Large Remote Sensing Model with Artificial Intelligence for Target Information Enhancement

Remote Sensing technologies enable us to gain a more comprehensive understanding of the changing patterns of the Earth's physical, chemical, and biological systems. Especially in the current context where countries around the world are threatened by issues such as the environment, energy, and disasters, the use of remote sensing technologies can establish a data acquisition, processing, and product service system, as well as application systems tailored to different needs, to meet the normal and emergency application requirements of various industries. With the rapid development of remote sensing technologies represented by satellite remote sensing, aerial imagery, unmanned aerial vehicles, and ground observation stations, these technologies have accumulated a vast amount of data. However, it is difficult to fully extract information using traditional data processing and analysis methods. Therefore, there is a need to further explore new remote sensing technologies with high precision and high timeliness.

This research project aims to promote exchanges in frontier theoretical research, technological innovation, and applications in the field of remote sensing. The main objectives include the in-depth integration of artificial intelligence technology and remote sensing technology to address bottleneck issues related to information acquisition mechanisms, data processing methods, systems, and applications in Remote Sensing technology. By focusing on these goals, this research seeks to provide more effective information support for a deeper understanding of the Earth system, as well as for fields such as climate and environmental change, topographic mapping, resource management, and disaster response.

This Research Topic aims to collect and highlight outstanding contributions that cover advancing remote sensing technology with artificial intelligence, including (but not limited to):

- Novel Artificial Intelligence-based remote sensing system;

- Novel Artificial Intelligence-based processing framework for remote sensing;

- Artificial Intelligence-based modelling and algorithm for remote sensing;

- Novel applications of artificial Intelligence-based remote sensing;

- Artificial Intelligence theory for remote sensing;

- Artificial Intelligence-based hardware design for remote sensing.

Keywords: artificial intelligence, ai, earth observation, remote sensing, deep learning, data analysis

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.