Rapid Identification of Post-Earthquake Collapsed Buildings via Multi-Scale Morphological Profiles With Multi-Structuring Elements

Bin Wang,Dongmei Song,Ling Zhang,Xuan Tan

doi:10.1109/access.2020.3007255

Abstract

Rapid identification of post-earthquake collapsed buildings can be conducive to capturing an immediate disaster assessment, which can help design effective emergency response strategies. At present, earthquake disaster assessment in practice mainly relies on time-consuming artificial field investigations, which cannot adapt to the demands of a timely rescue. However, morphological methods have proved to be of great potential in describing the disaster characteristics of building as for size, shape, directionality and contrast. Conventionally, boundaries of intact building appear flat and smooth, thus it can be reasonably depicted by linear structural element, while collapsed buildings generally emerge dispersedly distributed without regular geometry which can be suitably described by disk structural element. Based on these intuitive findings, we propose an approach for extracting intact and collapsed buildings via multi-scale morphological profiles with multi-structuring elements from post-earthquake satellite imagery. This approach consists of three core components: 1) Linear and disk structuring elements are established through top-hat reconstruction for extracting the initial intact and collapsed building, respectively. 2) Purified intact and collapsed buildings can be obtained by a straightforward threshold segmentation and further post processing, such as area, normalized green plant index (NGPI) and the length-width ratio for image noise suppression. 3) Boolean set operations are adopted to distinguish the intact and collapsed buildings. Experiments demonstrate that the proposed method has achieved satisfactory results and exerted great superiority in computational efficiency.

Highlights

Earthquake is one of the most emergency situations, which causes heavy casualties and economic losses, and causes various secondary disasters [1]
2) Purified intact and collapsed buildings can be obtained by a straightforward threshold segmentation and further post processing, such as area, normalized green plant index (NGPI) and the length-width ratio for image noise suppression
This study presents a rapid extraction method for earthquake damage building based on differential morphological profiles (DMP) via multiple structuring elements

Summary

Introduction

Earthquake is one of the most emergency situations, which causes heavy casualties and economic losses, and causes various secondary disasters [1]. Damages to buildings have been considerable when earthquake events occur. If collapse occurs in a chemical factory, a mass of noxious chemical will be discharged to the environment, thereby causing serious environmental pollution. The collapse of buildings can cause a large number of solid wastes [2], [3]. It is very difficult to obtain an immediate assessment of such large-scale natural disasters only relying on artificial field investigation, since secondary disasters such as landslides, mudslides and quake lakes may serious obstruct ground transportation and disrupt communication [4], [5]. Remote sensing technology has proved to be a convenient, rapid and cost-effective way to help extraction and monitor earthquake damage information. A variety of algorithms have been used for earthquake-damaged buildings extracting at home and abroad and obtained a series

Methods

Findings

Discussion

Conclusion