Abstract
Abstract. Due to the systematic error, especially the horizontal deviation that exists in the multi-source, multi-temporal DEMs (Digital Elevation Models), a method for high precision coregistration is needed. This paper presents a new fast DEM coregistration method based on a given SAR (Synthetic Aperture Radar) imaging geometry to overcome the divergence and time-consuming problem of the conventional DEM coregistration method. First, intensity images are simulated for two DEMs under the given SAR imaging geometry. 2D (Two-dimensional) offsets are estimated in the frequency domain using the intensity cross-correlation operation in the FFT (Fast Fourier Transform) tool, which can greatly accelerate the calculation process. Next, the transformation function between two DEMs is achieved via the robust least-square fitting of 2D polynomial operation. Accordingly, two DEMs can be precisely coregistered. Last, two DEMs, i.e., one high-resolution LiDAR (Light Detection and Ranging) DEM and one low-resolution SRTM (Shutter Radar Topography Mission) DEM, covering the Yangjiao landslide region of Chongqing are taken as an example to test the new method. The results indicate that, in most cases, this new method can achieve not only a result as much as 80 times faster than the minimum elevation difference (Least Z-difference, LZD) DEM registration method, but also more accurate and more reliable results.
Highlights
Due to the globe coverage from various large-scale missions, such as Shutter Radar Topography Mission (SRTM)and the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Model (GDEM), and feasible access to technology, such as airborne light detection and ranging (LiDAR) and unmanned aerial vehicle (UAV) technology, recently, the DEM has been widely applied in many aspects of earth surface research, such as cartography, climate modelling, geophysics, geomorphology, geology and soil science
The SRTM DEM elevation is converted to WGS-84 geodetic height. (ii) Basically, regarding two different resolution DEMs comparison, two ways can be usually adopted to unify the DEM resolution
As the accuracy of image coregistration is highly correlated to pixel size, in this test, SRTM DEM is oversampled to the same resolution as that of the LiDAR DEM with the bicubic spline method to hold the high resolution of LiDAR DEM. (iii) The two DEMs are simulated as intensity images based on a given SAR imaging geometry, as shown in Figure 6. (iv) The SRTM DEM is coregistered to the LiDAR DEM
Summary
Due to the globe coverage from various large-scale missions, such as Shutter Radar Topography Mission (SRTM)and the Advanced Spaceborne Thermal Emission and Reflection (ASTER) Global Digital Elevation Model (GDEM), and feasible access to technology, such as airborne light detection and ranging (LiDAR) and unmanned aerial vehicle (UAV) technology, recently, the DEM has been widely applied in many aspects of earth surface research, such as cartography, climate modelling, geophysics, geomorphology, geology and soil science. The ICP and LS3D algorithms are proposed for use on 3D terrain data with irregular distribution, such as 3D laser point cloud data; the LZD algorithm (which is the most commonly used DEM coregistration) is proposed for use on regular grid data, such as SRTM DEM data, because it provides an overall optimal performance (Yang 2012). These methods may lead to convergence errors, or even divergence, for the sake of local optimization, which in theory mainly depends on the choice of the initial value (Gruen et al 2004). 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 with the performance of the LZD algorithm
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