In response to the massive, dynamic, multi-dimensional, and heterogeneous high-resolution satellite remote sensing observation data, improving the comprehensive utilization capability of earth observation system by acquiring high-resolution compressed information (“sensing”), establishing multi-scale geometric analysis modeling (“knowing”), and learning and analyzing features (“using”) has become an inevitable trend in the development of remote sensing technology. This book, consisting of fifteen chapters, systematically discusses the theoretical foundation of the remote sensing brain, sensing and interpretation applications, as well as the remote sensing brain system. Chapters one to four primarily introduce the research background and significance of remote sensing technology and brain-inspired approaches, compressed sensing fundamentals, mechanisms and characteristics of remotely-sensed imaging, and advancements in deep neural networks. Chapters five to 12 mainly present specific application results of the authors’ team related to the sensing and interpretation aspects of the remote sensing brain. Chapters 13 to 14 mainly introduce the remote sensing brain system developed by the authors’ team. Chapter 15 primarily provides an outlook and summary of the major disclosed issues in the field. This book is suitable for senior undergraduate and graduate students involved in deep learning and image processing.