Using satellite observations to evaluate forest recovery following a wildfire could be an innovative, cost-efficient way to ...

Mountain environments feature steep terrain, variable climates, and diverse ecosystems, making traditional data collection ...

Deep learning-based high-resolution remote sensing for farmland extraction is a crucial method for obtaining large-scale farmland information. However, variations in crop types, growth conditions, and ...

Remote sensing images semantic segmentation is typically challenging due to the complexity of land cover information. Existing convolutional neural network (CNN)-based models lack the capability to ...