The accuracy of Digital Elevation Models (DEMs) plays a crucial role in determining their reliability for geoscientific and engineering applications. Next-generation distributed interferometric synthetic aperture radar (SAR) constellations, such as the PIESAT-1 wheel constellation with its “one primary, three secondary” setup, provide a novel method for efficiently acquiring high-precision DEMs. However, a comprehensive and systematic performance evaluation of DEMs derived from such an innovative constellation is lacking, particularly in the context of comparative studies under complex terrain conditions. This study uses PIESAT-1 SAR imagery to generate a 10 m resolution DEM through multi-baseline interferometric processing. The ICESat-2 ATL08 dataset serves as the reference baseline, and mainstream products, including ZY-3, GLO-30, TanDEM-X DEM, and AW3D30, are incorporated for a multidimensional vertical accuracy evaluation, considering land cover, slope, aspect, and topographic profiles. The results indicate that, in three representative mountainous regions, the PIESAT-1 DEM achieves optimal overall accuracy (RMSE = 3.25 m). Furthermore, in regions with significant radar geometric distortions, such as south-facing slopes, vegetation-covered areas, and regions with noticeable anthropogenic topographic changes, the PIESAT-1 DEM demonstrates superior stability and information capture capabilities relative to conventional single- or dual-baseline SAR systems. This study validates the technological potential of the PIESAT-1 wheel constellation in enhancing DEM accuracy and terrain adaptability, and provides insights for the scientific selection of high-resolution topographic data and the design of future spaceborne interferometric missions.
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Shen Qiao
Chengzhi Sun
Xiaowei Wu
Remote Sensing
Nanjing University of Information Science and Technology
Ministry of Natural Resources
China Centre for Resources Satellite Data and Application
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Qiao et al. (Tue,) studied this question.
www.synapsesocial.com/papers/69d8967d6c1944d70ce07e98 — DOI: https://doi.org/10.3390/rs18071101