Near real time epoch 2019 from the Collection 3 of annual, global 100m land cover maps.

Other available epochs: 2015 2016 2017 2018

Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.

The maps include

• a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,
• a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes
• a forest type layer
• quality layers on input data density and on the confidence of the detected land cover change

Click here to view the maps

More information about the land cover maps

Product User Manual

Consolidated epoch 2018 from the Collection 3 of annual, global 100m land cover maps.

Other available epochs: 2015 2016 2017 2019

Produced by the global component of the Copernicus Land Service, derived from PROBA-V satellite observations and ancillary datasets.

The maps include

• a main discrete classification with 23 classes aligned with UN-FAO's Land Cover Classification System,
• a set of versatile cover fractions: percentage (%) of ground cover for the 10 main classes
• a forest type layer
• quality layers on input data density and on the confidence of the detected land cover change

Click here to view the maps

More information about the land cover maps

Product User Manual

A map of 73 global biome clusters, geographic areas that were grouped to optimize the global 100m land cover processing.

In order to group Earth Observation data for faster processing or adaptation of algorithms to specific regions, the 100m global land cover (CGLS-LC100) algorithm uses a Global Biome Cluster layer. The term biome cluster hereby refers to a geographic area which has similar bio-geophysical parameters and, therefore, can be grouped for processing. In other words, the biome cluster layer can be seen as an ecological regionalisation which outlines areas of similar environmental conditions, ecological processes, and biotic communities (Coops et al., 2018). There are already several global regionalisation layers existing, e.g. Ecoregions 2017 global dataset (Dinerstein et al., 2017), Geiger-Koeppen global ecozones after Olofsson update (Olofsson et al., 2012), Global ecological zones for FAO forest reporting with update 2010 (FAO, 2012). But several tests in the CGLS-LC100 workflow have shown that the existing layers did not provide the required global and continental classification accuracy. These findings go along with Coops et al. (2018) who stated that "Most regionalisations are made based on subjective criteria, and cannot be readily revised, leading to outstanding questions with respect to how to optimally develop and define them."

Therefore, we decided to develop a customized ecological regionalisation layer which performs best with the given PROBA-V remote sensing data and the specifications of the CGLS-LC100 product. It groups spectral similar areas and helps to optimize the later classification/regression to regional patterns. Input into the layer creation were well-known existing datasets which were combined, re-grouped and advanced based on prior CGLS-LC100 classification results and local mapping knowledge of the workflow developer. To ensure that this layer is clearly separable from other existing regionalisations and not mistakenly interpreted as an eco-region layer, we decide to call it biome clusters layer.

The following steps outline the global biome clusters layer generation:

Spatial union of Ecoregions 2017 dataset (Dinerstein et al., 2017), Geiger-Koeppen dataset (Olofsson et al., 2012) and Global FAO eco-regions datasets (FAO, 2012);

Regrouping and dissolving by using experience from first global CGLS-LC100 mapping results and subjective mapping experience of the developer;

Refinement of the biome clusters in the High North latitudes via incorporation of a Global tree-line layer (Alaska Geobotany Center, 2003);

Manual improvement of borders between biome clusters to reduce classification artefacts by using a DEM and mapping experience from previous projects and continental test runs;

Usage of a global land/sea mask, the Sentinel-2 tiling grid and PROBA-V imaging extent to extend the borders of the biome clusters into the sea to make sure that also small islands on the coastline are correctly processed.

When developing a regionalisation, the definition of the clusters and the boundaries that delineate them in time and space is the key challenge. Overall, the map distinguishes 73 global biome clusters.

First global land cover maps from the global component of the Copernicus Land Service, derived from PROBA-V satellite observations.
Collection 2 refers to the first global maps, in 100m spatial resolution grid (collection 1 was a demonstration over Africa).
First epoch is year 2015. More years and maps of changes between years are expected to be added.
The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers.

Click here to view the maps

More information about the land cover maps

Product User Manual

This product is delivered by the Copernicus Global Land Cover and Tropical Forest Mapping and Monitoring service (LCFM), part of the Copernicus Land Monitoring Service (CLMS), and provides global land cover data at 10-meter resolution for the year 2020.

The LCM-10 product builds upon previous initiatives like the 100m Copernicus Global Land Cover layers (2015-2019). This product offers enhanced spatial detail that facilitates more effective monitoring of global land cover changes, including deforestation, urbanization, and other environmental transformations.

The LCM-10 comprises a MAP layer which provides a discrete classification map at 10m resolution. It denotes the dominant land cover class for each pixel across 11 primary classes as defined using the Land Cover Classification System (LCCS) developed by the Food and Agriculture Organization (FAO). These classes include Tree cover, Shrubland, Grassland, Cropland, Built-up, Bare/sparse vegetation, Snow and ice, Permanent water bodies, Herbaceous wetland, Mangroves, and Moss and lichen. Additionally, Unclassifiable is used where no or insufficient Sentinel-1/2 data is available, while no data denotes pixels outside of the area of interest.

The spatial forest coverage is derived from the Copernicus Global Land Cover dataset for the assessment year 2019 (accessed in February 2022). We outline the procedure of pre-processing the original Copernicus data segments into a continuous global forest mask, which is compliant with the FAO forest definition. This forest mask is then analysed for various forest attribute layers summarising the spatial status of forest cover and its degree of forest degradation. The analysis is conducted in a dual approach: first, using the original WGS84 map projection for explanatory and user-friendly visualisation on web portals and second, in equal area projection allowing statistical evaluation of the forest attribute layers. Spatially explicit maps and statistical summaries are derived for a total of 278 reporting units, comprised of 255 countries, 21 global ecological zones, the EU27, and the full global coverage.

The full dataset, described in section 3.5 of the Technical Report (https://doi.org/10.2760/41048) is available at: https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opendata/FOREST/FAL/CGLO/LATEST/

This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years 1992-2020. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2020Cell Size: 300 meter Source Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary Sphere Extent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: Annual until 2020, no updates thereafterWhat can you do with this layer? This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro. In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend. To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth. Different Classifications Available to Map Five processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display. Using Time By default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year. In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change. Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009. This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover. Land Cover Processing To provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015. Source data The datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.php CitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%) 50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

This product is delivered by the Copernicus Global Land Cover and Tropical Forest Mapping and Monitoring service (LCFM), part of the Copernicus Land Monitoring Service (CLMS), and provides global land cover data at 100-meter resolution for the year 2020.

This product is a continuation of the Global Dynamic Land Cover map at 100 m spatial resolution available for the years 2015–2019, but it uses different input data (Sentinel-1 and Sentinel-2 instead of Proba-V) and a different classification algorithm.

The LCM-100 comprises three layers: - Map layer - The core product providing a discrete classification map at 100m resolution. It denotes the dominant land cover class for each pixel across 12 primary classes as defined using the Land Cover Classification System (LCCS) developed by the Food and Agriculture Organization (FAO). These classes include Open and Closed tree cover, Shrubland, Grassland, Cropland, Built-up, Bare/sparse vegetation, Snow and ice, Permanent water bodies, Herbaceous wetland, Mangroves, and Moss and lichen. - Cover fraction layer - this layer provides Land Cover Fractions at 100m resolution for each class, scaled between 0 and 1. - Change layer - a layer that qualifies the confidence of change vs. previous year. For this version of the product, the layer is available, but does not contain data.

Forest cover: areas where forest cover is above 30%. Pixels with a value higher than the specified threshold (30%) were given a value of 1 (YES response)

The Dynamic Land Cover map at 100 m resolution (CGLS-LC100) is a new product in the portfolio of the CGLS and delivers a global land cover map at 100 m spatial resolution. The CGLS Land Cover product provides a primary land cover scheme. Next to these discrete classes, the product also includes continuous field layers for all basic land cover classes that provide proportional estimates for vegetation/ground cover for the land cover types. This continuous classification scheme may depict areas of heterogeneous land cover better than the standard classification scheme and, as such, can be tailored for application use (e.g. forest monitoring, crop monitoring, biodiversity and conservation, monitoring environment and security in Africa, climate modelling, etc.). These consistent Land Cover maps (v3.0.1) are provided for the period 2015-2019 over the entire Globe, derived from the PROBA-V 100 m time-series, a database of high quality land cover training sites and several ancillary datasets, reaching an accuracy of 80% at Level1 over all years. It is planned to provide yearly updates from 2020 through the use of a Sentinel time-series.

Data revision: 2021-12-14

Contact points:

Contact: Marcel Buchhorn Remote Sensing Unit, Flemish Institute for Technological Research

Metadata contact: OCB Environment FAO-UN

Resource constraints:

• The dataset contains modified Copernicus Climate Change Service information [2005-2019];

• Neither the European Commission nor ECMWF is responsible for any use that may be made of the Copernicus information or data it contains.

More information on Copernicus License in PDF version at https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf

Online resources:

Copernicus Global Land Cover Layers

This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years since 1992. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2019Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: AnnualWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.CitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc

This layer displays global land cover in 10 classes for the year 2018 produced by the European Space Agency Climate Change Initiative (ESA CCI). The 36 classes of the traditional ESA CCI land cover has been simplified to match the Esri 2050 land cover prediction layers. Phenomenon mapped: Land CoverData Projection: Cylindrical Equal AreaMosaic Projection: Cylindrical Equal AreaExtent: GlobalCell Size: 300mSource Type: ThematicVisible Scale: All scalesSource: ESA Climate Change InitiativePublication date: 2018ESA CCI land cover data for the years 1992-2019 are available here.What can you do with this layer?

This layer may be displayed in a map to show generalized land cover classes for the world in the year 2018.This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.More technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc

This demo dataset over Africa is deprecated. Please see this global dataset instead.

Demonstration land cover maps over Africa at 100m resolution for epoch year 2016, from the global component of the Copernicus Land Service and derived from PROBA-V satellite observations.

The maps include the main discrete classification (23 classes aligned with UN-FAO's LCCS), a set of cover fractions (%) for the 10 main classes and additional quality layers (e.g. density of input data).

For the consolidated epoch 2016, the classifier and regression models of base year 2015 are used, and the time window of the classified metrics covers one full year prior (2015) and pastor (2017) data. The layers with the probability of the discrete classification and the standard deviation of the cover fractions are only provided for the base year (epoch 2015). The Change Consistency Layer that checks consistency between classifier and break detection, is only available for the most recent (near-real time) year (epoch 2018).

View the maps and area statistics

Product User Manual

More land cover change product information and documentation

This webmap is a subset of Global Landcover 1992 - 2020 Image Layer. You can access the source data from here. This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years 1992-2020. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2020Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: Annual until 2020, no updates thereafterWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

This layer is a subset of Global Landcover 1992- 2020 Layer. This layer is a time series of the annual ESA CCI (Climate Change Initiative) land cover maps of the world. ESA has produced land cover maps for the years 1992-2020. These are available at the European Space Agency Climate Change Initiative website.Time Extent: 1992-2020Cell Size: 300 meterSource Type: ThematicPixel Type: 8 Bit UnsignedData Projection: GCS WGS84Mosaic Projection: Web Mercator Auxiliary SphereExtent: GlobalSource: ESA Climate Change InitiativeUpdate Cycle: Annual until 2020, no updates thereafterWhat can you do with this layer?This layer may be added to ArcGIS Online maps and applications and shown in a time series to watch a "time lapse" view of land cover change since 1992 for any part of the world. The same behavior exists when the layer is added to ArcGIS Pro.In addition to displaying all layers in a series, this layer may be queried so that only one year is displayed in a map. This layer can be used in analysis. For example, the layer may be added to ArcGIS Pro with a query set to display just one year. Then, an area count of land cover types may be produced for a feature dataset using the zonal statistics tool. Statistics may be compared with the statistics from other years to show a trend.To sum up area by land cover using this service, or any other analysis, be sure to use an equal area projection, such as Albers or Equal Earth.Different Classifications Available to MapFive processing templates are included in this layer. The processing templates may be used to display a smaller set of land cover classes.Cartographic Renderer (Default Template)Displays all ESA CCI land cover classes.*Forested lands TemplateThe forested lands template shows only forested lands (classes 50-90).Urban Lands TemplateThe urban lands template shows only urban areas (class 190).Converted Lands TemplateThe converted lands template shows only urban lands and lands converted to agriculture (classes 10-40 and 190).Simplified RendererDisplays the map in ten simple classes which match the ten simplified classes used in 2050 Land Cover projections from Clark University.Any of these variables can be displayed or analyzed by selecting their processing template. In ArcGIS Online, select the Image Display Options on the layer. Then pull down the list of variables from the Renderer options. Click Apply and Close. In ArcGIS Pro, go into the Layer Properties. Select Processing Templates from the left hand menu. From the Processing Template pull down menu, select the variable to display.Using TimeBy default, the map will display as a time series animation, one year per frame. A time slider will appear when you add this layer to your map. To see the most current data, move the time slider until you see the most current year.In addition to displaying the past quarter century of land cover maps as an animation, this time series can also display just one year of data by use of a definition query. For a step by step example using ArcGIS Pro on how to display just one year of this layer, as well as to compare one year to another, see the blog called Calculating Impervious Surface Change.Hierarchical ClassificationLand cover types are defined using the land cover classification (LCCS) developed by the United Nations, FAO. It is designed to be as compatible as possible with other products, namely GLCC2000, GlobCover 2005 and 2009.This is a heirarchical classification system. For example, class 60 means "closed to open" canopy broadleaved deciduous tree cover. But in some places a more specific type of broadleaved deciduous tree cover may be available. In that case, a more specific code 61 or 62 may be used which specifies "open" (61) or "closed" (62) cover.Land Cover ProcessingTo provide consistency over time, these maps are produced from baseline land cover maps, and are revised for changes each year depending on the best available satellite data from each period in time. These revisions were made from AVHRR 1km time series from 1992 to 1999, SPOT-VGT time series between 1999 and 2013, and PROBA-V data for years 2013, 2014 and 2015. When MERIS FR or PROBA-V time series are available, changes detected at 1 km are re-mapped at 300 m. The last step consists in back- and up-dating the 10-year baseline LC map to produce the 24 annual LC maps from 1992 to 2015.Source dataThe datasets behind this layer were extracted from NetCDF files and TIFF files produced by ESA. Years 1992-2015 were acquired from ESA CCI LC version 2.0.7 in TIFF format, and years 2016-2018 were acquired from version 2.1.1 in NetCDF format. These are downloadable from ESA with an account, after agreeing to their terms of use. https://maps.elie.ucl.ac.be/CCI/viewer/download.phpCitationESA. Land Cover CCI Product User Guide Version 2. Tech. Rep. (2017). Available at: maps.elie.ucl.ac.be/CCI/viewer/download/ESACCI-LC-Ph2-PUGv2_2.0.pdfMore technical documentation on the source datasets is available here:https://cds.climate.copernicus.eu/cdsapp#!/dataset/satellite-land-cover?tab=doc*Index of all classes in this layer:10 Cropland, rainfed11 Herbaceous cover12 Tree or shrub cover20 Cropland, irrigated or post-flooding30 Mosaic cropland (>50%) / natural vegetation (tree, shrub, herbaceous cover) (<50%)40 Mosaic natural vegetation (tree, shrub, herbaceous cover) (>50%) / cropland (<50%)50 Tree cover, broadleaved, evergreen, closed to open (>15%)60 Tree cover, broadleaved, deciduous, closed to open (>15%)61 Tree cover, broadleaved, deciduous, closed (>40%)62 Tree cover, broadleaved, deciduous, open (15-40%)70 Tree cover, needleleaved, evergreen, closed to open (>15%)71 Tree cover, needleleaved, evergreen, closed (>40%)72 Tree cover, needleleaved, evergreen, open (15-40%)80 Tree cover, needleleaved, deciduous, closed to open (>15%)81 Tree cover, needleleaved, deciduous, closed (>40%)82 Tree cover, needleleaved, deciduous, open (15-40%)90 Tree cover, mixed leaf type (broadleaved and needleleaved)100 Mosaic tree and shrub (>50%) / herbaceous cover (<50%)110 Mosaic herbaceous cover (>50%) / tree and shrub (<50%)120 Shrubland121 Shrubland evergreen122 Shrubland deciduous130 Grassland140 Lichens and mosses150 Sparse vegetation (tree, shrub, herbaceous cover) (<15%)151 Sparse tree (<15%)152 Sparse shrub (<15%)153 Sparse herbaceous cover (<15%)160 Tree cover, flooded, fresh or brakish water170 Tree cover, flooded, saline water180 Shrub or herbaceous cover, flooded, fresh/saline/brakish water190 Urban areas200 Bare areas201 Consolidated bare areas202 Unconsolidated bare areas210 Water bodies

The European Space Agency (ESA) WorldCover 10 m 2021 product provides a global land cover map for 2021 at 10 m resolution based on Sentinel-1 and Sentinel-2 data. The WorldCover product comes with 11 land cover classes, aligned with UN-FAO's Land Cover Classification System, and has been generated in the framework of the ESA WorldCover project, part of the 5th Earth Observation Envelope Programme (EOEP-5) of the European Space Agency.

The WorldCover 2021 v200 product is developed by a consortium lead by VITO Remote Sensing together with partners Brockmann Consult, Gamma Remote Sensing AG, IIASA and Wageningen University.

Data description

The ESA WorldCover 10m 2021 V200 is provided per 3 x 3 degree tile, 2651 in total. Each tile contains a set of 2 Cloud Optimized GeoTIFF (COG) files corresponding to the following data layers:

• Map: Land cover map with 11 classes

• InputQuality: Three band GeoTIFF providing three per pixel quality indicators of the Sentinel1 and Sentinel-2 input data

Tiles are provided in EPSG:4326, geographic projection (latitude/longitude CRS).

For more information on the ESA WorldCover product and details on how to use the data please see the Product User Manual for WorldCover 2021 v200.

Data publication: 2022-10-28

Citation:

To cite these maps as data source in your publication, please add:

WorldCover 2021 v200

Zanaga, D., Van De Kerchove, R., Daems, D., De Keersmaecker, W., Brockmann, C., Kirches, G., Wevers, J., Cartus, O., Santoro, M., Fritz, S., Lesiv, M., Herold, M., Tsendbazar, N.E., Xu, P., Ramoino, F., Arino, O., 2022. ESA WorldCover 10 m 2021 v200 (https://doi.org/10.5281/zenodo.7254221).

Contact points:

Resource Contact: ESA/VITO/Brockmann Consult/CS/GAMMA Remote Sensing/IIASA/WUR

Resource Contact: European Space Agency

Metadata Contact: FAO-Data

Data lineage:

The ESA WorldCover 10m 2021 v200 product updates the existing ESA WorldCover 10m 2020 v100 product to 2021 but is produced using an improved algorithm version (v200) compared to the 2020 map. Consequently, since the WorldCover maps for 2020 and 2021 were generated with different algorithm versions (v100 and v200, respectively), changes between the maps should be treated with caution, as they include both real changes in land cover and changes due to the algorithms used.

The ESA WorldCover product has been independently validated by Wageningen University (statistical accuracy) and IIASA (spatial accuracy). The WorldCover 2021 v200 reaches an overall accuracy of 76.7%. For more details please see the Product Validation Report V2.0.

Resource constraints:

The ESA WorldCover product is provided free of charge, without restriction of use. If you are using the data as a layer in a published map, please include the following attribution text:

Publications, models and data products that make use of these datasets must include proper acknowledgement, including citing the datasets and the journal article as in the following citation.

© ESA WorldCover project 2021 / Contains modified Copernicus Sentinel data (2021) processed by ESA WorldCover consortium.

Online resources:

Data access

WorldCover Product User Manual V.2.0

WorldCover Product Validation Report V2.0

Worldwide land cover mapping website

Map distinguishing 14 classes of agricultural land in Africa. Agricultural land includes arable land, permanent crops and permanent pastures. The map is a classification of the 'Agricultural Land of Africa (verion 2)' dataset. Primary input data source to develop the map was the Copernicus Global Land Service; Land Cover 100m; collection 3; epoch 2019; Globe (https://zenodo.org/record/3939050). In addition, the Agro-ecological zones of Africa (AEZ; version 2009 developed by IFPRI, https://doi.org/10.7910/DVN/HJYYTI) dataset was used. The map was generated by applying agricultural land classification rules to a set of Copernicus Global Land Cover layers (main discrete classification, cover fractions for cropland/forest/herbaceous vegetation/shrubland) and the AEZ layer. The map has a spatial resolution of 100 m.

This experimental land cover dataset at continental scale (Level 2) shows a broad classification aiming at identifying cultivated land and, more specifically, distinguishing between irrigated and rainfed areas. It is published on a yearly basis, while seasonal products are available upon request. The data is provided in near real time from January 2009 to present.

Data publication: 2020-01-01

Supplemental Information:

No data value: 255

Unit: class

Citation:

FAO 2018. WaPOR Database Methodology: Level 2. Remote Sensing for Water Productivity Technical Report: Methodology Series. Rome, FAO. 72 pages. Licence: CC BY-NC-SA 3.0 IGO

Contact points:

Metadata Contact: WaPOR

Resource Contact: WaPOR

Data lineage:

Land Cover Classification makes use of the dekadal reflectance time series and seasonal phenology information from the Crop Calendar. The Level 1 land cover products were derived from the Global Land Service of Copernicus, the Earth Observation programme of the European Commission. This product was generated from MODIS data, using the Copernicus training data and operational workflow, modified to account for differences in spatial resolution and the delivered land cover classes. In addition, irrigated areas are identified by applying a water deficit index that takes into consideration seasonal cumulated values of precipitation and actual evapotranspiration.

The classification applied is based on the Land Cover Classification System (LCCS) that was developed by FAO.

Data component developed through collaboration with the FRAME Consortium. More information can be found at: http://www.fao.org/in-action/remote-sensing-for-water-productivity/en/.

Until December 2019 the base input layers (NDVI, albedo, and fAPAR) for the Level 2 (100m) products were derived from the Proba-V satellite. Proba-V was decommissioned in June 2020. From January 2020 onwards the base input layers of NDVI, albedo and fAPAR for level 2 are derived from the Copernicus Sentinel-2 mission.

Class - Caption

0 - n.a.

20 - Shrubland

30 - Grassland

20 - Shrubland

30 - Grassland

41 - Cropland, rainfed

42 - Cropland, irrigated or under water management

43 - Cropland, fallow

50 - Built-up

60 - Bare / sparse vegetation

70 - Permament snow / ice

80 - Water bodies

81 - Temporary water bodies

90 - Shrub or herbaceous cover, flooded

111 - Tree cover: closed, evergreen needle-leaved

112 - Tree cover: closed, evergreen broadleaved

114 - Tree cover: closed, deciduous broadleaved

115 - Tree cover: closed, mixed type

116 - Tree cover: closed, unknown type

121 - Tree cover: open, evergreen needle-leaved

122 - Tree cover: open, evergreen broadleaved

123 - Tree cover: open, deciduous needle-leaved

124 - Tree cover: open, deciduous broadleaved

125 - Tree cover: open, mixed type

126 - Tree cover: open, unknown type

200 - Sea water

255 - no data

Resource constraints:

Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)

Online resources:

Download: Land Cover Classification (Africa and Near East - Annual - 100m)

Land cover describes what is visible on Earth’s surface, such as forests, grasslands, cropland, and built places. Knowing what land cover is in each location can help us understand a landscape. Tracking land cover over many years can tell us how the landscape is changing over time. It allows us to track urban growth, measure the loss of wetlands and wild places to prioritize conservation and preservation efforts, and plan for the potential impacts of climate change. For example, a study published in Nature (https://doi.org/10.1038/s41467-021-22702-2) found that from 1960-2019, humans changed the use of approximately 32 percent of the land worldwide, an estimated four times higher than previously thought.This map layer was created using data from the Copernicus Sentinel-1 and 2 earth observation satellites collected by the European Space Agency from 2017-2024. This map displays data from 2024. Each value in this map layer applies to a single grid cell, or about 10 square meters (approximately 108 square feet). All these grid cells combined form a raster, a dataset made of rows and columns of cells that include regularly spaced data for all the land area on Earth. If you zoom in, the dataset seems to pixelate. Each pixel is one 10-meter by 10-meter cell (108 feet by 108 feet). Within each cell, the predominant land category is assigned. For example, if the cell overlaps a park with many trees but catches part of the parking lot next to it where hikers leave their cars or bikes, the cell would be classified as tree cover. If you select an imagery basemap and adjust the transparency of the map layer, you will be able to find such examples.The data on this map has been sorted into nine categories (water, trees, flooded vegetation, crops, built area, bare ground, snow and ice, clouds, and rangeland) by a computer using machine learning. Machine learning is part of artificial intelligence. It uses computer systems designed to process large amounts of information and learn and adapt based on the data without specific instructions or code from a programmer. This technology allows us to use data that would otherwise take such a long time to examine it would no longer be useful, as it would be out of data. What is the most common land cover near you?Data CitationKarra, Kontgis, et al. “Global land use/land cover with Sentinel-2 and deep learning.” IGARSS 2021-2021 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2021.AcknowledgementsTraining data for this project makes use of the National Geographic Society Dynamic World training dataset, produced for the Dynamic World Project by National Geographic Society in partnership with Google and the World Resources Institute.

We provide a global spatially explicit characterization of 47 (version 001) terrestrial habitat types, as defined in the International Union for Conservation of Nature (IUCN) habitat classification scheme, which is widely used in ecological analyses, including for assessing species’ Area of Habitat. We produced this novel habitat map by creating a global decision tree that intersects the best currently available global data on land cover, climate and land use. The maps broaden our understanding of habitats globally, assist in constructing area of habitat (AOH) refinements and are relevant for broad-scale ecological studies and future IUCN Red List assessments. We hope that these data and outlined framework will spur further development of biodiversity-relevant habitat maps at global scales. An interactive interface helping to navigate the map can be found at on the Naturemap website ( https://explorer.naturemap.earth/map).

Provided is the code to recreate the map (to made available soon), the global composite image at native -100m Copernicus resolution for level 1 and level 2 and layers of aggregated fractional cover (unit: [0-1] * 1000) at 1km for level 1 and level 2.

Starting with version 004 there changemasks for the years 2016, 2017, 2018 and 2019 are supplied. Changemasks for the composite masks show the changed grid cells and their new values with earlier years being nested in later years, e.g. using the changemask for 2019 includes all changes up to 2019. For the fractional cover estimates at ~1km resolution, new fractional cover changemasks are supplied as subtraction (before - after) between the previous and current year (unit range: [-1 to 1] * 1000).

We highlight that only changes in land cover are considered since most of the ancillary layers (e.g. pasture, forest management, climate, etc...) are static and thus not all changes in habitats can be found. We therefore recommend end users to continue using the 2015 dataset unless specific habitat updates to habitat are needed.

Citation:

Please cite the published paper and state the used version of the habitat map

Jung, M., Dahal, P.R., Butchart, S.H.M., Donald, P.F., De Lamo, X., Lesiv, M., Kapos, V., Rondinini, C., Visconti, P., (2020). A global map of terrestrial habitat types. Sci. Data 7, 256. https://doi.org/10.1038/s41597-020-00599-8

CLC2018 is one of the Corine Land Cover (CLC) datasets produced within the frame the Copernicus Land Monitoring Service referring to land cover / land use status of year 2018, led by the European Environment Agency (EEA). Corine Land Cover (CLC) provides consistent and thematically detailed information on land cover and land cover changes across Europe. CLC products are based on the classification of satellite images by the national teams of the participating countries - the EEA member and cooperating countries. National CLC inventories are further integrated into a seamless land cover map of Europe. The resulting European database relies on standard methodology and nomenclature with following base parameters: 44 classes in the hierarchical 3-level CLC nomenclature; minimum mapping unit (MMU) for status layers is 25 hectares; minimum width of linear elements is 100 metres. The CLC program is also part of the Global Monitoring for Environment and Security (GMES http://gmes.info) initiative, led by the European Agency Commission and the European Space Agency, which will provide environmental information from a combination of observations based on air, space and in situ monitoring systems. Additional information about CLC product description including mapping guides can be found at https://land.copernicus.eu/user-corner/technical-library/clc2018technicalguidelines_final.pdf. CLC class descriptions can be found at https://land.copernicus.eu/user-corner/technical-library/corine-land-cover-nomenclature-guidelines/html/