Land Cover Vulnerability to Change 2050 - Global

Predicted vulnerability to land cover change by year 2050, as generated by Clark Labs. Vulnerability to change was modeled globally. A value of 1 means the pixel is among the most vulnerable to change, while a value of 0 means the pixel is among the least vulnerable.

Use this global model layer when performing analysis across continents. This layer displays predictions globally of relative vulnerability to modification by humans by the year 2050.  ESA CCI land cover maps from the years 2010 and 2018 were used to create this prediction.   Variable mapped: Vulnerability of land cover to anthropogenic change by 2050. Data Projection: Cylindrical Equal Area Mosaic Projection: Cylindrical Equal Area Extent: Global   Cell Size: 300m Source Type: Thematic Visible Scale: 1:50,000 and smaller Source: Clark University Publication date: April 2021 Analysis: Optimized for analysis   What you can do with this layer?   This layer can be used in analysis, to estimate and compare vulnerability to land cover change globally due to expansion of human activity, by 2050.     This layer is useful in ecological planning, helping to prioritize areas for conservation.     Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See the Living Atlas Imagery Layers Optimized for Analysis Group for a complete list of imagery layers optimized for analysis.    Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World: There are three scales (country, regional, and global) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between proximate countries, use the country level. If mapping larger patterns or vastly separated countries, use the global or regional extent (depending on your area of interest).    Land Cover 2050  - Global
  Land Cover 2050 - Regional
  Land Cover 2050 - Country
  Land Cover Vulnerability to Change 2050 Global
  Land Cover Vulnerability to Change 2050 Regional
  Land Cover Vulnerability to Change 2050 Country
    What these layers model (and what they don’t model)   The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many.   The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use.   Quantitative Variables used to create Models
  • Biomass
  • Crop Suitability
  • Distance to Airports
  • Distance to Cropland 2010
  • Distance to Primary Roads
  • Distance to Railroads
  • Distance to Secondary Roads
  • Distance to Settled Areas
  • Distance to Urban 2010
  • Elevation
  • GDP
  • Human Influence Index
  • Population Density
  • Precipitation
  • Regions  
  • Slope
  • Temperature
  Qualitative Variables used to create Models
  • Biomes
  • Ecoregions
  • Irrigated Crops
  • Protected Areas
  • Continent
  • Country
  • Rainfed Crops
  • Soil Classification
  • Soil Depth
  • Soil Drainage
  • Soil pH
  • Soil Texture

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Additional Info

Field Value
Last Updated March 24, 2026, 21:07 (UTC)
Created March 24, 2026, 21:04 (UTC)
Domain / Topic
Domain or topic of the dataset being cataloged.
Title
Title for the Dataset.
Land Cover Vulnerability to Change 2050 - Global
Description
A description of the dataset.

Predicted vulnerability to land cover change by year 2050, as generated by Clark Labs. Vulnerability to change was modeled globally. A value of 1 means the pixel is among the most vulnerable to change, while a value of 0 means the pixel is among the least vulnerable.

Use this global model layer when performing analysis across continents. This layer displays predictions globally of relative vulnerability to modification by humans by the year 2050.  ESA CCI land cover maps from the years 2010 and 2018 were used to create this prediction.   Variable mapped: Vulnerability of land cover to anthropogenic change by 2050. Data Projection: Cylindrical Equal Area Mosaic Projection: Cylindrical Equal Area Extent: Global   Cell Size: 300m Source Type: Thematic Visible Scale: 1:50,000 and smaller Source: Clark University Publication date: April 2021 Analysis: Optimized for analysis   What you can do with this layer?   This layer can be used in analysis, to estimate and compare vulnerability to land cover change globally due to expansion of human activity, by 2050.     This layer is useful in ecological planning, helping to prioritize areas for conservation.     Optimized for analysis means this layer does not have size constraints for analysis and it is recommended for multisource analysis with other layers optimized for analysis. See the Living Atlas Imagery Layers Optimized for Analysis Group for a complete list of imagery layers optimized for analysis.    Links to the six Clark University land cover 2050 layers in ArcGIS Living Atlas of the World: There are three scales (country, regional, and global) for the land cover and vulnerability models. They’re all slightly different since the country model can be more fine-tuned to the drivers in that particular area. Regional (continental) and global have more spatially consistent model weights. Which should you use? If you’re analyzing one country or want to make accurate comparisons between proximate countries, use the country level. If mapping larger patterns or vastly separated countries, use the global or regional extent (depending on your area of interest).    Land Cover 2050  - Global
  Land Cover 2050 - Regional
  Land Cover 2050 - Country
  Land Cover Vulnerability to Change 2050 Global
  Land Cover Vulnerability to Change 2050 Regional
  Land Cover Vulnerability to Change 2050 Country
    What these layers model (and what they don’t model)   The model focuses on human-based land cover changes and projects the extent of these changes to the year 2050. It seeks to find where agricultural and urban land cover will cover the planet in that year, and what areas are most vulnerable to change due to the expansion of the human footprint. It does not predict changes to other land cover types such as forests or other natural vegetation during that time period unless it is replaced by agriculture or urban land cover. It also doesn’t predict sea level rise unless the model detected a pattern in changes in bodies of water between 2010 and 2018. A few 300m pixels might have changed due to sea level rise during that timeframe, but not many.   The model predicts land cover changes based upon patterns it found in the period 2010-2018. But it cannot predict future land use. This is partly because current land use is not necessarily a model input. In this model, land set aside as a result of political decisions, for example military bases or nature reserves, may be found to be filled in with urban or agricultural areas in 2050. This is because the model is blind to the political decisions that affect land use.   Quantitative Variables used to create Models
  • Biomass
  • Crop Suitability
  • Distance to Airports
  • Distance to Cropland 2010
  • Distance to Primary Roads
  • Distance to Railroads
  • Distance to Secondary Roads
  • Distance to Settled Areas
  • Distance to Urban 2010
  • Elevation
  • GDP
  • Human Influence Index
  • Population Density
  • Precipitation
  • Regions  
  • Slope
  • Temperature
  Qualitative Variables used to create Models
  • Biomes
  • Ecoregions
  • Irrigated Crops
  • Protected Areas
  • Continent
  • Country
  • Rainfed Crops
  • Soil Classification
  • Soil Depth
  • Soil Drainage
  • Soil pH
  • Soil Texture
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Dataset Size
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0.08
Metadata Identifier
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Published Date
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2021-07-09
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GeoSpatial Area Data Span
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Field Value
Access category
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public
License
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Creative Commons Attribution
Limits on use
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Location
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https://climat.esri.ca/datasets/esri::land-cover-vulnerability-to-change-2050-global
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Owner
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esri_environment
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Esri
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Esri
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Author
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esri_environment
Author Email
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Accessed At
Date the data and metadata was accessed.
2025-10-29
Field Value
Identifier
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4040cafb922440f59d3ce52326402875
Language
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English
Link to dataset description
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https://climat.esri.ca/datasets/esri::land-cover-vulnerability-to-change-2050-global
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Contains data about individuals
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Contains Indigenous Data
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Version
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None
Source
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None
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Esri
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Temporal resolution
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GeoSpatial resolution in meters
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GeoSpatial resolution (in regions)
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Field Value
Indigenous Community Permission
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Community Permission
Community permission (who gave permission).
The Indigenous communities the dataset is about
Indigenous communities from which data is derived.
Field Value
Number of data rows
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4
Number of data columns
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16
Number of data cells
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64
Number of data relations
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