Multi-Scene Building Height Estimation Method Based on Shadow in High Resolution Imagery

Yakun Xie,Jun Zhu,Yangge Liu,Sifan Xiong,Dejun Feng

doi:10.3390/rs13152862

Yakun Xie, Jun Zhu + Show 3 more

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https://doi.org/10.3390/rs13152862

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Abstract

Accurately building height estimation from remote sensing imagery is an important and challenging task. However, the existing shadow-based building height estimation methods have large errors due to the complex environment in remote sensing imagery. In this paper, we propose a multi-scene building height estimation method based on shadow in high resolution imagery. First, the shadow of building is classified and described by analyzing the features of building shadow in remote sensing imagery. Second, a variety of shadow-based building height estimation models is established in different scenes. In addition, a method of shadow regularization extraction is proposed, which can solve the problem of mutual adhesion shadows in dense building areas effectively. Finally, we propose a method for shadow length calculation combines with the fish net and the pauta criterion, which means that the large error caused by the complex shape of building shadow can be avoided. Multi-scene areas are selected for experimental analysis to prove the validity of our method. The experiment results show that the accuracy rate is as high as 96% within 2 m of absolute error of our method. In addition, we compared our proposed approach with the existing methods, and the results show that the absolute error of our method are reduced by 1.24 m–3.76 m, which can achieve high-precision estimation of building height.

Highlights

IntroductionPublisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations
In order to verify the feasibility of our proposed approach, we judged the effectiveness of the building height estimation method in different scenarios
We completed the classification and semantic description of building shadows in different scenes, which provides a basis for using shadows to extract building height

Summary

Introduction

Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Building height information is an important part of urban basic geographic information, which plays an important role in many urban applications, such as urban planning, building floor area ratio calculation, smart city construction [1,2,3,4,5]. Automatic building height estimation from high-resolution images has always been one of the fundamental tasks in the field of remote sensing research. The existing building height estimation methods based on remote sensing images are mainly divided into two categories. The first is based on light detection and ranging (lidar) [6,7,8], interferometric synthetic aperture radar (InSAR) [9,10,11], and stereo pair [12,13,14]

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