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💧🌏 Greg CocksGregCocks@techhub.social
2024-12-03

Integrated Topographic Corrections Improve Forest Mapping Using Landsat Imagery
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doi.org/10.1016/j.jag.2022.102 <-- shared 2022 paper
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“HIGHLIGHTS:
• [They] evaluated the impacts of topographic correction on forest mapping in the mountains.
• The enhanced C-correction and the physical model reduced topographic effects.
• The corrected Landsat imagery time series resulted in higher accuracy.
• Terrain information improved classification but not as much as topographic correction.
• [They] recommend using topographic correction for forest cover mapping..."
#GIS #spatial #AtmosphericCorrection #IlluminationCondition #LandCover #ModelComparison #TimeSeries #TopographicCorrection #remotesensing #comparasion #topographic #correction #NDVI #forest #vegetation #model #modeling #spatialanalyis #accuracy #forestcover #Russia #Georgia #CaucasusMountains #spatiotemporal #landsat #elevation #DEM

graphic - Data processing workflowphoto - Mount Elbrusmaps / images - Landsat summer (panel A) and autumn (Panel B) images (RGB: 743) for the study area. Subset region marked in black frame. Panels C-F show uncorrected (panel C), corrected summer image using the enhanced C-correction (panel D) or the physical model (panel E), and the corresponding illumination condition (F). Panels G-J show the same as panel C-F, but for the autumn image. The QA layers generated from FORCE were not applied here.map - Forest cover classification agreement among the 18 sets of input variables. Pixels in red color were classified by all sets of input variables as coniferous, in green color as broadleaf forest, and in blue color as mixed forest. Black color indicates that no forest was predicted by any set of input variables. Two subsets A and B which are marked in white frames were zoomed in for a detailed map comparison in [another figure]
💧🌏 Greg CocksGregCocks@techhub.social
2024-05-02

Study Provides New Global Accounting Of Earth's Rivers
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phys.org/news/2024-04-global-a <-- shared technical article
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doi.org/10.1038/s41561-024-014 <-- shared paper
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#GIS #spatial #mapping #water #hydrology #global #waterresources #model #modeling #numericalmodeling #spatialanalyis #flow #river #storage #watersecurity #spatiotemporal #estimates #management #planning #runoff #remotesensing #earthobservation

maps - global river water storage by basinmaps - global ocean discharge by basinmaps - Global 30-year mean river discharge, corrected using mean observationsaerial photo - Colorado River supplies water to more than 40 million people as it snakes through seven U.S. states, including the part of southeastern Utah seen in this photo snapped by an astronaut aboard the International Space Station. The Colorado basin was identified in a NASA-led study as a region experiencing intense human water use.

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