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基于高分六号卫星宽幅高分辨率沿轨立体影像的 DSM 提取

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

机构信息

Hubei Key Laboratory of Optical Information and Pattern Recognition, School of Electrical and Information Engineering, Wuhan Institute of Technology, Wuhan 430205, China.

出版信息

Sensors (Basel). 2023 Mar 27;23(7):3497. doi: 10.3390/s23073497.

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.

摘要

数字表面模型 (DSM) 是一种呈现地球表面高程的三维模型,可通过光学卫星的沿轨或交轨立体影像获得。本文研究了利用高分六号 (GF-6) 高分辨率 (HR) 交轨宽视场 (WFV) 影像提取 DSM 的方法。为保证高程精度,分析了交轨影像交会角与重叠度的关系,选择 20%-40%重叠度的交轨影像进行 DSM 提取。首先,利用基于误差补偿的有理函数模型 (RFM) 实现影像的精确定向。然后,基于具有极线约束的半全局立体匹配 (SGBM) 算法生成视差图。最后,通过前方交会生成 DSM。利用中国山东泰安约 30%重叠的 GF-6 HR 交轨影像进行 DSM 提取。结果表明,提取的 DSM 完全保留了山区表面高程特征,山谷和城区的房屋和道路等细节得到了呈现。山谷、山脊、城区和山顶区域提取 DSM 的均方根误差 (RMSE) 分别可达 6.303m、12.879m、14.929m 和 19.043m。结果表明,一定重叠度的 GF-6 HR 交轨影像可用于提取 DSM,增强其在土地覆盖监测中的应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d32f/10099190/2eba357beb7d/sensors-23-03497-g001.jpg

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