Researchers developed 4D-FUELS, a semi-automated machine-learning system combining airborne lidar with Sentinel satellite imagery to map fourteen forest structure and ...
Atmospheric simulations show that high-resolution point-source satellite imagers can significantly improve diffuse methane emission estimates across cloudy tropical regions by ...
A multitemporal satellite analysis reveals that urban expansion and reclamation in Teluknaga and Kosambi eliminated over twenty-nine percent of mangrove ...
Satellite tracking of 26 post-mining lakes in Western Poland revealed an overall surface area decrease between 2016 and 2025, alongside ...
A high-resolution machine learning assessment reveals that Canary Island forests store 10.26 teragrams of carbon, driven primarily by forest canopy ...
Researchers in Egypt have developed a remote sensing method that estimates groundwater level fluctuations in arid-zone observation wells by tracking ...
Researchers reconstructed continuous bare soil albedo across European croplands at field scale using Sentinel-2 observations and machine learning, revealing key ...
Researchers have demonstrated a cross-scale remote sensing framework that combines drone hyperspectral estimates with multi-temporal Sentinel satellite imagery to map ...
Remote sensing of Malawi's Bua River catchment reveals that settlement expansion and deforestation significantly altered river channel widths between 2016 ...
A high-resolution Sentinel-2 study mapped 8.33 million hectares of rice residue burning in India during the 2025 Kharif season, estimating ...
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