Satellite Imagery

Satellite imagery analysis leverages advanced computational techniques to extract valuable information from remotely sensed data, primarily focusing on Earth observation and monitoring. Current research emphasizes the application of deep learning, particularly convolutional neural networks (CNNs) like U-Nets and YOLO, and transformer-based architectures, for tasks such as object detection, semantic segmentation, and change detection across various spatial and temporal scales. These advancements enable improved monitoring of environmental changes (e.g., deforestation, flooding), infrastructure assessment (e.g., building damage, road networks), and resource management (e.g., agriculture, aquaculture), impacting diverse fields from environmental science to humanitarian aid.