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Anil Kommareddy

Researcher at University of Maryland, College Park

Publications -  26
Citations -  9078

Anil Kommareddy is an academic researcher from University of Maryland, College Park. The author has contributed to research in topics: Bubble & Photobioreactor. The author has an hindex of 12, co-authored 25 publications receiving 6920 citations. Previous affiliations of Anil Kommareddy include South Dakota State University.

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High-Resolution Global Maps of 21st-Century Forest Cover Change

TL;DR: Intensive forestry practiced within subtropical forests resulted in the highest rates of forest change globally, and boreal forest loss due largely to fire and forestry was second to that in the tropics in absolute and proportional terms.
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Mapping global forest canopy height through integration of GEDI and Landsat data

TL;DR: In this paper, the Global Ecosystem Dynamics Investigation (GEDI) lidar instrument onboard the International Space Station has been collecting unique data on vegetation structure since April 2019, and the authors employed global Landsat analysis-ready data to extrapolate GEDI footprint-level forest canopy height measurements.
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Surface water extent dynamics from three decades of seasonally continuous Landsat time series at subcontinental scale in a semi-arid region

TL;DR: In this article, the authors used seasonally continuous Landsat TM/ETM+ data and generic random forest-based models to synoptically map the extent and dynamics of surface water and flooding (1986-2011) over the Murray-Darling Basin (MDB).
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Monitoring conterminous United States (CONUS) land cover change with Web-Enabled Landsat Data (WELD)

TL;DR: In this paper, forest cover loss and bare ground gain from 2006 to 2010 for the conterminous United States (CONUS) were quantified at a 30-m spatial resolution using Web-enabled Landsat Data available from the USGS Center for Earth Resources Observation and Science (EROS) ( http://landsat.cr.usgs.gov/WELD.php ).
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Landsat Analysis Ready Data for Global Land Cover and Land Cover Change Mapping

TL;DR: 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.