Satellite Data

Satellite data analysis is rapidly advancing, driven by the need for efficient and accurate extraction of information from increasingly large datasets. Current research focuses on applying machine learning, particularly deep learning architectures like convolutional neural networks (CNNs), U-Nets, and vision transformers, to diverse tasks such as predicting weather phenomena (e.g., precipitation, solar irradiance), detecting environmental changes (e.g., wildfires, crop burning, urban sprawl), and monitoring Earth systems (e.g., tropical cyclones, Martian frost). These advancements are significantly impacting various fields, enabling improved environmental monitoring, resource management, and disaster response through more timely and accurate insights.