Many communities coexist with wildfires that lead to loss of lives, property, and ecosystem services. Remote sensing tools can aid disaster response and post-event assessment, offering fire agencies opportunities for additional surveillance with radar, an all-weather instrument that can image day or night. The Station (2009) and Bobcat (2020) Fires are the two largest fires in Los Angeles County history, each burning over 100,000 acres. These areas are imaged with NASA's Uninhabited Aerial Vehicle Synthetic Aperture Radar L-band instrument. We test whether polarimetric radar can detect fire scars, burn severity, and different fuel types through its sensitivity to different scattering mechanisms. Polarimetric SAR products are moved into geographic information system-friendly formats, and in lieu of available field measurements are analyzed alongside agency data showing fire perimeters, burn progression outlines, and soil burn severity. We find that the HV polarization returns and the primary scattering mechanism, quantified through the Cloude-Pottier decomposition, are the most sensitive parameters. Higher HV values pre-fire correspond well to areas of moderate and high soil burn severity, and the pattern of fire progression follows higher HV to some extent. Using an HV difference threshold of 1.5 dB, the Bobcat burn scar is identified at 0.70 accuracy when compared with the published fire perimeter. Alpha 1 Angle can also demonstrate sensitivity to soil burn severity pre- and post-fire, showing vegetation types with increased surface scattering post-fire, which can be used to map burn scars and track recovery by vegetation type.

中文翻译：

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基于 L 波段偏振 SAR 的野火管理火灾前和火灾后燃料可用性评估

许多社区与野火共存，导致生命、财产和生态系统服务损失。遥感工具可以帮助灾难响应和事后评估，为消防机构提供利用雷达进行额外监视的机会，雷达是一种可以白天或夜间成像的全天候仪器。车站火灾（2009 年）和山猫火灾（2020 年）是洛杉矶县历史上最大的两场火灾，每场火灾面积均超过 100,000 英亩。这些区域是用 NASA 的无人飞行器合成孔径雷达 L 波段仪器进行成像的。我们测试极化雷达是否可以通过其对不同散射机制的敏感性来检测火痕、燃烧严重程度和不同燃料类型。偏振SAR产品被转换为地理信息系统友好的格式，并代替可用的现场测量，与显示火灾周长、燃烧进展轮廓和土壤烧伤严重程度的机构数据一起进行分析。我们发现，通过 Cloude-Pottier 分解量化的高压偏振返回和主散射机制是最敏感的参数。火灾前较高的 HV 值很好地对应了中度和高度土壤烧伤严重程度的区域，并且火灾进展模式在某种程度上遵循较高的 HV。使用 1.5 dB 的高压差阈值，与公布的火周界相比，山猫烧伤疤痕的识别精度为 0.70。 Alpha 1 角度还可以展示对火前和火后土壤烧伤严重程度的敏感性，显示火后表面散射增加的植被类型，可用于绘制烧伤疤痕图并按植被类型跟踪恢复情况。