Abstract
Texture features are important characteristics in distinguishing collapsed buildings and intact buildings. However, texture features currently used in synthetic aperture radar (SAR) building damage assessment are extracted following the methods of optical images directly, which do not consider the statistical feature of speckles and limit the accuracy improving. Therefore, a statistical texture feature—G0-para—was proposed to reflect the homogeneity of buildings in complex urban areas after a disaster. The G0-para is arising from the G0 distribution of SAR image and used to distinguish collapse buildings and intact buildings. First, the G0-para is unified to satisfy different polarization data—single-/dual-/quad-/compact-polarization. Second, the distinguishing ability of G0-para is under comparison in single-/dual-/quad-/compact-polarization, through the receiver operating characteristic (ROC) curve and the area under the ROC curve analysis. Then, collapsed buildings with RADARSAT-2 and ALOS-1 data are evaluated, selecting the optimal combinations of each mode and comparing with the preferable existing texture features. The results show that the statistical texture parameter—G0-para—is better than the variance of gray-level histogram and the contrast of gray level co-occurrence matrix in distinguishing intact buildings and collapsed ones and G0-para can be applied to single-/dual-/quad-/compact-polarimetric SAR data. For experimental data, VV and HH in single polarization, VH/VV and HH/HV in dual polarization, and hybrid mode in compact polarization are recommended when the best quad polarization is unavailable.
Highlights
N ATURAL disasters seriously threaten people’s lives and property safety [1]
The receiver operating characteristic (ROC) curves of G0-para for single-polarization synthetic aperture radar (SAR) (HH, VV, HV), dual-polarization SAR (HH/VV, HH/HV, VH/VV), compact-polarization SAR (CP-45, Compact polarization (CP)-HYB), and PolSAR image of RADARSAT-2 and ALOS-1 are shown in Figs. 11 and 12, respectively
There are many texture features that have been used for building damage in different polarization SAR images, they do not consider the inherent statistical distribution of SAR speckles, and the capability of distinguishing collapsed and intact buildings need to be improved
Summary
N ATURAL disasters seriously threaten people’s lives and property safety [1]. Building collapse causes serious casualties, which is an important part of disaster losses. Accurate building damage assessment can provide decision support to reconstruct disaster areas [2]. Synthetic aperture radar (SAR) has widely used in building damage assessment, with its 24-h, all-weather working capability. SAR systems have multiple polarization modes, and different polarized SAR data have their own advantages. The single- and dual-polarization SAR data are abundant, while the Manuscript received July 22, 2019; revised October 24, 2019; accepted November 14, 2019. Date of publication December 10, 2019; date of current version February 12, 2020.
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