Global Land Cover and Land Use Change 2000-2020
The GLAD Global Land Cover and Land Use Change dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020 at 30-m spatial resolution. The global dataset derived from the GLAD Landsat Analysis Ready Data. Each thematic product was independently derived using state-of-the-art, locally and regionally calibrated machine learning tools. Each thematic layer was validated independently using a statistical sampling. The dataset includes information on:
<br><div>Annual maps of land cover and land use (2000, 2005, 2010, 2015, 2020)
<br></div><div>Global map with continuous measures of bare ground and tree height inside and outside of wetlands, seasonal water percent, and binary labels of built-up, permanent snow/ice, and cropland.
Net change of land cover and land use between 2000 and 2020 (2000-2020change)</div><div>Land cover and land use states of 2020 with transitions relative to 2020 labelled.</div>
Default
IdentificationAbout this resource
- Alternate Identifier
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832ddf6a-6708-4b7a-aa55-7ca142f9b413
- Publication Date
- 2022-04-13
- Title
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Global Land Cover and Land Use Change 2000-2020
- Short Name
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Global Land Cover and Land Use Change
- Abstract
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The GLAD Global Land Cover and Land Use Change dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020 at 30-m spatial resolution. The global dataset derived from the GLAD Landsat Analysis Ready Data. Each thematic product was independently derived using state-of-the-art, locally and regionally calibrated machine learning tools. Each thematic layer was validated independently using a statistical sampling. The dataset includes information on:
<br><div>Annual maps of land cover and land use (2000, 2005, 2010, 2015, 2020)
<br></div><div>Global map with continuous measures of bare ground and tree height inside and outside of wetlands, seasonal water percent, and binary labels of built-up, permanent snow/ice, and cropland.
Net change of land cover and land use between 2000 and 2020 (2000-2020change)</div><div>Land cover and land use states of 2020 with transitions relative to 2020 labelled.</div>
- Dataset Language
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English
- Dataset Creator
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- Metadata Provider
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- Keywords (None)
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Land cover
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Land use
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Global
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Terrestrial
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Geographic Coverage
- Geographic Description
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Global
Bounding Box
- West Bounding Coordinate
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-180
- East Bounding Coordinate
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180
- North Bounding Coordinate
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90
- South Bounding Coordinate
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-90
Bounding Altitudes
- Minimum
- Maximum
- Unit
Temporal Coverage
Range of Dates
- Begin Date
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2000-01-01
- End Date
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2020-12-31
resourceLicensesLicense Information
- Intellectual Rights
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This work is licensed under a Creative Commons Attribution 4.0 International License
Distribution
Online
- A brief description of the the content of online URL.
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Annual maps of land cover and land use (2000)
Distribution
Online
- A brief description of the the content of online URL.
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Annual maps of land cover and land use (2005)
Distribution
Online
- A brief description of the the content of online URL.
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Annual maps of land cover and land use (2010)
Distribution
Online
- A brief description of the the content of online URL.
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Annual maps of land cover and land use (2015)
Distribution
Online
- A brief description of the the content of online URL.
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Annual maps of land cover and land use (2020)
Distribution
Online
- A brief description of the the content of online URL.
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Net change of land cover and land use between 2000 and 2020
Distribution
Online
- A brief description of the the content of online URL.
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Global Land Cover and Land Use 2000-2020
Project
• Project
- Title
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Global Land Cover and Land Use 2000 and 2020
- Abstract
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Recent advances in Landsat archive data processing and characterization enhanced our capacity to map land cover and land use globally with higher precision, temporal frequency, and thematic detail. Here, we present the first results from a project aimed at annual multidecadal land monitoring providing critical information for tracking global progress towards sustainable development. The global 30-m spatial resolution dataset quantifies changes in forest extent and height, cropland, built-up lands, surface water, and perennial snow and ice extent from the year 2000 to 2020. Landsat Analysis Ready Data served as an input for land cover and use mapping. Each thematic product was independently derived using locally and regionally calibrated machine learning tools. Thematic maps validation using a statistical sample of reference data confirmed their high accuracy (user’s and producer’s accuracies above 85% for all land cover and land use themes, except for built-up lands). Our results revealed dramatic changes in global land cover and land use over the past 20 years. The bitemporal dataset is publicly available and serves as a first input for the global land monitoring system.
Personnel
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Individual Name
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Methods
• Method
Method Step
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Most global thematic products, except open water, were derived using consistently processed Landsat Analysis Ready Data produced by the Global Land Analysis and Discovery laboratory (GLAD) at the University of Maryland. The annual GLAD data time series were integrated into a set of phenology metrics that enabled global model calibration and application. They used a separate supervised classification model to map each thematic class. Individual decision tree models calibrated with manually collected training data were implemented for cropland and perennial snow and ice mapping. Forest height was estimated using a regression tree model calibrated with Global Ecosystem Dynamics Investigation Lidar (GEDI) forest structure measurements. Built-up lands were mapped using a deep learning convolution neural network (CNN) algorithm trained with Open Street Map (OSM) data. The models were calibrated locally (for forest height and cropland mapping) or regionally (other products). Surface water mapping utilised pre-scene Landsat data classification and time series analysis in Google Earth Engine. We independently validated each global thematic product using statistical sample analysis. The sample reference data were collected through visual interpretation of the best available high-resolution satellite images and Landsat time series. Files are named as follows: [coordinate]_[coordinate].tif
- Citation
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Potapov, P., Hansen, M. C., Pickens, A., Hernandez-Serna, A., Tyukavina, A., Turubanova, S., ... Kommareddy, A. (2022). The global 2000-2020 land cover and land use change dataset derived from the Landsat archive: first results. Frontiers in Remote Sensing, 3, 856903. https://doi.org/10.3389/frsen.2022.856903.
Software
- Title
- Version
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2.0
Data Tables
• Data Table
- Name
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2000
Physical
Data Format
Externally Defined Format
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GeoTIFF
• Data Table
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2005
Physical
Data Format
Externally Defined Format
- Format Name
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GeoTIFF
• Data Table
- Name
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2010
Physical
Data Format
Externally Defined Format
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GeoTIFF
• Data Table
- Name
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2015
Physical
Data Format
Externally Defined Format
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GeoTIFF
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- Name
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2020
Physical
Data Format
Externally Defined Format
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GeoTIFF
• Data Table
- Name
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2000-2020change
Physical
Data Format
Externally Defined Format
- Format Name
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GeoTIFF
