High-Precision Digital Surface Model Extraction from Satellite Stereo Images Fused with ICESat-2 Data

Jiang Ye,Jiawei Zhang,Yixin Deng,Yuxuan Qiang,Xinguo Liu,Rui Zhang

doi:10.3390/rs14010142

Abstract

The lack of ground control points (GCPs) affects the elevation accuracy of digital surface models (DSMs) generated by optical satellite stereo images and limits the application of high-resolution DSMs. It is a feasible idea to use ICESat-2 (Ice, Cloud, and land Elevation Satellite-2) laser altimetry data to improve the elevation accuracy of optical stereo images, but it is necessary to accurately match the two types of data. This paper proposes a DSM registration strategy based on terrain similarity (BOTS), which integrates ICESat-2 laser altimetry data without GCPs and improves the DSM elevation accuracy generation from optical satellite stereo pairs. Under different terrain conditions, Worldview-2, SV-1, GF-7, and ZY-3 stereo pairs were used to verify the effectiveness of this method. The experimental results show that the BOTS method proposed in this paper is more robust when there are a large number of abnormal points in the ICESat-2 data or there is a large elevation gap between DSMs. After fusion of ICESat-2 data, the DSM elevation accuracy extracted from the satellite stereo pair is improved by 73~92%, and the root mean square error (RMSE) of Worldview-2 DSM reaches 0.71 m.

Highlights

The horizontal positioning accuracy of advanced topographic laser altimeter system (ATLAS) is better than 6.5 m, and the elevation accuracy is 0.2 m in plain areas and 2.0 m in mountainous areas, which is better than the accuracy is 0.2 m in plain areas and 2.0 m in mountainous areas, which is better than the vertical accuracy of satellite stereo pair
For the two ZY3_DSM data sets, the difference between the translational amount of the digital surface models (DSMs) center in the east and north directions was greater than 1 m, which was still less than the spatial resolution of the DSM (2.5 m)
This paper proposes an algorithm for accurate registration of satellite stereo image extraction DSMs and ICESat-2 laser altimetry data based on terrain similarity (BOTS)

Summary

Introduction

Regional network adjustment technology can improve image positioning accuracy [10]. The former needs to analyze the system error characteristics of imaging sensors and star sensors to ensure the consistency of the positioning accuracy of remote sensing images on a global scale. The latter needs to use the ground-measured control points or other methods with higher precision to correct the residual error in the image geometric model [11,12]

Methods

Results

Discussion

Conclusion