Sentinel 1
Sentinel-1 is a constellation of radar satellites providing valuable Earth observation data, largely unaffected by cloud cover, crucial for various applications. Current research focuses on integrating Sentinel-1 data with other sources (e.g., Sentinel-2 optical imagery) using advanced machine learning techniques, such as transformer networks and convolutional neural networks, to improve accuracy in tasks like land cover mapping, flood detection, and crop monitoring. This readily available, high-quality data, combined with sophisticated algorithms, significantly enhances the capabilities of remote sensing for diverse scientific and practical applications, including disaster response, precision agriculture, and environmental monitoring.
Papers
UrbanSARFloods: Sentinel-1 SLC-Based Benchmark Dataset for Urban and Open-Area Flood Mapping
Jie Zhao, Zhitong Xiong, Xiao Xiang Zhu
Assessment of Sentinel-2 spatial and temporal coverage based on the scene classification layer
Cristhian Sanchez, Francisco Mena, Marcela Charfuelan, Marlon Nuske, Andreas Dengel