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

This dataset provides global maps describing the land surface into 22 classes, which have been defined using the United Nations Food and Agriculture Organization’s (UN FAO) Land Cover Classification System (LCCS). In addition to the land cover (LC) maps, four quality flags are produced to document the reliability of the classification and change detection. In order to ensure continuity, these land cover maps are consistent with the series of global annual LC maps from the 1990s to 2015 produced by the European Space Agency (ESA) Climate Change Initiative (CCI), which are also available on the ESA CCI LC viewer. To produce this dataset, the entire Medium Resolution Imaging Spectrometer (MERIS) Full and Reduced Resolution archive from 2003 to 2012 was first classified into a unique 10-year baseline LC map. This is then back- and up-dated using change detected from (i) Advanced Very-High-Resolution Radiometer (AVHRR) time series from 1992 to 1999, (ii) SPOT-Vegetation (SPOT-VGT) time series from 1998 to 2012 and (iii) PROBA-Vegetation (PROBA-V), Sentinel-3 OLCI (S3 OLCI) and Sentinel-3 SLSTR (S3 SLSTR) time series from 2013. Beyond the climate-modelling communities, this dataset’s long-term consistency, yearly updates, and high thematic detail on a global scale have made it attractive for a multitude of applications such as land accounting, forest monitoring and desertification, in addition to scientific research.

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.

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 dataset contains 100m x 100m maps of cover fraction expressed in % ground cover per pixel for 10 base classes including moss & lichen for years 2015 to 2019.

The geographical area of interest corresponds to the Troms and Finnmark counties in Norway.

Along with 10.5281/zenodo.8142713 this is to be used as input to forecast vegetation browning in Troms and Finnmark using machine learning.

As part of the ESA Land Cover Climate Change Initiative (CCI) project a new set of Global Land Cover Maps have been produced. These maps are available at 300m spatial resolution for each year between 1992 and 2015.Each pixel value corresponds to the classification of a land cover class defined based on the UN Land Cover Classification System (LCCS). The reliability of the classifications made are documented by the four quality flags (decribed further in the Product User Guide) that accompany these maps. Data are provided in both NetCDF and GeoTiff format.Further Land Cover CCI products, user tools and a product viewer are available at: http://maps.elie.ucl.ac.be/CCI/viewer/index.php . Maps for the 2016-2020 time period have been produced in the context of the Copernicus Climate Change service, and can be downloaded from the Copernicus Climate Data Store (CDS).

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.

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

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 land cover dataset at continental scale is based on the Copernicus Global Land cover map. WaPOR data adds, on top of the Copernicus map, the distinction between irrigated and rainfed areas. It is published on a yearly basis. The data is provided in near real time from January 2009 to present.

Land Cover Classification covering the Nura-Sarysu Water Economic basin with complete drainage area of the Nura and Sarysu rivers and Lake Tengiz with buffer. This land cover dataset is based on the Copernicus GLobal Land Service. More information can be found at: https://land.copernicus.eu/global/products/lc

This hybrid 100-m CGLC-MODIS-LCZ global land cover dataset is produced for the Weather Research and Forecasting (WRF) model starting from version 4.5. It is based on 1) the Copernicus Global Land Service Land Cover (CGLC, Buchhorn et al., 2021) product resampled to MODIS IGBP classes (CGLC-MODIS), and 2) the global map of Local Climate Zones (LCZ, Demuzere et al., 2022a, b) that describes the urban and built-up land surface. Both the CGLC and LCZ products are available at a 100-m spatial resolution, are representative for the year 2018, and cover -180°W to 180°E and -60°S to 78°N. Remaining areas are filled with the MODIS land cover classes. This dataset has been implemented into the WRF Preprocessing System (WPS) as tiled binary data files with a new GEOGRID table entry to allow WRF/WPS users to flexibly use this dataset in their studies particularly for urban modeling applications.

To display the dataset in QGIS, cmap_Qgis_CGLC_MOD_LCZ.txt can be used as a color scheme.

For more details, please read the technical documentation: https://doi.org/10.5281/zenodo.7670792.

References:

Buchhorn, M., Smets, B., Bertels, L., De Roo, B., Lesiv, M., Tsendbazar, N.-E., Li, L., Tarko, A. Copernicus Global Land Service: Land Cover 100m: version 3 Globe 2015-2019: Product User Manual (Dataset v3.0, doc issue 3.4). Product User Manual; Zenodo, Geneve, Switzerland, September 2020; doi: 10.5281/zenodo.3938963

Demuzere M, Kittner J, Martilli A, et al. A global map of local climate zones to support earth system modelling and urban-scale environmental science. Earth Syst Sci Data. 2022a;14(8):3835-3873. doi:10.5194/essd-14-3835-2022

Demuzere M, Kittner J, Martilli A, et al. (2022). Global map of Local Climate Zones (2.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.6364593

Land cover and land cover change maps were created within the European Commission's Copernicus Global Land Monitoring Service's Hot-Spot Monitoring framework program. During the program's first phase, a total of 560442km2 area in Sub-Saharan Africa was mapped, from which 153665km2 was mapped with 8 land cover classes while 406776km2 was mapped with up to 32 classes based on FAO's Land Cover Classification System (LCCS). High-resolution optical satellite imagery were used to generate dense time-series data from which thematic land cover and change maps were derived. Each map was fully verified and validated by an independent team to achieve Copernicus' strict data quality requirements. Independent validation datasets for each KLCs were also collected and they are presented here. The validation datasets contain 35671 verified points for two dates (LC and LCC). Furthermore, a predefined symbology (QGIS legend file) for the land cover/change and validation datasets based on FAO's Land Cover Classification System is also shared here to ease the visualization of them. Further details regarding the sites selection, mapping and validation procedures are described in the corresponding publication: Szantoi, Z., Brink, A., Lupi, A., Mannone, C., and Jaffrain, G.: Key Landscapes for Conservation Land Cover and Change Monitoring, Thematic and Validation Datasets for Sub-Saharan Africa, Earth Syst. Sci. Data, 12-3001-2020, https://doi.org/10.5194/essd-12-3001-2020.

This dataset comprises a collection of high-resolution Sentinel-2 derived forest class maps and aggregated upscaled forest class maps from the Copernicus Global Land Service (CGLC) 100 m representing forested land in selected regions of Western Yakutia and Chukotka, in Eastern Siberia, Russia. The dataset is organized into three product groups, each containing geospatial data in GeoTIFF format. RegionalCode_classified-forest_S2_LS_10m products: These products are Sentinel-2 derived maps with a spatial resolution of 10 meters for the following locations: Lake Khamra (LK), Yakutsk (YA), Magaras (MA), Mirny (MI), Mirny-Lensk (ML), Nyurba (NY), Vilnius (VI), Suntar (SU), Suntar-West (SW) in Western Yakutia, and Bilibino (BI), in Chukotka. The preprocessed and optimized Sentinel-2 images used for the forest type classification are from our previous publication: van Geffen, Femke; Geng, Rongwei; Pflug, Bringfried; Kruse, Stefan; Pestryakova, Luidmila A; Herzschuh, Ulrike; Heim, Birgit (2021): SiDroForest: Sentinel-2 Level-2 Bottom of Atmosphere labelled image patches with seasonal information for Central Yakutia and Chukotka vegetation plots (Siberia, Russia) [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.933268. The forest class maps classify the land into four classes: evergreen needleleaf forest (class value 1), summergreen needleleaf forest (class value 2), mixed forest (class value 3), and non-forested land (class value 0). The evergreen forest class includes tree taxa such as Pine and Spruce and the summergreen forest class represents two larch species (Larix cajanderi and Larix gmelinii) common to these regions. This classification is based on the Random Forest algorithm using late summer Sentinel-2 multispectral data as detailed in the study by van Geffen et al. (submitted). RegionalCode_aggregated-forest_100mLandCover2019_10m: These products are aggregated and upsampled maps based on the 100 m Copernicus Global Land Service 100 m 2019 (reference) data, with the resolution refined from 100 meters to 10 meters. The land cover classes have been aggregated to match the classification scheme of the Sentinel-2 derived forest type maps: open and closed evergreen forests (111, 121), open and closed summergreen forests (113, 123), and open and closed mixed forests (115, 125) have been reclassified into three forest classes (1, 2, 3) and non-forested land (0). This adaptation facilitates direct comparison between the Sentinel-2 forest type maps and the upsampled global land cover data, enabling more precise spatial analysis. RegionalCode_unknown-forest_100mLandCover2019_10m: These products are the upsampled 10-meter resolution maps for two unknown forest classes (116 and 126) identified in the Copernicus Global Land Service 100 m 2019 (reference) dataset. These classes remain distinct from the aggregated classes allowing for further study and comparison. This dataset is intended to support research in forest classification, land cover analysis, and ecological studies in Siberia, providing a valuable resource for understanding the complex vegetation dynamics in these remote regions. The use of both high-resolution Sentinel-2 data at a 10 m resolution and aggregated global land cover data sampled to 10 m resolution enables a comprehensive assessment of forest types across varying spatial resolutions and classifications.

The FAOSTAT domain Land Cover under the Agri-Environmental Indicators section contains land cover information organized by the land cover classes of the international standard system for Environmental and Economic Accounting Central Framework (SEEA CF). The land cover information is compiled from publicly available Global Land Cover (GLC) maps: a) MODIS land cover types based on the Land Cover Classification System, LCCS (2001–2021); b) The European Spatial Agency (ESA) Climate Change Initiative (CCI) annual land cover maps (1992–2020) produced by the Université catholique de Louvain (UCL)-Geomatics and now under the European Copernicus Program; c) The annual land cover maps which were produced under the European Copernicus Global Land Service (CGLS) (CGLS land cover, containing discrete land cover categorization for the period 2015–2019), with spatial resolution 100m; and d) 4) The WorldCover maps of the European Space Agency —available for the years 2020 and 2021, produced at 10m resolution.

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 land cover dataset at continental scale is based on the Copernicus Global Land cover map. WaPOR data adds, on top of the Copernicus map, the distinction between irrigated and rainfed areas. It is published on a yearly basis. 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 1. 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. 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/

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:

Land Cover Classificatio (Africa and Near East - Annual)

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