Journal of Geodesy and Geoinformation Science ›› 2021, Vol. 4 ›› Issue (3): 1-12.doi: 10.11947/j.JGGS.2021.0301

• Special Issue •     Next Articles

Cloud Detection and Centroid Extraction of Laser Footprint Image of GF-7 Satellite Laser Altimetry

Jiaqi YAO1,2(),Guoyuan LI1,2(),Jiyi CHEN2,Genghua HUANG3,Xiongdan YANG2,Shuaitai ZHANG2,4   

  1. 1. College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
    2. Land Satellite Remote Sensing Application Center, Ministry of Natural Resources of P.R. China, Beijing, 100048, China
    3. Key Laboratory of Space Active Opto-electronics Technology, Chinese Academy of Sciences, Shanghai, 200083, China
    4. College of Mapping and Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
  • Received:2020-09-15 Accepted:2021-01-15 Online:2021-09-20 Published:2021-10-09
  • Contact: Guoyuan LI;
  • About author:Jiaqi YAO (1995—), male, PhD, engaged in scientific research such as data processing of satellite laser altimetry. E-mail:
  • Supported by:
    National Nature Science Foundation(41971425);National Nature Science Foundation(41601505);Special Fund for High Resolution Images Surveying and Mapping Application System(42-Y30B04-9001-19/21)


The laser altimeter loaded on the GaoFen-7(GF-7) satellite is designed to record the full waveform data and footprint image, which can obtain high-precision elevation control points for stereo image. The footprint camera equipped on the GF-7 laser altimetry system can capture the energy distribution at the time of laser emission and the image of the ground object where the laser falls, which can be used to judge whether the laser is affected by the cloud. At the same time, the centroid of laser spot on the footprint image can be extracted to monitor the change of laser pointing stability. In this manuscript, a data quality analysis scheme of laser altimetry based on footprint image is presented. Firstly, the cloud detection of footprint image is realized based on deep learning. The fusion result of the model is about 5% better than that of the traditional cloud detection algorithm, which can quickly and accurately determine whether the laser spot is affected by cloud. Secondly, according to the characteristics of footprint image, a threshold constrained ellipse fitting method for extracting the centroid of laser spot is proposed to monitor the pointing stability of long-period lasers. Based on the above method, the change of laser spot centroid since GF-7 satellite was put into operation is analyzed, and the conclusions obtained have certain reference significance for the quality control of satellite laser altimetry data and the analysis of pointing angle stability.

Key words: GF-7; quality control; satellite laser altimetry; laser footprint image; cloud detection; stability analysis of laser pointing angle