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Article

Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping

Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA
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Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(3), 426; https://doi.org/10.3390/rs12030426
Received: 30 December 2019 / Revised: 22 January 2020 / Accepted: 26 January 2020 / Published: 29 January 2020
(This article belongs to the Special Issue Regional and Global Land Cover Mapping)
The multi-decadal Landsat data record is a unique tool for global land cover and land use change analysis. However, the large volume of the Landsat image archive and inconsistent coverage of clear-sky observations hamper land cover monitoring at large geographic extent. Here, we present a consistently processed and temporally aggregated Landsat Analysis Ready Data produced by the Global Land Analysis and Discovery team at the University of Maryland (GLAD ARD) suitable for national to global empirical land cover mapping and change detection. The GLAD ARD represent a 16-day time-series of tiled Landsat normalized surface reflectance from 1997 to present, updated annually, and designed for land cover monitoring at global to local scales. A set of tools for multi-temporal data processing and characterization using machine learning provided with GLAD ARD serves as an end-to-end solution for Landsat-based natural resource assessment and monitoring. The GLAD ARD data and tools have been implemented at the national, regional, and global extent for water, forest, and crop mapping. The GLAD ARD data and tools are available at the GLAD website for free access. View Full-Text
Keywords: Landsat; analysis ready data; surface reflectance; land surface phenology; image compositing; multi-temporal metrics; land cover; land cover change; time-series analysis; global analysis Landsat; analysis ready data; surface reflectance; land surface phenology; image compositing; multi-temporal metrics; land cover; land cover change; time-series analysis; global analysis
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MDPI and ACS Style

Potapov, P.; Hansen, M.C.; Kommareddy, I.; Kommareddy, A.; Turubanova, S.; Pickens, A.; Adusei, B.; Tyukavina, A.; Ying, Q. Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping. Remote Sens. 2020, 12, 426. https://doi.org/10.3390/rs12030426

AMA Style

Potapov P, Hansen MC, Kommareddy I, Kommareddy A, Turubanova S, Pickens A, Adusei B, Tyukavina A, Ying Q. Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping. Remote Sensing. 2020; 12(3):426. https://doi.org/10.3390/rs12030426

Chicago/Turabian Style

Potapov, Peter, Matthew C. Hansen, Indrani Kommareddy, Anil Kommareddy, Svetlana Turubanova, Amy Pickens, Bernard Adusei, Alexandra Tyukavina, and Qing Ying. 2020. "Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping" Remote Sensing 12, no. 3: 426. https://doi.org/10.3390/rs12030426

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