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REMOTE SENSING FOR LAND & RESOURCES    2017, Vol. 29 Issue (s1) : 13-20     DOI: 10.6046/gtzyyg.2017.s1.03
Orginal Article |
The realization of intelligent optimization based on multi-source and massive domestic satellite image
ZHENG Xiongwei1, WEI Yingjuan1, LI Chunying1, LEI Bing2, GAN Yuhang2
1. China Areo Geophysical Survey and Remote Sensing Center for Land and Resources, Beijing 100083, China;
2. Satellite Surveying and Mapping Application Center, NASG, Beijing 100048, China
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Abstract  In view of the difficulty and time-consuming problem of high quality data filtering in the utilization of massive domestic satellite image data, the authors designed and realized automatic high quality data filtering. The intelligent optimization model of domestic satellite image was constructed based on ZY1-02C,GF-1, GF-2. The requirements of satellite and sensor type, space range, time, spatial resolution and spatial analysis method were abstracted into mathematical model to complete the efficient integration and management of heterogeneous metadata. The evaluation index system and evaluation model of remote sensing image were developed, and the customization requirements of users were set up. By means of adaptive preference rules and autonomous weight setting, the typical operational research methods were used to quantitatively analyze the satellite images so as to optimize the coverage of satellite images. The experimental results show that the coincidence rate of automatic selection and artificial selection is higher than 85%, and the efficiency of implementation is improved by more than 10 times, which verifies the correctness and efficiency of the automatic optimization method.
Keywords ZY1-02C      ecological environment remote sensing investigation      ecological environment index     
Issue Date: 24 November 2017
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GAO Hui
ZHANG Jinghua
ZHANG Jianlong
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GAO Hui,ZHANG Jinghua,ZHANG Jianlong. The realization of intelligent optimization based on multi-source and massive domestic satellite image[J]. REMOTE SENSING FOR LAND & RESOURCES, 2017, 29(s1): 13-20.
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https://www.gtzyyg.com/EN/10.6046/gtzyyg.2017.s1.03     OR     https://www.gtzyyg.com/EN/Y2017/V29/Is1/13
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