Satellite Image
Satellite image analysis is a rapidly evolving field focused on extracting meaningful information from Earth observation data for various applications. Current research emphasizes the use of deep learning, particularly convolutional neural networks (CNNs) and vision transformers (ViTs), for tasks such as object detection, segmentation, and classification, often incorporating techniques like attention mechanisms and transfer learning to improve efficiency and accuracy. These advancements are significantly impacting fields like environmental monitoring, urban planning, disaster response, and precision agriculture by enabling automated and large-scale analysis of geospatial data.
Papers
DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou, Chenlin Meng, Robin Rombach, Marshall Burke, David Lobell, Stefano Ermon
Active Wildfires Detection and Dynamic Escape Routes Planning for Humans through Information Fusion between Drones and Satellites
Chang Liu, Tamas Sziranyi