High Precision DEM Generation Algorithm Based on InSAR Multi-Look Iteration

Abstract

Interferometric Synthetic Aperture Radar (InSAR) is one of the most sufficient technologies to provide global digital elevation modeling (DEM). It unwraps the interferometric phase to provide observations for phase-to-height conversion. However, the phase gradient has great influence on the phase unwrapping quality, thereby affecting the topographic mapping accuracy. Multi-look processing can improve the reliability of phase unwrapping by reducing the noise phase gradient. Nevertheless, it reduces the spatial resolution while increasing the height phase gradient, thus lowering the reliability of height values. In this paper, we propose a multi-look iteration algorithm to suppress the noise and maintain the reliability of height values. First, we use a large number of looks (NL) to suppress the noise phase gradient and obtain a coarse DEM. Then taking this coarse DEM as a reference, we remove the topographic phase from the interferogram with a small NL, which will reduce height phase gradient and ensure the accuracy of phase unwrapping. Finally, we obtain DEM products with high precision and fine resolution. We validate the proposed algorithm using both simulated and real data, and obtain DEM products in a greatly undulated region using TanDEM-X data. Results show that the proposed method is capable of providing DEM with resolution of 4 m and accuracy of 1.73 m.

Preliminary Gaofen-3 Insar Dem Accuracy Analysis

“…The other error sources are related to the height measurement, such as phase and baseline length, which is the focus of this paper. Phase error is an important error source in InSAR processing, and the phase error of 1 radian can cause a height error of about 10 m, and the millimeter level baseline measurement error can cause the elevation error of the meter level (Gonzalez, 2010;Wu, 2017;Wang, 2014c). So, it need to be considered and eliminated in the work.…”

“…In order to analyze and verify the interferometric results under complex terrain conditions, we choose data from mountain or alpine areas, respectively, which are located in Songshan, Henan province and Tangshan, Hebei province in China. Then, we build the model for measuring the height of InSAR (Jordan, 1980;Goldstein, 1988;Massonnet, 1993), and research the orthogonal decomposition of visual- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3, 2018 ISPRS TC III Mid-term Symposium "Developments, Technologies and Applications in Remote Sensing", 7-10 May, Beijing, China vector model and three-dimensional reconstruction model (Wang, 2011a;Hua, 2014;Wang, 2003b). Interferometric error sources are analyzed (Chen, 2016a;Chen, 2016b), then we use ground control points (GCPs) for the interferometric calibration model optimization (Gonzalez, 2010;Wu, 2017) and generate related DEM products (Gao, 2017).…”

“…Then, we build the model for measuring the height of InSAR (Jordan, 1980;Goldstein, 1988;Massonnet, 1993), and research the orthogonal decomposition of visual- The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLII-3, 2018 ISPRS TC III Mid-term Symposium "Developments, Technologies and Applications in Remote Sensing", 7-10 May, Beijing, China vector model and three-dimensional reconstruction model (Wang, 2011a;Hua, 2014;Wang, 2003b). Interferometric error sources are analyzed (Chen, 2016a;Chen, 2016b), then we use ground control points (GCPs) for the interferometric calibration model optimization (Gonzalez, 2010;Wu, 2017) and generate related DEM products (Gao, 2017). Then we use data of SRTM DEM, the data of Geoscience Laser Altimeter System (GLAS) in Ice Cloud and Land Elevation Satellite (ICESat) (Zwally, 2002), as well as ground control points database of ZY-3 satellite (GCPD-ZY-3) to evaluate the accuracy of elevation (Krieger, 2012).…”

An Interferometric Processing Method to Maintain Both Accuracy and Resolution of Dem Using Gaofen-3 Sar Data

“…If we use a small ML factor, the resolution is ensured but the phase noise cannot be decreased, making it challenging to unwrap the phase correctly. Therefore, in this study, an improved method to maintain both the accuracy and resolution of DEM using InSAR data is used (Gao et al, 2017).…”

Evaluation of Airborne L- Band Multi-Baseline Pol-Insar for Dem Extraction Beneath Forest Canopy

“…Digital elevation model (DEM) extraction in areas without forest or with sparse trees is the advantage of optical stereo pairs (Alrousan et al 1997, D'Angelo et al 2008, InSAR (Zhang and Yue 2017, Geymen 2014, Gao et al 2017)and Pol-InSAR (Fu et al 2016, Fu et al 2017, Shimada, Natsuaki and Hirose 2018. While, DEM beneath forest canopy is difficult to obtain with optical stereo pairs, InSAR and Pol-InSAR technique as the surface is covered with forest and the images hardly include terrain information.…”