AI Learns to Grade Riverbank Health From Space Using Satellite Photos
Canadian researchers have trained a multi-view convolutional neural network to assess riparian buffer strip quality directly from high-resolution satellite imagery, ...
Canadian researchers have trained a multi-view convolutional neural network to assess riparian buffer strip quality directly from high-resolution satellite imagery, ...
A yearlong Stanford-led experiment with 481 controlled methane releases found that dedicated methane-detecting satellites correctly identified nearly all plumes on ...
By fusing L-band radar from ALOS-2 with Sentinel-2 optical data and a weighted machine learning ensemble, researchers have mapped above-ground ...
Researchers in Iran combined Sentinel-2 satellite data, hybrid machine learning, and game theory to rank groundwater quality parameters, finding that ...
A three-decade satellite-based assessment reveals that vegetation condition and annual precipitation are the dominant drivers of landscape ecological risk in ...
A two-decade satellite analysis of Dehradun shows built-up area growing nearly 140 percent while groundwater quality, air quality, and waste ...
A remote sensing and machine learning study of Poyang Lake reveals that extreme precipitation drives wetland plant diversity through scale-dependent ...
New Virginia Tech research combining NASA GRACE satellite data with hydrologic estimates shows that the Colorado River Basin's Upper Basin, ...
A new satellite-based cross-border study shows that nearly 90 per cent of mapped Alpine peatlands in Austria, Germany and Switzerland ...
Egyptian researchers used Landsat 8 imagery and machine learning to map the bathymetry of Manzala Lagoon with centimeter-level accuracy, identifying ...
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© 2025 Scienmag - Science Magazine