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A Preliminary Global Automatic Burned-Area Algorithm at Medium Resolution in Google Earth Engine.

, , , and . Remote. Sens., 13 (21): 4298 (2021)

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Can We Go Beyond Burned Area in the Assessment of Global Remote Sensing Products with Fire Patch Metrics?, , , and . Remote Sensing, 9 (1): 7 (2017)Developing a Random Forest Algorithm for MODIS Global Burned Area Classification., and . Remote Sensing, 9 (11): 1193 (2017)Landsat and Sentinel-2 Based Burned Area Mapping Tools in Google Earth Engine., , , and . Remote. Sens., 13 (4): 816 (2021)Implementation of the Burned Area Component of the Copernicus Climate Change Service: From MODIS to OLCI Data., , , , , and . Remote. Sens., 13 (21): 4295 (2021)A Preliminary Global Automatic Burned-Area Algorithm at Medium Resolution in Google Earth Engine., , , and . Remote. Sens., 13 (21): 4298 (2021)Fire danger assessment in Iran based on geospatial information., and . Int. J. Appl. Earth Obs. Geoinformation, (2015)Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: analysis at leaf and canopy level., , , , and . IEEE Trans. Geosci. Remote. Sens., 43 (4): 819-826 (2005)Mapping the Spatial Distribution of Forest Fire Danger Using GIS., and . Int. J. Geogr. Inf. Sci., 10 (3): 333-345 (1996)Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types (2003)., , , and . IEEE Trans. Geosci. Remote. Sens., 41 (5): 1056-1061 (2003)Introduction to the Issue on Wildland Fires and Biomass Burning., , and . IEEE J Sel. Topics in Appl. Earth Observ. and Remote Sensing, 1 (4): 218-219 (2008)