Automatic registration of a single SAR image and GIS building footprints in a large-scale urban area

Yao Sun,Sina Montazeri,Yuanyuan Wang,Xiao Xiang Zhu

doi:10.1016/j.isprsjprs.2020.09.016

Yao Sun, Sina Montazeri + Show 2 more

Open Access

https://doi.org/10.1016/j.isprsjprs.2020.09.016

Copy DOI

Abstract

Existing techniques of 3-D reconstruction of buildings from SAR images are mostly based on multibaseline SAR interferometry, such as PSI and SAR tomography (TomoSAR). However, these techniques require tens of images for a reliable reconstruction, which limits the application in various scenarios, such as emergency response. Therefore, alternatives that use a single SAR image and the building footprints from GIS data show their great potential in 3-D reconstruction. The combination of GIS data and SAR images requires a precise registration, which is challenging due to the unknown terrain height, and the difficulty in finding and extracting the correspondence. In this paper, we propose a framework to automatically register GIS building footprints to a SAR image by exploiting the features representing the intersection of ground and visible building facades, specifically the near-range boundaries in the building polygons, and the double bounce lines in the SAR image. Based on those features, the two data sets are registered progressively in multiple resolutions, allowing the algorithm to cope with variations in the local terrain. The proposed framework was tested in Berlin using one TerraSAR-X High Resolution SpotLight image and GIS building footprints of the area. Comparing to the ground truth, the proposed algorithm reduced the average distance error from 5.91 m before the registration to −0.08 m, and the standard deviation from 2.77 m to 1.12 m. Such accuracy, better than half of the typical urban floor height (3 m), is significant for precise building height reconstruction on a large scale. The proposed registration framework has great potential in assisting SAR image interpretation in typical urban areas and building model reconstruction from SAR images.

Highlights

The GIS data are radar coded to the SAR image coordinate system with heights from a coarse terrain model
The TomoSAR point cloud was used to calibrate the height of the digital elevation models (DEMs) with respect to our InSAR processor, as each point in the TomoSAR point cloud has direct corre spondence with the pixels coordinates in the SAR image
The detailed procedures of ground truth generation can be seen in Fig. 4: (1) we added the height coordinate to the 2-D GIS data footprint using the ground height H from the DEM; (2) the 3-D GIS data with coordinates (East, North, Height) was registered to the TomoSAR point cloud, using the transformation parameters derived from a 3-D matching of the DEM and the TomoSAR point cloud (Wang et al, 2017); (3) the shifted 3-D GIS data (East′, North′, Height′) were radar coded to the SAR image coordinate system

Summary

Introduction

The increased spatial resolution of modern SAR satellites, such as TerraSAR-X, TanDEM-X, and COSMO-SkyMed, has enabled reconstruc tion of building models from spaceborne SAR data (Franceschetti et al, 2002; Tupin and Roux, 2003; Guida et al, 2010; Brunner et al, 2010; Sportouche et al, 2011; Liu and Yamazaki, 2013; Zhu and Shahzad, 2014). In the SAR image, with the side-looking ge ometry and the X-band SAR sensor, the urban structures are clearly visible, but difficult to distinguish from each other clearly

Objectives

Methods

Results

Discussion

Conclusion