Multi Spectral Satellite

Multispectral satellite imagery, capturing data across multiple wavelengths, is revolutionizing Earth observation by enabling detailed analysis of diverse features. Current research heavily utilizes deep learning, particularly transformer and U-Net architectures, to address tasks like biomass estimation, flood mapping, and ship detection, often incorporating self-supervised pre-training for improved performance with limited labeled data. These advancements significantly improve the accuracy and efficiency of various applications, ranging from environmental monitoring and disaster response to precision agriculture and resource management. The development of efficient, low-power onboard processing techniques further expands the capabilities and accessibility of multispectral satellite data analysis.