37ed544d-6e02-411b-af7e-9df9e4384413 Global Forest Change University of Maryland Matthew Hansen Professor mhansen@umd.edu https://orcid.org/0000-0003-0042-2767 University of Maryland Peter Potapov Research Professor potapov@umd.edu https://orcid.org/0000-0003-3977-0021 Google Rebecca Moore Software engineer Google Matt Hancher Engineering Lead University of Maryland Svetlana Turubanova Assistant Research Scientist sveta@umd.edu https://orcid.org/0000-0001-6386-156X University of Maryland Alexandra Tyukavina Associate Research Professor atyukav@umd.edu https://orcid.org/0000-0003-3872-9844 Google David Thau https://orcid.org/0000-0001-8598-9820 State University of New York Stephen Stehman Distinguished Teaching Professor svstehma@esf.edu Woods Hole Research Center Scott Goetz Senior Scientist Scott.Goetz@nau.edu https://orcid.org/0000-0002-6326-4308 United States Geological Survey Thomas Loveland Chief Scientist loveland@usgs.gov https://orcid.org/0000-0003-3114-6646 South Dakota State University Anil Kommareddy IT Systems Analyst anilk@umd.edu South Dakota State University Alexey Egorov alexey.egorov@sdstate.edu University of Maryland Louise Chini Research Assistant Professor chini@umd.edu https://orcid.org/0000-0002-9070-3505 University of Maryland Chris Justice Distinguished University Professor cjustice@umd.edu University of Maryland John Townshend Emeritus Professor jtownshe@umd.edu SIB Swiss Institute of Bioinformatics Chiara Bortoluzzi Data Manager chiara.bortoluzzi@sib.swiss https://orcid.org/0000-0001-6589-6635 2013-11-15 English This dataset provides maps of global tree cover extent, loss, and gain for the period from 2000 to 2024. The dataset is divided into 10x10 degree tiles with a spatial resolution of 1 arc-second per pixel, or approximately 30 meters per pixel at the equator. Derived from time-series analysis of Landsat images, the dataset includes information on: <br><div>Tree canopy cover for year 2000 (treecover2000) Tree cover in the year 2000, defined as canopy closure for all vegetation taller than 5m in height. Encoded as a percentage per output grid cell, in the range 0-100. <br></div><div>Global forest cover gain (2000-2021) (gain) Forest gain during the period 2000-2012, defined as the inverse of loss, or a non-forest to forest change entirely within the study period. Encoded as either 1 (gain) or 0 (no gain). <br></div><div>Year of gross forest cover loss event (lossyear) Forest loss during the period 2000-2024, defined as a stand-replacement disturbance, or a change from a forest to non-forest state. Encoded as either 0 (no loss) or else a value in the range 1-20, representing loss detected primarily in the year 2001-2024, respectively. <br></div><div>Data mask (datamask) Three values representing areas of no data (0), mapped land surface (1), and persistent water bodies (2) based on 2000-2012. <br></div><div>Circa year 2000 Landsat 7 cloud-free image composite (first) Reference multispectral imagery from the first available year, typically 2000. If no cloud-free observations were available for year 2000, imagery was taken from the closest year with cloud-free data, within the range 1999-2012. <br></div><div>Circa year 2024 Landsat cloud-free image composite (last) Reference multispectral imagery from the last available year, typically 2024. If no cloud-free observations were available for the year 2024, imagery was taken from the closest year with cloud-free data.</div> Tree cover Forest gain Forest loss Forest change None This work is licensed under a Creative Commons Attribution 4.0 International License Creative Commons CC0 https://creativecommons.org/licenses/by/4.0/ Tree canopy cover for the year 2000 https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/treecover2000.txt Global forest cover gain over the period 2000-2012 https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/gain.txt Year of gross forest cover loss event https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/lossyear.txt Data mask for the period 2000-2012 https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/datamask.txt Circa year 2000 Landsat 7 cloud-free image composite (first year) https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/first.txt Circa year 2024 Landsat cloud-free image composite (last year) https://storage.googleapis.com/earthenginepartners-hansen/GFC-2024-v1.12/last.txt Global -180 180 90 -90 2000-01-01 2024-12-31 University of Maryland Matthew Hansen Professor mhansen@umd.edu The study analyzed global land areas (excluding Antarctica and some Arctic islands), covering 128.8 million km², equivalent to 143 billion Landsat 30m pixels. Trees were defined as vegetation taller than 5 meters. Forest loss was defined as a stand-replacement disturbance, while forest gain was the inverse of loss, or a non-forest to forest change. Gain was related to percent tree crown cover densities greater than 50% and reported as a 12 year total. Files are named as follows: Hansen_GFC-2024-v1.12_[variable_name]_[coordinate]_[coordinate].tif Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342 (15 November): 850-53. https://doi.org/10.1126/science.1244693. The Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland, in partnership with Global Forest Watch (GFW), provides annually updated global-scale forest loss data, derived using Landsat time-series imagery. These data are a relative indicator of spatio-temporal trends in forest loss dynamics globally. University of Maryland Global Forest Watch (GFW) treecover2000 GeoTIFF gain GeoTIFF lossyear GeoTIFF datamask GeoTIFF first GeoTIFF last GeoTIFF