Deep Learning For Environmental Remote Sensing

This Special Issue aims to gather contributions using deep learning to analyze remote sensing data for environmental applications. It will cover a range of topics, including environmental studies, agroecology, agroforestry, water management, biodiversity assessment and restoration, forest disturbances, natural resources mapping, disaster management, etc. Contributions are accepted in different areas of application, including, but not limited to, modeling, deep learning architecture search, remote sensing data engineering for DL, benchmarking, open access datasets, etc.