Urban Building Height Extraction from Gaofen-7 Stereo Satellite Images Enhanced by Contour Matching

Author:

Cui Yunfan1ORCID,Zhao Shuangming1,Jiang Wanshou2ORCID,Yu Guorong3

Affiliation:

1. School of Remote Sensing Information Engineering, Wuhan University, Wuhan 430079, China

2. State Key Laboratory of Information Engineering in Surveying Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China

3. School of Computer Science and Technology, Wuhan University of Science and Technology, Wuhan 430065, China

Abstract

The traditional method for extracting the heights of urban buildings involves utilizing dense matching algorithms on stereo images to generate a digital surface model (DSM). However, for urban buildings, the disparity discontinuity issue that troubles the dense matching algorithm makes the elevations of high-rise buildings and the surrounding areas inaccurate. The occlusion caused by trees in greenbelts makes it difficult to accurately extract the ground elevation around the building. To tackle these problems, a method for building height extraction from Gaofen-7 (GF-7) stereo images enhanced by contour matching is presented. Firstly, a contour matching algorithm was proposed to extract accurate building roof elevation from GF-7 images. Secondly, a ground filtering algorithm was employed on the DSM to generate a digital elevation model (DEM), and ground elevation can be extracted from this DEM. The difference between the rooftop elevation and the ground elevation represents the building height. The presented method was verified in Yingde, Guangzhou, Guangdong Province, and Xi’an, Shaanxi Province. The experimental results demonstrate that our proposed method outperforms existing methods in building height extraction concerning accuracy.

Funder

High-Resolution Remote Sensing Application Demonstration System for Urban Fine Management

Publisher

MDPI AG

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