University of Maryland

The University of Maryland (UMD), a public research university founded in 1856 and located in College Park, Maryland, operates the Global Land Analysis & Discovery (GLAD) laboratory within its Department of Geographical Sciences.^[1][2] GLAD is the primary research unit relevant to EO-Atlas: it produces satellite-derived global land cover and forest change datasets that underpin operational forest monitoring worldwide.

GLAD's foundational output is the Hansen Global Forest Change dataset, a joint product of UMD, Google, USGS, and NASA.^[2] First published in 2013, the dataset maps annual global forest loss and gain at 30-metre resolution from Landsat imagery, covering 2000-2025 in its current version (v1.13).^[3][2] The 2013 Science paper introducing the dataset has accumulated over 14,000 citations, establishing the methodology as the reference approach for global-scale forest cover change monitoring.

Building on this foundation, GLAD operates two near-real-time forest disturbance alert systems. The GLAD-L alert system uses Landsat imagery to detect tropical forest disturbance at 30-metre resolution.^[4] The GLAD-S2 alert system extends this to 10-metre resolution using Sentinel-2 data, expanding detection sensitivity to smaller clearing events. Both are distributed via the Global Forest Watch platform (operated by WRI) and via the GLAD Earth Engine application portal.

UMD researchers also contributed to the RADD (Radar for Detecting Deforestation) alert system, which uses Sentinel-1 SAR data to detect disturbance through cloud cover. RADD is led by Wageningen University and Research (WUR); the UMD contribution was methodological rather than operational leadership.^[5]

The GLAD lab is led by Professor Matthew C. Hansen and Research Professor Peter V. Potapov.^[4][2] Both are affiliated with the Department of Geographical Sciences at UMD and have co-authored the primary peer-reviewed papers underpinning all major GLAD products.