Sentinel-1

Remote Sensing of Soil Moisture
Soil moisture is an essential climate variable and knowledge about its state and dynamics is vital for numerous applications, from …
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DeepForest: Novel Deep Learning Models for Land Use and Land Cover Classification Using Multi-Temporal and -Modal Sentinel Data of the Amazon Basin
Land use and land cover (LULC) mapping is a powerful tool for monitoring large areas. For the Amazon rainforest, automated mapping is …
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Retrieval of Simultaneous Water-Level Changes in Small Lakes With InSAR
Abstract Monitoring water level changes is necessary to manage, conserve and restore natural, and anthropogenic lake systems. However, …
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Estimation and Evaluation of High-Resolution Soil Moisture from Merged Model and Earth Observation Data in the Great Britain
Soil moisture is an important component of the Earth system and plays a key role in land-atmosphere interactions. Remote sensing of …
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Sentinel-1 Soil Moisture at 1 Km Resolution: A Validation Study
This study presents an assessment of a pre-operational soil moisture product at 1 km resolution derived from satellite data acquired by …
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Predicting Forest Cover in Distinct Ecosystems: The Potential of Multi-Source Sentinel-1 and -2 Data Fusion
The fusion of microwave and optical data sets is expected to provide great potential for the derivation of forest cover around the …
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