Acta Optica Sinica, Volume. 42, Issue 24, 2428001(2022)

Hybrid Source Photogrammetry of Optical Remote Sensing Images and Space-Borne LiDAR

Xinlei Zhang1,2,3、*, Qing Xu1,2,3, Shuai Xing1,2,3, Ming Gao1,2,3, Pengcheng Li1,2,3, Guoping Zhang1,2,3, and Jin Wang1,2,3
Author Affiliations
  • 1Institute of Geospatial Information, PLA Strategic Support Force Information Engineering University, Zhengzhou 450001, Henan , China
  • 2Collaborative Innovation Center of Geo-Information Technology for Smart Central Plains, Zhengzhou 450001, Henan , China
  • 3Key Laboratory of Spatiotemporal Perception and Intelligent Processing, Ministry of Natural Resources, Zhengzhou 450001, Henan , China
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    As the research on space-borne LiDAR in China is insufficient, we explore the hybrid source photogrammetry of optical remote sensing images and space-borne LiDAR. The surface-element trajectory matching of digital elevation model (DEM) is performed on photon data of space-borne LiDAR to establish the correspondence between the trajectory of laser altimetry points and the digital surface model (DSM) generated by remote sensing images. Then, the selected ground photons and high-resolution optical remote sensing images are combined with the joint block adjustment method. By the iterative solution method considering coordinate errors of laser altimetry points, the stereo positioning accuracy of satellite remote sensing images can be promoted. The data ATL03 of space-borne LiDAR, as well as satellite remote sensing images from Gaofen-7 (GF-7) and Tianhui-3 (TH-3), are used to verify the performance of the method. The experimental results indicate that the proposed method can effectively improve the stereo positioning accuracy of satellite remote sensing images without ground control points, and the elevation accuracy can reach 1.258 m.

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    Xinlei Zhang, Qing Xu, Shuai Xing, Ming Gao, Pengcheng Li, Guoping Zhang, Jin Wang. Hybrid Source Photogrammetry of Optical Remote Sensing Images and Space-Borne LiDAR[J]. Acta Optica Sinica, 2022, 42(24): 2428001

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Mar. 21, 2022

    Accepted: May. 5, 2022

    Published Online: Dec. 14, 2022

    The Author Email: Zhang Xinlei (zxl9602@163.com)

    DOI:10.3788/AOS202242.2428001

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