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.

中文翻译：

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一种用于不同极化模式下 SAR 建筑物损伤评估的新统计纹理特征

纹理特征是区分倒塌建筑和完好建筑的重要特征。然而，目前合成孔径雷达（SAR）建筑物损伤评估中使用的纹理特征是直接按照光学图像的方法提取的，没有考虑散斑的统计特征，限制了精度的提高。因此，提出了一种统计纹理特征——G0-para——来反映灾后复杂城市地区建筑物的同质性。G0-para由SAR图像的G0分布产生，用于区分倒塌建筑物和完好建筑物。首先，统一G0-para以满足不同的极化数据——单极化/双极化/四极化/紧凑极化。其次，G0-para的区分能力在单极化/双极化/四极化/紧凑极化下比较，通过受试者工作特征（ROC）曲线和ROC曲线下面积分析。然后，利用RADARSAT-2 和ALOS-1 数据对倒塌建筑物进行评估，选择每种模式的最佳组合，并与优选的现有纹理特征进行比较。结果表明，统计纹理参数G0-para优于灰度直方图的方差和灰度共生矩阵的对比度在区分完整建筑物和倒塌建筑物时，G0-para可以应用于单/dual-/quad-/compact-polarimetric SAR 数据。对于实验数据，当最佳四极极化不可用时，推荐单极化VV和HH，双极化VH/VV和HH/HV，紧凑极化混合模式。