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Improving Geometric Performance for Imagery Captured by Non-Cartographic Optical Satellite: A Case Study of GF-1 WFV Imagery

1,2, 1,2,*, 2,3, 2,4 and 1,2
1
State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China
2
Collaborative Innovation Center of Geospatial Technology, Wuhan University, Wuhan 430079, China
3
School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China
4
China Academy of Space Technology, Beijing 100094, China
*
Author to whom correspondence should be addressed.
Remote Sens. 2018, 10(6), 971; https://doi.org/10.3390/rs10060971
Received: 14 May 2018 / Revised: 8 June 2018 / Accepted: 13 June 2018 / Published: 18 June 2018
(This article belongs to the Section Remote Sensing Image Processing)
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Abstract

Numerous countries have established their own Earth observing systems (EOSs) for global change research. Data acquisition efforts are generally only concerned with the completion of the mission regardless of the potential to expand into other areas, which reduces the application effectiveness of Earth observation data. This paper explores the cartographic possibility of images being not initially intended for surveying and mapping, and a novel method is proposed to improve the geometric performance. First, the rigorous sensor model (RSM) is recovered from the rational function model (RFM), and then the system errors of the non-cartographic satellite’s imagery are compensated by using the conventional geometric calibration method based on RSM; finally, a new and improved RFM is generated. The advantage of the method over traditional ones is that it divides the errors into static errors and non-static errors for each image during the improvement process. Experiments using images collected with the Gaofen-1 (GF-1) wide-field view (WFV) camera demonstrate that the orientation accuracy of the proposed method is within 1 pixel for both calibration and validation images, and the obvious high-order system errors are eliminated. Moreover, a block adjustment test shows that the vertical accuracy is improved from 21 m to 11 m with four ground control points (GCPs) after compensation, which can fulfill requirements for 1:100,000 stereo mapping in mountainous areas. Generally, the proposed method can effectively improve the geometric potential for images captured by non-cartographic satellite. View Full-Text
Keywords: geometric performance; non-cartographic; satellite image; rigorous sensor model (RSM); rational function model (RFM); GF-1; wide-field view (WFV) camera geometric performance; non-cartographic; satellite image; rigorous sensor model (RSM); rational function model (RFM); GF-1; wide-field view (WFV) camera
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Xu, K.; Zhang, G.; Deng, M.; Zhang, Q.; Li, D. Improving Geometric Performance for Imagery Captured by Non-Cartographic Optical Satellite: A Case Study of GF-1 WFV Imagery. Remote Sens. 2018, 10, 971.

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