Abstract
Voids caused by shadow, layover, and decorrelation usually occur in digital elevation models (DEMs) of mountainous areas that are derived from interferometric synthetic aperture radar (InSAR) datasets. The presence of voids degrades the quality and usability of the DEMs. Thus, void removal is considered as an integral part of the DEM production using InSAR data. The fusion of multiple DEMs has been widely recognized as a promising way for the void removal. Because the vertical accuracy of multiple DEMs can be different, the selection of optimum weights becomes a key problem in the fusion and is studied in this article. As a showcase, two high-resolution InSAR DEMs near Mt. Qilian in northwest China are created and then merged. The two pairs of InSAR data were acquired by TerraSAR-X from an ascending orbit and COSMO-SkyMed from a descending orbit. A maximum likelihood fusion scheme with the weights optimally determined by the height of ambiguity and the variance of phase noise is adopted to syncretize the two DEMs in our study. The fused DEM has a fine spatial resolution of 10 m and depicts the landform of the study area well. The percentage of void cells in the fused DEM is only 0.13 %, while 6.9 and 5.7 % of the cells in the COSMO-SkyMed DEM and the TerraSAR-X DEM are originally voids. Using the ICESat/GLAS elevation data and the Chinese national DEM of scale 1:50,000 as references, we evaluate vertical accuracy levels of the fused DEM as well as the original InSAR DEMs. The results show that substantial improvements could be achieved by DEM fusion after atmospheric phase screen removal. The quality of fused DEM can even meet the high-resolution terrain information (HRTI) standard.
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Acknowledgments
The anonymous reviewers are appreciated for their helpful comments and suggestions to improve the quality of this paper. This work was financially supported by the National Key Basic Research Program of China (Grant Nos. 2013CB733205 and 2013CB733204), the National Natural Science Foundation of China (Grant Nos. 41271457, 61331016, and 41021061), the Research Fund for the Doctoral Program of Higher Education of China (Grant No. 20110141110057), and the Shanghai Academy of Spaceflight Technology Innovation Fund (Grant No. SAST201214). The authors thank the Italian Space Agency (ASI) and the Eastdawn Corp. for providing the COSMO-SkyMed data, the Astrium Services Corp. for providing the TerraSAR-X data, the National Snow and Ice Data Center (NSIDC) of USA for providing ICESat/GLAS data products, and the National Geomatics Center of China for providing the Chinese national DEM.
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Jiang, H., Zhang, L., Wang, Y. et al. Fusion of high-resolution DEMs derived from COSMO-SkyMed and TerraSAR-X InSAR datasets. J Geod 88, 587–599 (2014). https://doi.org/10.1007/s00190-014-0708-x
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DOI: https://doi.org/10.1007/s00190-014-0708-x