Progress and Challenges in Intelligent Remote Sensing Satellite Systems

By Bing Zhang, Yuanfeng Wu, Boya Zhao, Jocelyn Chanussot, Danfeng Hong, Jing Yao, Lianru Gao. 2022

365 citations recorded by the source corpus.

Due to advances in remote sensing satellite imaging and image processing technologies and their wide applications, intelligent remote sensing satellites are facing an opportunity for rapid development. The key technologies, standards, and laws of intelligent remote sensing satellites are also experiencing a series of new challenges. Novel concepts and key technologies in the intelligent hyperspectral remote sensing satellite system have been proposed since 2011. The aim of these intelligent remote sensing satellites is to provide real-time, accurate, and personalized remote sensing information services. This article reviews the current developments in new-generation intelligent remote sensing satellite systems, with a focus on intelligent remote sensing satellite platforms, imaging payloads, onboard processing systems, and other key technological chains. The technological breakthroughs and current defects of intelligence-oriented designs are also analyzed. Intelligent remote sensing satellites collect personalized remote sensing data and information, with real-time data features and information interaction between remote sensing satellites or between satellites and the ground. Such developments will expand the use of remote sensing applications beyond government departments and industrial users to a massive number of individual users. However, this extension faces challenges regarding privacy protection, societal values, and laws regarding the sharing and distribution of data and information.

Subfields: Artificial Intelligence, Mechanics of Materials, Media Technology

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In Media Technology

1. Pengyu Guo
2. Junhua Yan
3. Guiyi Zhu
4. Mu Ye
5. Yong Liu
6. Yin Zhang

Citations in the corpus

• Continual Barlow Twins: Continual Self-Supervised Learning for Remote Sensing Semantic Segmentation (2022, neutral): “able Earth Observation (EO) images [1].”
• FFCA-YOLO for Small Object Detection in Remote Sensing Images (2024, background): “On the other hand, with the continuous increase of camera bands and resolution, massive data are generated during on-board imaging [10].”