributes in this layer include:

Additionally, 3 class description fields were added by Esri based on the document Harmonized World Soil Database Version 1.2 for use in web map pop-ups:

The layer is symbolized with the Soil Unit Name field.

The document Harmonized World Soil Database Version 1.2 provides more detail on the soil properties attributes contained in this layer.

Other attributes contained in this layer include:
More information on the Harmonized World Soil Database is available here.

Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:

World Soils Harmonized World Soil Database - Bulk Density
World Soils Harmonized World Soil Database – Chemistry
World Soils Harmonized World Soil Database - Exchange Capacity
World Soils Harmonized World Soil Database – Hydric
World Soils Harmonized World Soil Database – Texture

The authors of this data set request that projects using these data include the following citation:

FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. 

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:
The Esri Insider Blog provides an introduction to the Ecophysiographic Mapping project.
", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:43:51.000Z", "modified": "2024-04-26T03:44:21.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0001,180.0000,89.0000", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-general-mature-support" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Soils_HWSD_General/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=233818f3e40a4bc39e4f8a942c19e6fb", "landingPage": "https://agriculture.africageoportal.com/datasets/233818f3e40a4bc39e4f8a942c19e6fb", "title": "{{name}}", "description": "{{description}}", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:44:03.000Z", "modified": "{{modified:toISO}}", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/233818f3e40a4bc39e4f8a942c19e6fb" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=aa9a3a2dc6924f46adc5a999787f7961", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-texture-mature-support", "title": "World Soils Harmonized World Soil Database - Texture (Mature Support)", "description": "Important Note: This item is in mature support as of April 2024 and will be retired in December 2026. Please use the following layers at replacements: World Soils 250m Percent Sand, World Soils 250m Percent Silt, World Soils 250m Percent Clay. Esri recommends updating your maps and apps to use the new version.
   
Soil is a key natural resource that provides the foundation of basic ecosystem services. Soil determines the types of farms and forests that can grow on a landscape. Soil filters water. Soil helps regulate the Earth's climate by storing large amounts of carbon. Activities that degrade soils reduce the value of the ecosystem services that soil provides. For example, since 1850 35% of human caused green house gas emissions are linked to land use change. The Soil Science Society of America is a good source of of additional information.

Soil texture is an important factor determining which kinds of plants can be grown in a particular location. Texture determines a soil's susceptibility to erosion or compaction and how well a soil holds nutrients and water. For example sandy soils tend to be well drained and dry quickly often holding few nutrients while clay soils may hold much more water and many more plant nutrients.

Dataset Summary

This layer provides access to a 30 arc-second (roughly 1 km) cell-sized raster with attributes related to soil texture derived from the Harmonized World Soil Database v 1.2. The values in this layer are for the dominant soil in each mapping unit (sequence field = 1).

Fields for topsoil (0-30 cm) and subsoil (30-100 cm) are available for each of these attributes related to soil texture:
The layer is symbolized with the topsoil texture class.

The document Harmonized World Soil Database Version 1.2 provides more detail on the soil texture attributes contained in this layer.

Other attributes contained in this layer include:
  • Soil Mapping Unit Name - the name of the spatially dominant major soil group
  • Soil Mapping Unit Symbol - a two letter code for labeling the spatially dominant major soil group in thematic maps
  • Data Source - the HWSD is an aggregation of datasets. The data sources are the European Soil Database (ESDB), the 1:1 million soil map of China (CHINA), the Soil and Terrain Database Program (SOTWIS), and the Digital Soil Map of the World (DSMW).
  • Percentage of Mapping Unit covered by dominant component
More information on the Harmonized World Soil Database is available here.

Other layers created from the Harmonized World Soil Database are available on ArcGIS Online:


The authors of this data set request that projects using these data include the following citation:

FAO/IIASA/ISRIC/ISSCAS/JRC, 2012. Harmonized World Soil Database (version 1.2). FAO, Rome, Italy and IIASA, Laxenburg, Austria.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.
This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 16,000 x 16,000 pixels - an area 4,000 kilometers on a side or an area approximately the size of Europe. 

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.
", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2014-11-18T21:44:06.000Z", "modified": "2024-04-26T03:43:14.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-89.0001,180.0000,89.0000", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::world-soils-harmonized-world-soil-database-texture-mature-support" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Soils_HWSD_Texture/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ab06bbc6ecbb42d59d9379d4c64bf8a3", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-terrestrial-ecosystems", "title": "Africa Terrestrial Ecosystems", "description": "
Organisms and nonliving elements of the environment such as climate, soil, and water are connected through the movement of nutrients and energy in ecosystems. Ecosystems represent specific areas where organisms and environmental conditions create a network of interactions and are affected by forces such as disturbance and succession. 

Dataset Summary

This layer provides access to a 100m cell sized raster of Ecosystems of Africa. The layer’s attributes include macrogroup, division, formation, subclass, and class.

The layer was derived from data described in the publication A New Map of Standardized Terrestrial Ecosystems of Africa. The data covers the continent of Africa, Madagascar, and other nearby islands. The data were produced in 2013.

Layers that were used to create the ecosystems map are available on ArcGIS Online: 

     Africa Isobioclimates
     Africa Topographic Moisture Potential
     Africa Land Surface Forms
     Africa Surficial Lithology

Link to source metadata

What can you do with this layer?

This layer has query, identify, and export image services available.  The layer is restricted to a 24,000 x 24,000 pixel limit for these services, which represents an area roughly 2,400 kilometers on a side. The source data for this layer is available here. 

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.
", "keyword": [ "biological", "esri_landscape", "esri_earth", "terrestrial ecosystems", "ecology", "landscape5", "Africa", "landscape", "retiring-2026-12" ], "issued": "2014-05-21T16:21:30.000Z", "modified": "2019-12-18T17:00:17.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-terrestrial-ecosystems" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Terrestrial_Ecosystems/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=23605c21c353454892978587d1b3d8bb", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::gldas-evapotranspiration-2000-present", "title": "GLDAS Evapotranspiration 2000 - Present", "description": "
Most of us understand the hydrologic cycle in terms of the visible paths that water can take such as rainstorms, rivers, waterfalls and lakes. However, an even larger volume of water flows through the air all around us in two invisible paths: evaporation and transpiration. These two paths together are referred to as evapotranpsiration (ET), and claim 61% of all terrestrial precipitation. Solar radiation, air temperature, wind speed, soil moisture, and land cover all affect the rate of evapotranspiration, which is a major driver of the global water cycle, and key component of most catchments' water budget. This map contains a historical record showing the volume of water lost to evapotranspiration globally during each month from March 2000 to the present.

Dataset Summary

The GLDAS Evapotranspiration layer is a time-enabled image service that shows total actual evapotranspiration monthly from 2000 to the present, measured in millimeters of water loss. It is calculated by NASA using the Noah land surface model, run at 0.25 degree spatial resolution using satellite and ground-based observational data from the Global Land Data Assimilation System (GLDAS-2.1). The model is run with 3-hourly time steps and aggregated into monthly averages. Review the complete list of model inputs, explore the output data (in GRIB format), and see the full Hydrology Catalog for all related data and information!

Phenomenon Mapped: Evapotranspiration
Units: Millimeters
Time Interval: Monthly
Time Extent: 2000/01/01 to present
Cell Size: 28 km
Source Type: Scientific
Pixel Type: Signed Integer
Data Projection: GCS WGS84
Mosaic Projection: Web Mercator Auxiliary Sphere
Extent: Global Land Surface
Source: NASA
Update Cycle: Sporadic

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS for Desktop. It is useful for scientific modeling, but only at global scales. 

By applying the "Calculate Anomaly" processing template, it is also possible to view these data in terms of deviation from the mean. Mean evapotranspiration for a given month is calculated over the entire period of record - 2000 to present.

Time: This is a time-enabled layer. By default, it will show the first month from the map's time extent. Or, if time animation is disabled, a time range can be set using the layer's multidimensional settings. If you wish to calculate the average, sum, or min/max over the time extent, change the mosaic operator used to resolve overlapping pixels. In ArcGIS Online, you do this in the "Image Display Order" tab. In ArcGIS Pro, use the "Data" ribbon. In ArcMap, it is in the 'Mosaic' tab of the layer properties window. The minimum time extent is one month, and the maximum is 8 years. 

Important: You must switch from the cartographic renderer to the analytic renderer in the processing template tab in the layer properties window before using this layer as an input to geoprocessing tools.
", "keyword": [ "ET", "NOAH", "Actual Evapotranspiration", "earth observations", "NASA", "Evaporation", "Transpiration", "landscape", "climate", "weather", "earthobs2" ], "issued": "2015-06-30T21:18:02.000Z", "modified": "2022-04-14T20:58:00.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-60.0670,180.0000,89.0000", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::gldas-evapotranspiration-2000-present" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://earthobs2.arcgis.com/arcgis/rest/services/GLDAS_Evapotranspiration/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=db028cfc90a342d7b2f16ac7a9ad779b", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-wheat-harvested-area", "title": "Africa Crop Wheat - Harvested Area", "description": "
Wheat (Triticum spp.) is one of the world's most important crops. In the developing world only rice is more important as a food source. In Africa, Ethiopia and South Africa are important producers.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of wheat harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of wheat as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Maize (Corn)
Millet
Potato
Rice
Sorghum
Sweet Potato and Yam

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:40:17.000Z", "modified": "2019-12-20T06:13:24.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-wheat-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Wheat/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a2220563c2e04b99bbe600b0d192ac60", "landingPage": "https://agriculture.africageoportal.com/datasets/a2220563c2e04b99bbe600b0d192ac60", "title": "{{name}}", "description": "{{description}}", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:29.000Z", "modified": "{{modified:toISO}}", "publisher": { "name": "{{source}}" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/a2220563c2e04b99bbe600b0d192ac60" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=f64fbb5ac501469a8ae13543af55632b", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-sorghum-harvested-area", "title": "Africa Crop Sorghum - Harvested Area", "description": "
Sorghum (Sorghum bicolor) is an important grass species used for human and animal food. It was first cultivated in Africa and currently 53% of the world's production is in sub-Saharan Africa. Millions of farmers in arid regions rely on this crop due to its drought tolerant qualities.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of sorghum harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of sorghum as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Maize (Corn)
Millet
Potato
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:
", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:24.000Z", "modified": "2019-09-18T22:40:40.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-sorghum-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Sorghum/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a35b683f6ba045b2a4da4eacf58ea642", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-rice-harvested-area", "title": "Africa Crop Rice - Harvested Area", "description": "
Rice (Oryza sativa and O. glaberrima) is one of the world's most important staple food crops. Over half of the world's population relies on rice. The people in some parts of Africa have been cultivating rice for over 3,500 years.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of rice harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of rice as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Maize (Corn)
Millet
Potato
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

\n\n\n\n\n\n\n\n

", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:21.000Z", "modified": "2019-12-18T17:03:57.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-rice-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Rice/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a15e23a3fd734914a227b236e0ff715e", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-potato-harvested-area", "title": "Africa Crop Potato - Harvested Area", "description": "
Potato (Solanum tuberosum) a native of South America was first domesticated between 8000 and 5000 BC. In the middle of the 16th century it was introduced to Europe, Asia and Africa. Africa produces about 5% of the world's potato crop.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of potato harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of potato as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Maize (Corn)
Millet
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:18.000Z", "modified": "2019-12-18T17:04:32.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-potato-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Potato/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=5ef402b9fc2d4544bf72dfe740282bcf", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-millet-harvested-area", "title": "Africa Crop Millet - Harvested Area", "description": "
Millet is a group of grass species that produce small-seeded grains used for food and animal feed around the world. Common species include finger millet (Eleusine coracana), proso millet (Panicum miliaceum), pearl millet (Pennisetum glaucum), and foxtail millet (Setaria italica). Africa is a major producer growing 56% of the worlds millet. Pearl millet is an important food source in Africa and is known for its tolerance of hot and dry climates.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of millet harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of millet as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Maize (Corn)
Potato
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

Landscape Layers - a reintroduction
Living Atlas Discussion Group
", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:16.000Z", "modified": "2019-12-18T17:06:18.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-millet-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Millet/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=6fab7020446c43b0b44727d6cb134ae8", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-maize-harvested-area", "title": "Africa Crop Maize - Harvested Area", "description": "
Maize (Zea mays), also known as corn, is a crop of world wide importance. Originally domesticated in what is now Mexico, its tolerance of diverse climates has lead to its widespread cultivation. Globally, it is tied with rice as the second most widely grown crop. Only wheat is more widely grown. In Africa it is grown throughout the agricultural regions of the continent from the Nile Delta in the north to the country of South Africa in the south. In sub-Saharan Africa it is relied on as a staple crop for 50% of the population.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of maize harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of maize as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Cassava
Groundnut (Peanut)
Millet
Potato
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

", "keyword": [ "Landscpe", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:12.000Z", "modified": "2019-12-18T17:06:53.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-maize-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Maize/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b6ff9a8a0a134e308b1aa4b889a0fb74", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-groundnut-harvested-area", "title": "Africa Crop Groundnut - Harvested Area", "description": "
Groundnut (Arachis hypogaea), also known as peanut, is grown around the world in a broad region between 40 degrees north and south latitude. Originally from South America, major producers of groundnut include China, India and the United States. Producing 30% of Africa's total, Nigeria leads the continent's production followed by Senegal, Sudan, Ghana, and Chad. Groundnut is a valuable source of protein and oil. It has the additional benefit of enriching depleted soils by converting nitrogen from the air into a form that is required by most plants.

Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of groundnut harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of casava as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Groundnut (Peanut)
Maize (Corn)
Millet
Potato
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.

What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

Geonet is a good resource for learning more about landscape layers and the Living Atlas of the World. To get started follow these links:

Landscape Layers - a reintroduction
Living Atlas Discussion Group
", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:08.000Z", "modified": "2019-12-18T17:05:07.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-groundnut-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Groundnut/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=1f7863773c2649e5bb290b406c4d36f2", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-cassava-harvested-area", "title": "Africa Crop Cassava - Harvested Area", "description": "
Cassava (Manihot esculenta) also known as manioc in South America, is grown world-wide in tropical and sub-tropical regions providing an important staple for the diet of over half a billion people. It is drought tolerant and grows well in marginal soils. More than half of the world's cassava production is from Africa and Nigeria is the world's largest producer. In Ghana, cassava accounts for roughly 30% of the calories eaten. The root of the cassava plant must be prepared to remove harmful compounds prior to eating. 


Dataset Summary

This layer provides access to a 5 arc-minute (approximately 10 km at the equator) cell-sized raster of the 1999-2001 annual average area of cassava harvested in Africa. The data are in units of hectares/grid cell.

The SPAM 2000 v3.0.6 data used to create this layer were produced by the International Food Policy Research Institute in 2012. This dataset was created by spatially disaggregating national and sub-national harvest data using the Spatial Production Allocation Model. 
          
Link to source metadata

For more information about this dataset and the importance of casava as a staple food see the Harvest Choice webpage.

For data on other agricultural species in Africa see these layers:
Groundnut (Peanut)
Maize (Corn)
Millet
Potato
Rice
Sorghum
Sweet Potato and Yam
Wheat

Data for important agricultural crops in South America are available here.


What can you do with this layer?

This layer is suitable for both visualization and analysis. It can be used in ArcGIS Online in web maps and applications and can be used in ArcGIS Desktop.

This layer has query, identify, and export image services available. This layer is restricted to a maximum area of 24,000 x 24,000 pixels which allows access to the full dataset.

The source data for this layer are available here.

This layer is part of a larger collection of landscape layers that you can use to perform a wide variety of mapping and analysis tasks.

The Living Atlas of the World provides an easy way to explore the landscape layers and many other beautiful and authoritative maps on hundreds of topics.

", "keyword": [ "Landscape", "landscape5", "esri_landscape", "retiring-2026-12" ], "issued": "2014-11-18T21:38:01.000Z", "modified": "2019-12-18T17:05:43.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-20.0000,-39.0000,55.0000,40.0000", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::africa-crop-cassava-harvested-area" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape5.arcgis.com/arcgis/rest/services/Africa_Crop_Cassava/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=718429fe190648ad89729b45e37e0aa2", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::potential-evapotranspiration", "title": "Potential Evapotranspiration", "description": "
The combined processes of evaporation and transpiration, known as evapotranspiration (ET), plays a key role in the water cycle.  Precipitation that falls on land can either run off in streams and rivers, soak into the ground, or return to the atmosphere through evapotranspiration. Water that evaporates returns directly to the atmosphere while water that is transpired is taken up by plant roots and lost to the atmosphere through the leaves.

Evapotranspiration data can be used to calculate regional water and energy balance and soil water status and provides key information for water resource management. Potential evapotranspiration, the amount of ET that would occur if soil moisture were not limited, is a purely meteorological characteristic, based on air temperature, solar radiation, and wind speed. Actual evapotranspiration also depends on water availability, so it might occur at very close to the potential rate in a rainforest, but be much lower in a desert despite the higher potential there.

Dataset Summary
Phenomenon Mapped: Evapotranspiration
Units: Millimeters per year
Cell Size: 927.6623821756539  meters
Source Type: Continuous
Pixel Type: 16-bit unsigned integer
Data Coordinate System: Web Mercator Auxiliary Sphere
Extent: Global 
Source: University of Montana Numerical Terradynamic Simulation Group
Publication Date: March 10, 2015
ArcGIS Server URL: https://landscape6.arcgis.com/arcgis/

This layer provides access to a 1km cell sized raster of average annual evaporative loss from the land surface, measured in mm/year. Data are from the MOD16 Global Evapotranspiration Product, which is derived from MODIS imagery by a team of researchers at the University of Montana. This algorithm, which involves estimating land surface temperature and albedo and using them to solve the Penman-Monteith equation, is not valid over urban or barren land so these are shown as NoData, as is any open water. For all other pixels, the algorithm was used to estimate evapotranspiration for every 8-day period from 2000 to 2014 and these estimates have been averaged together to come up with the annual normal. You can also get access to the monthly totals using the MODIS Toolbox.

What can you do with this Layer? 
This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.

Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:
  • In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "evapotranspiration" in the search box and browse to the layer. Select the layer then click Add to Map.
  • In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "evapotranspiration" in the search box, browse to the layer then click OK.
In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.

The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.
", "keyword": [ "ET", "evap", "evapo", "evaporation", "transpiration", "hydro", "MODIS", "PET", "esri_landscape", "landscape", "landscape6", "climate", "weather", "water", "earth observations" ], "issued": "2018-03-01T04:01:15.000Z", "modified": "2020-08-27T00:03:01.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-59.9995,180.0000,80.0000", "license": "This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:
If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::potential-evapotranspiration" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Evapotranspiration/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a239f73530284c509ab574513dd0cf58&sublayer=0", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::global-water-provinces", "title": "Global Water Provinces", "description": "

Retirement Notice: This item is in mature support as of April 2026 and will be retired in December 2027. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.

River basins or hydrologic units are often the spatial unit used for aggregating and analyzing components of the water cycle such as precipitation, runoff, riverine discharge, etc. The hydroSHEDS dataset, derived from the Shuttle Radar Topography Mission, are the most commonly used global hydrologic unit for these analyses. But when planning water use or gaps, political boundaries need to be considered. Water provinces (Straatsma et al 2020) provide a much more realistic hydrologic unit for such purposes.

Esri’s World Administration Divisions (2011) defines 3,300 subnational units. Areas less than 150,000 sq km were aggregated into 1,099 regions. The water provinces were then calculated by overlaying these regions with the major basins from hydroSHEDS.  After sliver polygons were removed, the result was 1,604 unique units based on river basins but constrained by political boundaries. These water provinces provide a suitable unit for longterm water use planning, especially at local scales.

A more detailed description can be accessed here. 
 

Dataset Summary
Phenomenon Mapped: Water provinces of the world
Geographic Extent: Global
Layer Projection: Web Mercator Auxiliary Sphere 
Update Frequency: Semi-annual
Source: PCR-GLOBWB
Data Vintage: June 2013
Publication Date: March 2021

Questions?
Please leave a comment below if you have a question about this layer, and we will get back to you as soon as possible.

", "keyword": [ "landscape2", "retiring-2027-12" ], "issued": "2021-03-01T17:08:24.000Z", "modified": "2026-03-03T21:15:58.598Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-179.9997,-55.9796,179.9999,83.1132", "license": "

 This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::global-water-provinces" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services.arcgis.com/P3ePLMYs2RVChkJx/arcgis/rest/services/Global_Water_Provinces/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/kml?layers=0" }, { "@type": "dcat:Distribution", "title": "File Geodatabase", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/filegdb?layers=0" }, { "@type": "dcat:Distribution", "title": "Feature Collection", "format": "TXT", "mediaType": "text/plain", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/featureCollection?layers=0" }, { "@type": "dcat:Distribution", "title": "Excel", "format": "XLSX", "mediaType": "application/vnd.ms-excel", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/excel?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoPackage", "format": "GPKG", "mediaType": "application/geopackage+sqlite3", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/geoPackage?layers=0" }, { "@type": "dcat:Distribution", "title": "SQLite Geodatabase", "format": "GDB", "mediaType": "application/geopackage+sqlite3", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/a239f73530284c509ab574513dd0cf58/sqlite?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=bc6a9440f3cb41d6904b2c8831745903", "landingPage": "https://agriculture.africageoportal.com/datasets/africageoportal::digital-earth-africas-cropland-extents-for-africa", "title": "Digital Earth Africa's Cropland extents for Africa", "description": "

A\ncentral focus for governing bodies in Africa is the need to secure the\nnecessary food sources to support their populations. It has been estimated that\nthe current production of crops will need to double by 2050 to meet future\nneeds for food production. Higher level crop-based products that can assist\nwith managing food insecurity, such as cropping watering intensities, crop\ntypes, or crop productivity, require as a starting point precise and accurate\ncropland extent maps indicating where cropland occurs. Current cropland extent\nmaps are either inaccurate, have coarse spatial resolutions, or are not updated\nregularly. An accurate, high-resolution, and regularly updated cropland area\nmap for the African continent is therefore recognised as a gap in the current\ncrop monitoring services. 

Key Properties

Geographic Coverage: Continental Africa - approximately 37° North to 35 South
Temporal Coverage: 2019
Spatial Resolution: 10 x 10 meter
Update Frequency: TBD
Number of Bands: 3 Bands
Parent Dataset: Digital Earth Africa's Sentinel-2 Semiannual GeoMAD
Source Data Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)
Service Coordinate System: WGS 84 / NSIDC EASE-Grid 2.0 Global (EPSG:6933)

\n\n
Digital\nEarth Africa’s cropland extent maps for Eastern, Western, and Northern Africa\nshow the estimated location of croplands in these countries for the period of\nJanuary to December 2019: 
\n\n\n\n

Cropland is\ndefined as:

\n\n

"a\npiece of land of minimum 0.01 ha (a single 10m x 10m pixel) that is\nsowed/planted and harvestable at least once within the 12 months after the\nsowing/planting date."

\n\n


\n\n

This\ndefinition will exclude non-planted grazing lands and perennial crops which can\nbe difficult for satellite imagery to differentiate from natural vegetation.

\n\n

The\nprovisional cropland extent maps have a resolution of 10 metres and were built\nusing Copernicus Sentinel-2 satellite images from 2019. The cropland extent\nmaps were built separately using extensive training data from Eastern, Western,\nand Northern Africa, coupled with a Random Forest machine learning model. A\ndetailed exploration of the methods used to produce the cropland extent map can\nbe found in the Jupyter Notebooks in DE Africa’s crop-mask GitHub\nrepository.

\n\n

Independent\nvalidation datasets suggest the following accuracies:

\n\n\n\n

The algorithms\nfor all regions tend to report more omission errors (labelling actual crops as\nnon-crops) than commission errors (labelling non-crops as crops). Where\ncommission errors occur, they tend to be focussed around wetlands and seasonal\ngrasslands which spectrally resemble some kinds of cropping.


\n\n

Available Bands


Band ID

Description

Value range

Data type

NoData/Fill value

mask

crop extent (pixel)

0 - 1

uint8

0

prob

crop probability (pixel)

0 - 100

uint8

0

filtered

crop extent (object-based)

0 - 1

uint8

0

\n\n

mask: This band\ndisplays cropped regions as a binary map. Values of 1 indicate the\npresence of crops, while a value of 0 indicates the absence of\ncropping. This band is a pixel-based cropland extent map, meaning the\nmap displays the raw output of the pixel-based Random Forest classification.

\n\n

prob: This band\ndisplays the prediction probabilities for the ‘crop’ class. As this service\nuses a random forest classifier, the prediction probabilities refer to the\npercentage of trees that voted for the random forest classification. For\nexample, if the model had 200 decision trees in the random forest, and 150 of\nthe trees voted ‘crop’, the prediction probability is 150 / 200 x 100 = 75\n%. Thresholding this band at > 50 % will produce a map identical\nto mask.

\n\n

filtered: This band displays cropped regions as a\nbinary map. Values of 1 indicate the presence of crops, while a value\nof 0 indicates the absence of cropping. This band is an object-based cropland extent map where the mask band has\nbeen filtered using an image segmentation algorithm (see this paper for\ndetails on the algorithm used). During this process, segments smaller than 1 Ha\n(100 10m x 10m pixels) are merged with neighbouring segments, resulting in a\nmap where the smallest classified region is 1 Ha in size.\nThe filtered dataset is provided as a complement to\nthe mask band; small commission errors are removed by object-based\nfiltering, and the ‘salt and pepper’ effect typical of classifying pixels is\ndiminished.

\n\n


More details on this dataset can be found here.


", "keyword": [ "crop_mask_eastern", "crop_mask_western", "crop_mask_northern", "crop_mask_southern", "crop_mask_sahel", "analysis", "agriculture", "cropland extent", "Africa", "Digital Earth Africa", "DE Africa" ], "issued": "2022-01-13T04:01:44.000Z", "modified": "2026-04-09T20:52:18.000Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "DigitalEarthAfrica", "hasEmail": "mailto: africageoportal@esri.com" }, "accessLevel": "public", "spatial": "-17.9093,-35.2421,58.7026,38.0420", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/africageoportal::digital-earth-africas-cropland-extents-for-africa" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://di-deafrica.img.arcgis.com/arcgis/rest/services/deafrica/cropmask/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=31f7c3727abf42249a43fe8f25470af4", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::actual-evapotranspiration-mature-support", "title": "Actual Evapotranspiration (Mature Support)", "description": "Important Note: This item is in mature support as of April 2024 and will be retired in December 2026. A new version of this item is available for your use. Esri recommends updating your maps and apps to use the new version.

The combined processes of evaporation and transpiration, known as evapotranspiration (ET), plays a key role in the water cycle.  Precipitation that falls on land can either run off in streams and rivers, soak into the ground, or return to the atmosphere through evapotranspiration. Water that evaporates returns directly to the atmosphere while water that is transpired is taken up by plant roots and lost to the atmosphere through the leaves.

Evapotranspiration data can be used to calculate regional water and energy balance and soil water status and provides key information for water resource management. Potential evapotranspiration, the amount of ET that would occur if soil moisture were not limited, is a purely meteorological characteristic, based on air temperature, solar radiation, and wind speed. Actual evapotranspiration also depends on water availability, so it might occur at very close to the potential rate in a rainforest, but be much lower in a desert despite the higher potential there.

Dataset Summary
Phenomenon Mapped: Evapotranspiration
Units: Millimeters per year
Cell Size: 927.6623821756539  meters
Source Type: Continuous
Pixel Type: 16-bit unsigned integer
Data Coordinate System: Web Mercator Auxiliary Sphere
Extent: Global 
Source: University of Montana Numerical Terradynamic Simulation Group
Publication Date: March 10, 2015
ArcGIS Server URL: https://landscape6.arcgis.com/arcgis/

This layer provides access to a 1km cell sized raster of average annual evaporative loss from the land surface, measured in mm/year. Data are from the MOD16 Global Evapotranspiration Product, which is derived from MODIS imagery by a team of researchers at the University of Montana. This algorithm, which involves estimating land surface temperature and albedo and using them to solve the Penman-Monteith equation, is not valid over urban or barren land so these are shown as NoData, as is any open water. For all other pixels, the algorithm was used to estimate evapotranspiration for every 8-day period from 2000 to 2014 and these estimates have been averaged together to come up with the annual normal. You can also get access to the monthly totals using the MODIS Toolbox.

What can you do with this Layer? 
This layer is suitable for both visualization and analysis across the ArcGIS system. This layer can be combined with your data and other layers from the ArcGIS Living Atlas of the World in ArcGIS Online and ArcGIS Pro to create powerful web maps that can be used alone or in a story map or other application.

Because this layer is part of the ArcGIS Living Atlas of the World it is easy to add to your map:
  • In ArcGIS Online, you can add this layer to a map by selecting Add then Browse Living Atlas Layers. A window will open. Type "evapotranspiration" in the search box and browse to the layer. Select the layer then click Add to Map.
  • In ArcGIS Pro, open a map and select Add Data from the Map Tab. Select Data at the top of the drop down menu. The Add Data dialog box will open on the left side of the box, expand Portal if necessary, then select Living Atlas. Type "evapotranspiration" in the search box, browse to the layer then click OK.
In ArcGIS Pro you can use the built-in raster functions or create your own to create custom extracts of the data. Imagery layers provide fast, powerful inputs to geoprocessing tools, models, or Python scripts in Pro.

The ArcGIS Living Atlas of the World provides an easy way to explore many other beautiful and authoritative maps on hundreds of topics like this one.
", "keyword": [ "landscape6", "retiring-2026-12" ], "issued": "2018-03-01T04:01:13.000Z", "modified": "2024-04-05T00:34:22.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_landscape2", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-59.9995,180.0000,80.0000", "license": "

This work is licensed under the Esri Master License Agreement. 

View Summary | View Terms of Use
 
Important Note: This item requires an ArcGIS Online organizational subscription or an ArcGIS Developer account and does not consume credits. To access this item, you'll need to do one of the following:

If you don't have an account, you can sign up for a free trial of ArcGIS or a free ArcGIS Developer account.
 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::actual-evapotranspiration-mature-support" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://landscape6.arcgis.com/arcgis/rest/services/World_Evapotranspiration/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=42ebbb6428324a22a7a2c592b0b2935e", "landingPage": "https://agriculture.africageoportal.com/apps/LandscapeTeam::global-ecoexplorer-application", "title": "Global EcoExplorer Application", "description": "Explore the ecological tapestry of the world. The EcoExplorer Application provides access to the World Ecophysiography Map and the four layers, World Bioclimate, World Lithology, World Landform, and World Land Cover, used to create it.

More information on the application and the data behind it are available here.
", "keyword": [ "Ecophysiography", "landscape", "ecology", "climate", "weather", "soils", "geology", "landcover", "Explore the ecological tapestry of the world" ], "issued": "2014-12-10T21:27:46.000Z", "modified": "2026-01-16T20:02:52.000Z", "publisher": { "name": "Living Atlas – Landscape Content " }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_Landscape", "hasEmail": "mailto:cfrye@esri.com" }, "accessLevel": "public", "spatial": "-21.7749,-40.6139,86.8139,51.5816", "license": " This work is licensed under the Esri Master License Agreement.
View Summary | View Terms of Use

Landscape layers and other ArcGIS.com resources linked to in this map may require an ArcGIS.com organizational subscription. If you don't have an organizational subscription, you can sign up for a free 30-day trial of ArcGIS Online.", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/LandscapeTeam::global-ecoexplorer-application" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas.arcgis.com/ecoexplorer/" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=5670f96c2d0d4ad8ac549e092d6c2bd4", "landingPage": "https://agriculture.africageoportal.com/apps/esri::landsat-explorer-classic", "title": "Landsat Explorer Classic", "description": "
Mature Support Notice:  This item is in mature support as of February 2024. A new version of this item is available for your use.
 
This web application highlights some of the capabilities for accessing Landsat imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Landsat images on a daily basis.
 

Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Landsat Explorer app provides the power of Landsat satellites, which gather data beyond what the eye can see. Use this app to draw on Landsat's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the entire Landsat archive to visualize how the Earth's surface has changed over the last forty years.

Quick access to the following band combinations and indices is provided:

 

Optionally, you can also choose the \"Custom Bands\" or \"Custom Index\" option to create your own band combinations
 
The Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Stories tool will direct you to pre-selected interesting locations.
 
The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript.
 
The following Imagery Layers are being accessed : 
These imagery layers can be accessed through the public group Landsat Community on ArcGIS Online.
", "keyword": [ "esri_imagery" ], "issued": "2018-01-09T20:05:16.000Z", "modified": "2025-08-29T00:50:42.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "

This work is licensed under the Esri Master License Agreement.

View Summary | View Terms of Use
 
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/esri::landsat-explorer-classic" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://livingatlas2.arcgis.com/landsatexplorer/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=93ba20b268fb426c9c665a6bcd816da8", "landingPage": "https://agriculture.africageoportal.com/apps/esri::sentinel-explorer-classic", "title": "Sentinel Explorer Classic", "description": "
Mature Support Notice: This item is in mature support as of February 2025. A new version of this item is available for your use.
 

This web application highlights some of the capabilities for accessing Sentinel-2 imagery layers, powered by ArcGIS for Server, accessing Landsat Public Datasets running on the Amazon Web Services Cloud. The layers are updated with new Sentinel-2 images on a daily basis.

Created for you to visualize our planet and understand how the Earth has changed over time, the Esri Sentinel-2 Explorer app provides the power of Sentinel-2 satellites, which gather data beyond what the eye can see. Use this app to draw on Sentinel's different bands to better explore the planet's geology, vegetation, agriculture, and cities. Additionally, access the Sentinel-2 archive to visualize how the Earth's surface has changed over the last fourteen months

Quick access to the following band combinations and indices is provided:

 

Band

Description

Wavelength (µm)

Resolution (m)

1

Coastal aerosol

0.433 - 0.453

60

2

Blue

0.458 - 0.523

10

3

Green

0.543 - 0.578

10

4

Red

0.650 - 0.680

10

5

Vegetation Red Edge

0.698 - 0.713

20

6

Vegetation Red Edge

0.733 - 0.748

20

7

Vegetation Red Edge

0.773 - 0.793

20

8

NIR

0.785 - 0.900

10

8A

Narrow NIR

0.855 - 0.875

20

9

Water vapour

0.935 - 0.955

60

10

SWIR – Cirrus

1.365 - 1.385

60

11

SWIR-1

1.565 - 1.655

20

12

SWIR-2

2.100 - 2.280

20

 

Optionally, you can also choose the \"Custom Bands\" or \"Custom Index\" option to create your own band combinations
 
The Time tool enables access to a temporal time slider and a temporal profile of different indices for a selected point. The Time tool is only accessible at larger zoom scales. It provides temporal profiles for indices like NDVI (Normalized Difference Vegetation Index), NDMI (Normalized Difference Moisture Index) and Urban Index. The Identify tool enables access to information on the images, and can also provide a spectral profile for a selected point. The Bookmark tool will direct you to pre-selected interesting locations.
NOTE:  Using the Time tool to access imagery in the Sentinel-2 archive requires an ArcGIS account.
 
The application is written using Web AppBuilder for ArcGIS accessing imagery layers using ArcGIS API for JavaScript.
 
The following Imagery Layer are being accessed : 

 

", "keyword": [ "imagery", "Sentinel", "Sentinel-2", "multispectral", "temporal", "multitemporal", "earth" ], "issued": "2018-05-22T22:05:42.000Z", "modified": "2025-08-29T00:50:18.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_imagery", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "", "license": "
The Sentinel-2 data available through this service is licensed under the Copernicus Open Access Hub Terms and Conditions. Esri services are licensed under the Esri Master License Agreement.
 
View Sentinel-2 Terms of Use | View Summary | View Esri Terms of Use
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/esri::sentinel-explorer-classic" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://sentinel2explorer.esri.com/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=fcc7fd564c6441fba3b310d2281173b7", "landingPage": "https://agriculture.africageoportal.com/maps/esri::global-stream-flow-web-map", "title": "Global Stream Flow Web Map", "description": "
Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.
 
This web map includes the GEOGLOWS 2.0 ECMWF Streamflow Model (10-Day Forecast) and a customized vector base map.
 
The individual base layers (Reference and Base) were created from similar Esri Vector Basemaps (World Terrain Reference Local Language and Dark Gray Canvas) using the Vector Style Editor.
 
Each layer was customized specifically for the Global Water Sustainability (GEOGLOWS) and the European Centre for Medium-range Weather Forecasting (ECMWF) Streamflow Model 2.0 (10-Day Forecast).
 
", "keyword": [ "global", "basemaps", "basemap", "GWM", "GEOGLOWS", "Forecast", "Flow", "Streamflow", "Flood", "BYU", "ESRI", "esri_environment", "landscape", "fresh water", "freshwater", "livefeeds2", "Stream Flow", "Stream Discharge", "ECMWF" ], "issued": "2020-11-04T22:19:03.000Z", "modified": "2025-08-28T00:24:51.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_observations", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-117.5332,-49.0998,153.3457,74.4240", "license": "

This work is licensed under the Esri Master License Agreement.

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Alignment of boundaries is a presentation of the feature provided by our data vendors and does not imply endorsement by Esri or any governing authority. 
", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/maps/esri::global-stream-flow-web-map" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=91288ee7299b4f328147f9ad8bac617f", "landingPage": "https://agriculture.africageoportal.com/datasets/esri::global-land-cover-change-2018-to-2050", "title": "Global Land Cover Change 2018 to 2050", "description": "

Beta Notice: This item is currently in beta and is intended for early access, testing, and feedback. It is not recommended for production use, as functionality and content are subject to change without notice.

This layer shows the change in land cover between the 2018 European Space Agency Climate Change Initiative land cover layer (ESA CCI) and projected 2050 land cover from Clark Labs. The focus is on the difference between areas of human modified lands (cropland, urban, artificial surface) between the two periods.

 
Dataset Summary

Phenomenon mapped: Projected land cover change from 2018 to 2050

Data Projection: Cylindrical Equal Area
Mosaic Projection: Cylindrical Equal Area
Global Cell Size: 300m
Source Type: Thematic
Visible Scale: 1:50,000 and smaller
Source: Clark Labs and European Space Agency Climate Change Initiative
Publication date: April 2021
", "keyword": [ "env1", "landcover", "2050", "2018", "change", "esa", "esri_environment", "conservation", "development", "European Space Agency" ], "issued": "2021-07-09T01:20:11.000Z", "modified": "2025-08-28T00:24:37.000Z", "publisher": { "name": "Esri" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_environment", "hasEmail": "{{orgContactEmail}}" }, "accessLevel": "public", "spatial": "-180.0000,-48.6135,180.0000,74.4651", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/esri::global-land-cover-change-2018-to-2050" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://env1.arcgis.com/arcgis/rest/services/change_landcover_2018_2050/ImageServer" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=7e35012a609048e990945ca843fc64c9", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::inondations-en-république-du-congo-2023-2024", "title": "Inondations en République du Congo, 2023-2024", "description": "

Depuis le 28 décembre 2023, le Congo a connu des précipitations supérieures à la moyenne et des crues soudaines, avec un impact sur l'agriculture et les moyens d’existence. L'équipe Données en situations d’urgence (DIEM) de l'Organisation des Nations Unies pour l'alimentation et l'agriculture (FAO) a étudié les images satellites depuis cette date pour mener une évaluation rapide de l'impact, comprendre les conséquences des inondations et soutenir le pays avec une évaluation sur le terrain. Cette StoryMap présente l'impact potentiel des inondations sur la production agricole et les moyens d'existence au Congo.

Principales observations:

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2024-01-18T11:58:42.000Z", "modified": "2024-01-18T13:47:15.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::inondations-en-république-du-congo-2023-2024" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/7e35012a609048e990945ca843fc64c9" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=22561dc1baee4f4387881d3801dc16d7", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::drc-conflict-impact-assessment-in-ituri-province", "title": "DRC - Conflict impact assessment in Ituri province", "description": "{{description}}", "keyword": [ "Other DIEM documents", "Impact assessment" ], "issued": "2023-12-14T09:34:48.000Z", "modified": "2024-01-11T01:06:09.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Ibrahim.AliAhmad_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::drc-conflict-impact-assessment-in-ituri-province" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://experience.arcgis.com/experience/22561dc1baee4f4387881d3801dc16d7/" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=51693d84f32c498982f128151db091c8", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::monitoring-floods-in-the-sahel-and-central-africa", "title": "Monitoring floods in the Sahel and Central Africa", "description": "

Photo credits: © FAO

The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) regularly examines satellite images to monitor the flood extent resulting from the various rain seasons around the world. This StoryMap provided an update on the current flood extent assessment in the Sahel and Central Africa and provided comparisons to last year for 6 countries (Cameroon, Central African Republic, Chad, Niger, Nigeria and Mali) between July to end of October 2023.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-08-09T14:43:22.000Z", "modified": "2023-11-20T14:42:48.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::monitoring-floods-in-the-sahel-and-central-africa" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/51693d84f32c498982f128151db091c8" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=237dacf9a2c946a08dc2b1b4a77f563b", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::al-haouzmorocco-earthquake-september-2023", "title": "Al Haouz–Morocco earthquake, September 2023", "description": "

A high macroseismic intensity earthquake measuring 6.8 in magnitude hit Morocco on 8 September 2023 at 22.11 UTC. The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) examined the satellite images for this period to understand the impact. This StoryMap provides an assessment of the potential impacts of the earthquake on agriculture and livelihoods in Morocco.

Remote-sensing data indicate that most of the rainfed cropland lies in zones that were affected by moderate or light macroseismic activity. The crop types grown in zones where macroseismic intensity was the most severe are mostly fodder and vegetables. In these zones, the highest number of exposed animals (cattle, goat and sheep) were found in Al Haouz and Chichaoua provinces. In the High Atlas Mountains, damages caused by the earthquake may have led to disruptions in the transportation of goods and the market supply.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-10-06T10:45:37.000Z", "modified": "2023-11-06T09:47:46.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::al-haouzmorocco-earthquake-september-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/237dacf9a2c946a08dc2b1b4a77f563b" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e451e32a054847469b1c1c731a8e5cff", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::storm-daniel-libya-september-2023", "title": "Storm Daniel, Libya, September 2023", "description": "

On 10 September 2023, floods due to extreme rains impacted Libya after the passage of storm Daniel through the Mediterranean basin. The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) examined the satellite images for this period to understand the impact. This StoryMap is a rapid impact assessment that provides the potential impact of the floods on agriculture and livelihoods in Libya.

Remote sensing data indicate that a small percentage of flooded land is cropland. Even though the flooded cropland may be small, the impact of the floods on agricultural activities could be substantial given the potential damages to irrigation networks, roads, markets, grain storage and other infrastructure. The fisheries sector may have also been severely impacted given that the areas most affected by the floods are coastal areas.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-09-13T09:25:46.000Z", "modified": "2023-09-25T10:14:24.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::storm-daniel-libya-september-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/e451e32a054847469b1c1c731a8e5cff" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=b447b8aae28347f2ad045aad994c413c", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-malawi-2023", "title": "Tropical cyclone Freddy, Malawi, 2023", "description": "

Very heavy rainfall, a result of tropical cyclone Freddy which affected southern Malawi from 12 to 15 March 2023, caused floods and landslides. The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) examined the satellite images for this period to understand the impact. This StoryMap provides an assessment of the potential impacts of the floods and landslides on agriculture and livelihoods in Malawi.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-03-30T12:28:07.000Z", "modified": "2023-08-18T08:43:14.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-malawi-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/b447b8aae28347f2ad045aad994c413c" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=86bd04f382144c1e9259cf1d91303c86", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-cheneso-madagascar-2023", "title": "Tropical cyclone Cheneso, Madagascar, 2023", "description": "

Photo credits: @Copernicus Sentinel

On 19 January 2023, tropical cyclone Cheneso formed over the southwestern Indian Ocean and made landfall, as a tropical storm, at around 11.00 local time. On 26 January, the tropical storm peaked as a tropical cyclone and made landfall for the second time. This cyclone was the first cyclone during the 2022–2023 cyclone season in Southern Africa and affected different regions for more than one week. Around 470 000 hectares of land were affected, 141 000 hectares of agricultural land, and nearly 90 000 people. The Data in Emergencies team at the Food and Agriculture Organization of the United Nations (FAO) examined satellite images in the days following tropical cyclone Cheneso in order to understand the impact. This StoryMap provides an assessment of the potential impacts on agriculture and livelihoods in Madagascar.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-01-24T12:49:11.000Z", "modified": "2023-08-18T08:41:16.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-cheneso-madagascar-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/86bd04f382144c1e9259cf1d91303c86" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=e2fb1cfad13a4d8492b2ac00854b546c", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-mozambique-2023", "title": "Tropical cyclone Freddy, Mozambique, 2023", "description": "

In Mozambique, the 2022–⁠2023 rainy season brought with it above average rainfall, flash flooding and events that have led to the destruction of infrastructure and loss of lives. On 24 February 2023, tropical storm Freddy made landfall as a moderate tropical storm over Mozambique. Then Freddy returned and made landfall for the second time on 12 March 2023. The Data in Emergencies (DIEM) team at the Food and Agriculture Organization of the United Nations (FAO) examined the satellite images for this period to understand the impact. This StoryMap provides an assessment of the potential impacts of those floods on agriculture and livelihoods in Mozambique.

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-03-17T14:11:52.000Z", "modified": "2023-05-09T09:55:40.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-mozambique-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/e2fb1cfad13a4d8492b2ac00854b546c" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=591c404b88a342ec8c9fbd1691ae7eb7", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-madagascar-2023", "title": "Tropical cyclone Freddy, Madagascar, 2023", "description": "

Photo credits: @Copernicus Sentinel

On 21 February 2023, tropical cyclone Freddy made landfall on the east coast (Mananjary) of Madagascar. Freddy was the second cyclone to hit Madagascar in 2023. The Data in Emergencies team at the Food and Agriculture Organization of the United Nations (FAO) examined satellite images in the days following in order to understand the impact. This StoryMap provides an assessment of the potential impacts on agriculture and livelihoods in Madagascar.

Key findings in numbers:

", "keyword": [ "DIEM StoryMap", "Impact assessment" ], "issued": "2023-02-20T16:52:06.000Z", "modified": "2023-05-09T09:54:54.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::tropical-cyclone-freddy-madagascar-2023" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/591c404b88a342ec8c9fbd1691ae7eb7" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=461cbd480c1440869d81360870335de8", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::tchad-1", "title": "Tchad", "description": "

Crédits photo : ©FAO

", "keyword": [ "DIEM StoryMap" ], "issued": "2022-10-18T07:35:08.000Z", "modified": "2023-05-09T09:53:08.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::tchad-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/461cbd480c1440869d81360870335de8" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=ae8aaef165e24a7ab1d93de256fb2994", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::niger-1", "title": "Niger", "description": "

Crédits photo : ©FAO

", "keyword": [ "DIEM StoryMap" ], "issued": "2022-10-18T07:33:41.000Z", "modified": "2023-05-09T09:52:48.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ece.aksoy_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::niger-1" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/ae8aaef165e24a7ab1d93de256fb2994" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=4ad20d802b6f443fa46b68f1675aa3ab", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::madagascar-", "title": "Madagascar ", "description": "

Crédits photo : ©FAO/Cédric Fioekou

", "keyword": [ "DIEM StoryMap" ], "issued": "2022-04-22T14:32:52.000Z", "modified": "2023-05-09T09:52:03.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "ecegultan_hqfao", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by-nc-sa/3.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::madagascar-" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/4ad20d802b6f443fa46b68f1675aa3ab" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=06e95b1bc3e9406d90ba0504207bdcad", "landingPage": "https://agriculture.africageoportal.com/apps/UNEP-WCMC::cocoa-and-forests-in-west-africa-", "title": "Cocoa and forests in West Africa ", "description": "

The West African Upper Guinean forest is a global biodiversity hotspot1,2. It supports globally important ecosystem services, such as carbon sequestration, and important local benefits such as fuelwood, timber, wild foods and medicines3.

However, this forest, along with its ecosystem services, has seen large declines in recent decades. Cocoa is an important historical driver and direct cause of this loss4,5,6,7,8.    

The map below shows the cocoa growing zones in the cocoa production countries of West Africa with current tree cover.

", "keyword": [ "" ], "issued": "2022-01-06T10:25:22.000Z", "modified": "2023-02-28T12:09:36.000Z", "publisher": { "name": "UN Environment World Conservation Monitoring Centre" }, "contactPoint": { "@type": "vcard:Contact", "fn": "joe.gosling_UNEP_WCMC", "hasEmail": "mailto: info@unep-wcmc.org" }, "accessLevel": "public", "spatial": "", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/UNEP-WCMC::cocoa-and-forests-in-west-africa-" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.arcgis.com/stories/06e95b1bc3e9406d90ba0504207bdcad" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=cb5f86383b794dbaa0c207186d29fbae&sublayer=0", "landingPage": "https://agriculture.africageoportal.com/datasets/africa::geoglam-sub-national-crop-calendars", "title": "GEOGLAM Sub-national Crop Calendars", "description": "The Crop Monitor sub-national crop calendars are based on a combination of the best available data from different international agencies, national ministries, and expert knowledge from country partners. For the Crop Monitor for AMIS sub-national calendars, the USDA Major World Crop Areas and Climatic Profiles was used as a base to create the crop calendars at the national level. The Crop Monitor for Early Warning sub-national calendars used FAO GIEWS, FEWS NET, and national ministries as a base to create the crop calendars at the national level. Then for both Crop Monitors, each country was broken down into sub-national regions through the combination of agro-ecological zones, administrative level 1 FAO GAUL units, production statistics, and national partner inputs. The sub-national regions are each an aggregation of administrative FAO GAUL level 1 units or in some cases the administrative level 1 units themselves.", "keyword": [], "issued": "2022-02-07T18:44:07.000Z", "modified": "2022-02-07T18:45:02.651Z", "publisher": { "name": "Africa GeoPortal" }, "contactPoint": { "@type": "vcard:Contact", "fn": "esri_africa", "hasEmail": "https://support.esri.com" }, "accessLevel": "public", "spatial": "-92.2313,-46.9814,130.6749,55.4318", "license": "", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/africa::geoglam-sub-national-crop-calendars" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services8.arcgis.com/zNrTBuYXV2f35M0U/arcgis/rest/services/Sub-national_Crop_Calendars/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/cb5f86383b794dbaa0c207186d29fbae/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/cb5f86383b794dbaa0c207186d29fbae/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/cb5f86383b794dbaa0c207186d29fbae/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/cb5f86383b794dbaa0c207186d29fbae/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=89749a5b25a74409b9f2d25b9566fee1&sublayer=0", "landingPage": "https://agriculture.africageoportal.com/datasets/NRF-SAEON::conservation-agriculture-benefits", "title": "Conservation Agriculture Benefits", "description": "To raise awareness of the benefits of conservation agriculture for restoring the productive capacity of soil. The ploughing and overuse of agricultural lands causes the productive capacity of soil to be eroded over time posing great risks for food security. The use of conservation agriculture is picking up momentum among land owners and by making it visible (the projects, the research) through this layer and an interface for the public ASSET hopes to encourage its uptake. 

ASSET Research is committed to the development of capacity within the field of environmental and natural resource economics and related fields including the economics of restoration.  We do this through research programmes that engage both junior and senior researchers alike from various disciplines and institutions.  We rally our teams' research efforts around real-life challenges and thereby providing innovative and context-specific yet research-driven science-based options with respect to ways and means to answer those challenges.  Being a research and capacity organisation and an NGO/PBO, ASSET Research is not constrained by formal, institutional or subject-disciplinary borders.  This allows for the twinning of researchers and disciplines across many conventional divides.

Restoration, in addition to being a science, a business and a process involving a series of interwoven activities and ecosystem trajectories on a continuum of uncertainty, is also a narrative cast in a set of intentional interventions.  It is thus a social-ecological dialogue with ourselves in an ecological as well as a socio-economic space. Only when we look in the mirror, face the brutal reality of degradation, impairment and decline, and start to catalyse change towards societies, ecosystems and a planet in repair, then restoration, and a restoration culture may become the narrative, the vision and the paradigm leading to a new, revitalised and regenerative future.
", "keyword": [ "ecology", "conservation", "restoration", "South Africa", "Restoration", "Economics", "Agriculture", "Soil", "Conservation", "Yields", "Soil Depletion" ], "issued": "2021-06-23T07:49:19.000Z", "modified": "2021-06-23T14:12:33.008Z", "publisher": { "name": "South African Environmental Observation Network (SAEON)" }, "contactPoint": { "@type": "vcard:Contact", "fn": "Curation", "hasEmail": "mailto:datascience@SAEON.ac.za" }, "accessLevel": "public", "spatial": "21.8569,-33.2278,30.8958,-25.5653", "license": "https://creativecommons.org/licenses/by-sa/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/datasets/NRF-SAEON::conservation-agriculture-benefits" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://services7.arcgis.com/jbdCPRrwkIrZb0KZ/arcgis/rest/services/Conservation_Agriculture_Benefits2/FeatureServer/0" }, { "@type": "dcat:Distribution", "title": "CSV", "format": "CSV", "mediaType": "text/csv", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/89749a5b25a74409b9f2d25b9566fee1/csv?layers=0" }, { "@type": "dcat:Distribution", "title": "Shapefile", "format": "ZIP", "mediaType": "application/zip", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/89749a5b25a74409b9f2d25b9566fee1/shapefile?layers=0" }, { "@type": "dcat:Distribution", "title": "GeoJSON", "format": "GeoJSON", "mediaType": "application/vnd.geo+json", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/89749a5b25a74409b9f2d25b9566fee1/geojson?layers=0" }, { "@type": "dcat:Distribution", "title": "KML", "format": "KML", "mediaType": "application/vnd.google-earth.kml+xml", "accessURL": "https://agriculture.africageoportal.com/api/download/v1/items/89749a5b25a74409b9f2d25b9566fee1/kml?layers=0" } ], "theme": [ "geospatial" ] }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=cb0258df53284b40a4891b5ceda5b66d", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::food-security-livelihoods-dashboard-household-survey-v1-0", "title": "Food Security & Livelihoods Dashboard - Household survey V1.0", "description": "

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries.

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. 

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

", "keyword": [ "HH Dashboard V1" ], "issued": "2020-12-11T13:37:13.000Z", "modified": "2021-05-11T12:57:37.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "dmarsh@esri.com", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::food-security-livelihoods-dashboard-household-survey-v1-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=36bf84b0ac1f49a49a6a02074463659b", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::needs-dashboard-household-survey-v1-0", "title": "Needs Dashboard - Household survey V1.0", "description": "

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries.

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. 

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

", "keyword": [ "HH Dashboard V1" ], "issued": "2021-02-10T06:27:25.000Z", "modified": "2021-05-11T09:57:28.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "dmarsh@esri.com", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::needs-dashboard-household-survey-v1-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=459f2042a21546cd8542187bfd99fd7b", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::livestock-production-dashboard-household-survey-v1-0", "title": "Livestock Production Dashboard - Household survey V1.0", "description": "

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries.

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. 

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

", "keyword": [ "HH Dashboard V1" ], "issued": "2020-12-11T09:59:44.000Z", "modified": "2021-04-28T12:44:29.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "dmarsh@esri.com", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::livestock-production-dashboard-household-survey-v1-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a37ffc3714924648a32884bdf34b13e6", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::value-chains-markets-dashboard-household-survey-v1-0", "title": "Value Chains & Markets Dashboard - Household survey V1.0", "description": "

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries.

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. 

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

", "keyword": [ "HH Dashboard V1" ], "issued": "2020-12-11T12:16:18.000Z", "modified": "2021-04-27T08:23:16.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "dmarsh@esri.com", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::value-chains-markets-dashboard-household-survey-v1-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=4c7b428eb36349cf936e15ed6921fce1", "landingPage": "https://agriculture.africageoportal.com/apps/hqfao::crop-production-dashboard-household-survey-v1-0", "title": "Crop Production Dashboard - Household survey V1.0", "description": "

The Office of Emergency and Resilience (OER) of the Food and Agriculture Organization (FAO) is piloting a monitoring system to better understand the impacts of COVID-19 and other shocks on food supply, agricultural livelihoods and food security in a number of food crisis countries.

The monitoring system consists of primary data collected from households and key informants (including agricultural inputs vendors, food traders and agriculture extension officers) on a periodic basis (more or less every 3 months). Data are mainly collected through Computer-Assisted Telephone Interviews (CATI). In-person surveys are conducted where the circumstances allow for field access. During the first round of the system, from June to November 2020, more than 40,000 interviews have been completed in more than 20 countries. 

Data are used to guide strategic decisions, to design programmes and to inform analytical processes such as the IPC.

The present dashboard shows the portion of data referring to Livestock Production from Colombia, Liberia, DRC, Sierra Leone, Niger, Somalia, Zimbabwe and Mali.

", "keyword": [ "HH Dashboard V1" ], "issued": "2020-12-11T08:19:56.000Z", "modified": "2021-04-16T14:45:44.000Z", "publisher": { "name": "Food and Agriculture Organization of the United Nations" }, "contactPoint": { "@type": "vcard:Contact", "fn": "dmarsh@esri.com", "hasEmail": "mailto:fao-data@fao.org" }, "accessLevel": "public", "spatial": "", "license": "https://creativecommons.org/licenses/by/4.0", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/hqfao::crop-production-dashboard-household-survey-v1-0" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=d29065c5443f4d008e7d7e181e54b05d", "landingPage": "https://agriculture.africageoportal.com/apps/Story::the-living-land", "title": "The Living Land", "description": "

For many of us, urban areas are the first thing that comes to mind when we think of spaces that have been altered by people. But, as it turns out, these mental images aren't very representative of our overall land use.    


In the second chapter of our Living in the Age of Humans series, the Esri Story Maps team takes a closer look at the ways Homo sapiens have modified Earth's limited land, and what implications this use has for our future.

Data:

", "keyword": [ "Story Map", "Cascade", "land use", "agriculture", "Age of Humans", "croplands", "Pasturelands", "urban areas", "crops", "Pasture", "livestock", "Anthropocene" ], "issued": "2018-10-03T09:32:06.000Z", "modified": "2020-09-24T21:00:44.000Z", "publisher": { "name": "ArcGIS StoryMaps" }, "contactPoint": { "@type": "vcard:Contact", "fn": "StoryMaps", "hasEmail": "https://www.esri.com/en-us/contact" }, "accessLevel": "public", "spatial": "", "license": "

Esri logoThis work is licensed under the Esri Master License Agreement.    

                               View Summary  |  View Terms of Use 

", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/Story::the-living-land" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://storymaps.esri.com/stories/2018/anthropocene/2-the-land.html" } ], "theme": "" }, { "@type": "dcat:Dataset", "identifier": "https://www.arcgis.com/home/item.html?id=a9d345446d1a48a2918ff95b51f5841c", "landingPage": "https://agriculture.africageoportal.com/apps/nation::five-years-of-drought", "title": "Five Years of Drought", "description": "Visualize five years of drought in this series of visualizations. Walk through a set of cartographic map images to visualize the sustained impact. Navigate the interactive map to dig into details. Then, learn how you can make a similar map using these techniques!

Here are some links to helpful reference and source material:
Source GIS files: US Drought Monitor
Derivative drought point data: Feature Service
Link to web map: Five Years of Drought Web Map

John Nelson Esri
", "keyword": [ "Story Map", "Cascade", "story map cascade", "USA", "Water resources", "hydrology", "drought", "cartography", "hexagon", "hexbins", "bi-variate", "earth observations", "agriculture", "landscape", "climate", "weather", "ecology", "disturbance", "water" ], "issued": "2016-07-13T12:42:29.000Z", "modified": "2017-09-01T16:35:25.000Z", "publisher": { "name": "ArcGIS Maps for the Nation" }, "contactPoint": { "@type": "vcard:Contact", "fn": "j_nelson", "hasEmail": "mailto:jherries@esri.com" }, "accessLevel": "public", "spatial": "-128.8040,22.6090,-63.7650,50.5240", "license": "This story map is freely shareable to the public, for the benefit of knowledge distribution and cartographic education.", "distribution": [ { "@type": "dcat:Distribution", "title": "ArcGIS Hub Dataset", "format": "Web Page", "mediaType": "text/html", "accessURL": "https://agriculture.africageoportal.com/apps/nation::five-years-of-drought" }, { "@type": "dcat:Distribution", "title": "ArcGIS GeoService", "format": "ArcGIS GeoServices REST API", "mediaType": "application/json", "accessURL": "https://nation.maps.arcgis.com/apps/Cascade/index.html?appid=a9d345446d1a48a2918ff95b51f5841c" } ], "theme": [ "geospatial" ] } ] }