Evidence map›Paper›PMID 37050558›Full record

ArticleSensors (Basel, Switzerland)2023

DSM Extraction Based on Gaofen-6 Satellite High-Resolution Cross-Track Images with Wide Field of View.

Suqin Yin, Ying Zhu, Hanyu Hong, Tingting Yang, Yi Chen, Yi Tian

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Suqin YinHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Ying ZhuHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Hanyu HongHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Tingting YangHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Yi ChenHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.
Yi TianHubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

Funding

National Natural Science Foundation of China Grant No. 42090011, 62171329
6 · The paper itself

Abstract

Digital Surface Model (DSM) is a three-dimensional model presenting the elevation of the Earth's surface, which can be obtained by the along-track or cross-track stereo images of optical satellites. This paper investigates the DSM extraction method using Gaofen-6 (GF-6) high-resolution (HR) cross-track images with a wide field of view (WFV). To guarantee the elevation accuracy, the relationship between the intersection angle and the overlap of the cross-track images was analyzed. Cross-track images with 20-40% overlaps could be selected to conduct DSM extraction. First, the rational function model (RFM) based on error compensation was used to realize the accurate orientation of the image. Then, the disparity map was generated based on the semi-global block matching (SGBM) algorithm with epipolar constraint. Finally, the DSM was generated by forward intersection. The GF-6 HR cross-track images with about 30% overlap located in Taian, Shandong Province, China, were used for DSM extraction. The results show that the mountainous surface elevation features were retained completely, and the details, such as houses and roads, were presented in valleys and urban areas. The root mean square error (RMSE) of the extracted DSM could reach 6.303 m, 12.879 m, 14.929 m, and 19.043 m in valley, ridge, urban, and peak areas, respectively. The results indicate that the GF-6 HR cross-track images with a certain overlap can be used to extract a DSM to enhance its application in land cover monitoring.

Indexed as

DSMGF-6 satelliteprojection trajectory methodrational function modelsemi-global block matchingwide-field high-resolution camera

Identifiers

PMID37050558
PMCPMC10099190

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