Research on technical system of environmental comprehensive perception

Yu Peng; Jin-zhong Zhang; Yu Wang; Zhi-qiang Li; Jin-ming Zhang

doi:10.1117/12.3010337

15 November 2023 Research on technical system of environmental comprehensive perception

Yu Peng, Jin-zhong Zhang, Yu Wang, Zhi-qiang Li, Jin-ming Zhang

Proceedings Volume 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023); 1281520 (2023) https://doi.org/10.1117/12.3010337
Event: International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 2023, Kaifeng, China

Abstract

With the rapid development and widespread application of information technology, various information resources targeting complex application scenarios have been continuously enriched. Consequently, a large number of information management systems have emerged, and the capacity and processing requirements of information have far exceeded the capabilities of traditional processing methods. This presents significant challenges for comprehensive environmental perception that encompasses multiple sources of data from geographic, surveying, meteorological, oceanic, and human-related domains, involving the entire process from data generation to knowledge acquisition. In this paper, firstly, the concept and connotation of environmental comprehensive perception are expounded. Secondly, the key technology system of environmental comprehensive perception is explored, and the key links and cutting-edge research status of multi-source data acquisition, processing, management, analysis, mining and service of environmental comprehensive perception are sorted out, and a hierarchical environmental comprehensive perception system is constructed. Finally, the development trend of environmental comprehensive perception is prospected.

(2023) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Yu Peng, Jin-zhong Zhang, Yu Wang, Zhi-qiang Li, and Jin-ming Zhang "Research on technical system of environmental comprehensive perception", Proc. SPIE 12815, International Conference on Remote Sensing, Mapping, and Geographic Systems (RSMG 2023), 1281520 (15 November 2023); https://doi.org/10.1117/12.3010337

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KEYWORDS

Data fusion

Data modeling

Environmental sensing

Machine learning

Mining

Atmospheric modeling

Data acquisition

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