Multi Temporal Remote Sensing Image

Multi-temporal remote sensing image analysis focuses on extracting information from sequences of satellite images acquired over time to understand Earth's surface changes. Current research emphasizes developing deep learning models, including generative adversarial networks (GANs), transformers, and neural radiance fields (NeRFs), to address challenges like change detection, data augmentation, and high-resolution 3D reconstruction from often noisy or incomplete data. These advancements improve our ability to monitor environmental dynamics, urban development, and disaster response, offering valuable insights for various scientific disciplines and practical applications such as precision agriculture and public health.