Pulse Brain · Growing Health Evidence Index
Peer-reviewed

The Global 2000-2020 Land Cover and Land Use Change Dataset Derived From the Landsat Archive: First Results

Peter Potapov; Matthew C. Hansen; Amy Pickens; Andrés Hernández-Serna; Alexandra Tyukavina; Svetlana Turubanova; Viviana Zalles; Xinyuan Li; Ahmad Khan; Fred Stolle; Nancy L. Harris; Xiao‐Peng Song; Antoine Baggett; Indrani Kommareddy; Anil Kommareddy

Frontiers in Remote Sensing · 2022

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Summary

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 usin

Source type
Peer-reviewed study
DOI
10.3389/frsen.2022.856903
Catalogue ID
NRmo9rin9c-0ro
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