Abstract

Analyses of single-post-event polarimetric synthetic aperture radar (PolSAR) data permit fast and convenient post-disaster damage assessment work. By analyzing valid features, damaged and undamaged buildings can be quickly classified. However, the presence of oriented buildings in the disaster area makes the classification work more challenging. Many previous works extract the damage information of the disaster area by considering oriented buildings and undamaged parallel buildings as survived buildings. However, after-effect debris may create structures with random orientation angles. In our study on the Tohoku earthquake/tsunami disaster event, we found that some damaged buildings with large building orientation angles (with respect to the satellite flight path) are grouped as oriented buildings (undamaged buildings). In this paper, we propose a new earthquake/tsunami damage assessment method, particularly for urban areas, that takes this complex situation into consideration. The proposed method solves the problems of both urban-area extraction and damaged-building identification. For urban-area extraction, the proposed combined thresholding and majority voting method can accurately discriminate between urban and foreshortening mountain areas. Meanwhile, for damaged-building identification, the proposed new unsupervised damage assessment method classifies the buildings in a disaster area according to four conditions, and it outperforms the techniques used in existing works. The analysis results and the comparison with the supervised support vector machine (SVM) classification technique show that our proposed method can produce more accurate results for damage assessment using single-post-event PolSAR data.

Highlights

  • As some of the most dangerous natural disasters, earthquakes and tsunamis severely damage the lives and properties of human beings

  • An unsupervised damage assessment method is proposed for urban areas with a complex damage situation, and the proposed method shows high superiority for post-disaster damage assessment using only post-event polarimetric Synthetic aperture radar (SAR) (PolSAR) data

  • The method was validated through a study on the Tohoku earthquake/tsunami event, using the low-resolution L-band Advanced Land Observing Satellite (ALOS)/PALSAR dataset

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Summary

Introduction

As some of the most dangerous natural disasters, earthquakes and tsunamis severely damage the lives and properties of human beings. The significance of the work done in [14] is the removal of all the areas other than damaged buildings and introduction of the use of the normalized difference of the dihedral component (NDDC) [15] and the HH-HV (HH presents horizontal/horizontal polarization and HV represents horizontal/vertical polarization) correlation coefficient (ρHHHV) in their damage assessment technique. Both the proposed supervised techniques showed high accuracy in building-damage mapping, but they need the true damage condition (ground-truth data) for the classifier’s training, which is not applicable for real-time/quick disaster monitoring. Rather than assuming that all the oriented buildings are undamaged buildings, we take damaged buildings with large orientation angles into account; this greatly improves the accuracy of damage assessment

Study Area and Experimental Data
Methodology
Preliminary Pixel-Based Classification
Polarization Orientation Angle Compensation
Classification Features
Preliminary Classification Result
Urban and Mountain Area Classification
Damage Information Extraction
Circular Correlation Coefficient
Analyses of the Coastal Area of Ishinomaki City
An Unsupervised Damaged-Building Extraction Algorithm
Result and Analysis
Coastal Area of Ishinomaki City
Analysis for Two Other Areas
Comparison with Supervised Damage Assessment Technique
Findings
Conclusions
Full Text
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