ABSTRACT

Although fire management is essential to conserve ecosystems and protect communities in Australia, the best way to achieve these goals is controversial. Recent advances that use satellite imagery to map fire severity focus on canopy effects and provide limited ecological information. Fires and prescribed burns can also occur over weeks to months, limiting the relevance of a single post-fire image. We adapted the composite burn index, a field-truthing method commonly used in North America, to include parsimonious metrics that assess resprouting dynamics common among Australian eucalypts and the retention and recovery of key fauna habitat attributes. We used multitemporal satellite imagery to compile the greatest impacts within fire boundaries over several months and derive the maximum differenced normalised burn ratio (dNBR max). We used the dNBR max and a new field method, the OzCBI, to create distinct fire-severity models for three forested biogeographical regions in southwest Western Australia. Ecological outcomes were used to set thresholds between severity classes that were common to the three models. Balanced accuracies averaged above 0.7 across the models. This study demonstrates a practical method to incorporate ecological assessment into fire-severity maps. The approach informs efforts to achieve best-practice fire management that balances risk reduction and the conservation of natural environments.

摘要

尽管火灾管理对于保护澳大利亚的生态系统和社区至关重要，但实现这些目标的最佳方法仍存在争议。使用卫星图像来绘制火灾严重程度的最新进展主要集中在树冠效应上，并提供有限的生态信息。火灾和指定烧伤也可能发生数周至数月，从而限制了单个火灾后图像的相关性。我们采用了综合燃烧指数（一种北美常用的实地验证方法），以包括评估澳大利亚桉树常见的再发芽动态以及关键动物栖息地属性的保留和恢复的简约指标。我们使用多时相卫星图像来汇总几个月内火灾边界内的最大影响，并得出最大差异归一化燃烧率 (dNBR max)。我们使用 dNBR max 和新的现场方法 OzCBI 为西澳大利亚西南部的三个森林生物地理区域创建了不同的火灾严重程度模型。生态结果用于设定三个模型共有的严重程度类别之间的阈值。各个模型的平衡准确度平均高于 0.7。这项研究展示了一种将生态评估纳入火灾严重程度地图的实用方法。该方法为实现最佳火灾管理实践提供了信息，以平衡降低风险和保护自然环境。各个模型的平衡准确度平均高于 0.7。这项研究展示了一种将生态评估纳入火灾严重程度地图的实用方法。该方法为实现最佳火灾管理实践提供了信息，以平衡降低风险和保护自然环境。各个模型的平衡准确度平均高于 0.7。这项研究展示了一种将生态评估纳入火灾严重程度地图的实用方法。该方法为实现最佳火灾管理实践提供了信息，以平衡降低风险和保护自然环境。