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Journal of the Indian Society of Remote Sensing

, Volume 46, Issue 12, pp 2081–2092 | Cite as

Evaluation of the RPC Model for Ziyuan-3 Three-line Array Imagery

  • Zhonghua Hong
  • Shengyuan Xu
  • Yun Zhang
  • Yanling Han
  • Yongjiu Feng
Research Article
  • 45 Downloads

Abstract

Ziyuan-3 (ZY-3) satellite is the first civilian stereo mapping satellite in China and was designed to achieve the 1: 50,000 scale mapping for land and ocean. Rigorous sensor model (RSM) is required to build the relationship between the three-dimensional (3D) object space and two-dimensional (2D) image space of ZY-3 satellite imagery. However, each satellite sensor has its own imaging system with different physical sensor models, which increase the difficulty of geometric integration of multi-source images with different sensor models. Therefore, it is critical to generate generic model, especially rational polynomial coefficients (RPCs) of optical imagery. Recently, relatively a few researches have been conducted on RPCs generation to ZY-3 satellite. This paper proposes an approach to evaluate the performance of RPCs generation from RSM of ZY-3 imagery. Three scenario experiments with different terrain features (such as ocean, hill, city and grassland) are designed and conducted to comprehensively evaluate the replacement accuracies of this approach and analyze the RPCs fitting error. All the experimental results demonstrate that the proposed method achieved the encouraging accuracy of better than 1.946E−04 pixel in both x-axis direction and y-axis direction, and it indicates that the RPCs are suitable for ZY-3 imagery and can be used as a replacement for the RSM of ZY-3 imagery.

Keywords

Rational polynomial coefficients (RPCs) Ziyuan-3 satellite Rigorous sensor model (RSM) 

Notes

Acknowledgements

The work described in this paper was substantially supported by the National Natural Science Foundation of China (Project No. 41871325), Shanghai Foundation for University Youth Scholars (Project No. ZZHY13033), Innovation Program of Shanghai Municipal Education Commission (Project No. 15ZZ082).

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Copyright information

© Indian Society of Remote Sensing 2018

Authors and Affiliations

  1. 1.College of Information TechnologyShanghai Ocean UniversityShanghaiPeople’s Republic of China
  2. 2.College of Marine ScienceShanghai Ocean UniversityShanghaiPeople’s Republic of China

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