Abstract Wildfire is a critical process shaping the structure and composition of forest landscapes of western Canada. Spatially-explicit forest disturbance history and forest structure estimated using remotely-sensed data enables the characterization of burn probability, defined as the susceptibility of landscapes to fire hazard over time. In this research, we leveraged the Landsat archive to determine the capacity of land cover, forest structure, and forest disturbance information, together with ancillary data, to estimate burn probability. We analyzed the interactions between a number of contributing factors and identified landscapes with high probability to burn across forested ecosystems of Saskatchewan, Canada. Overall, we found that forests composed of coniferous species, with shorter trees (<3 m), low canopy height variability, an open stand structure (<10% canopy cover), and low timber volumes (<50 m3/ha), had higher burn probabilities. A 2015 burn probability map indicated that forests that did burn in 2015 (determined using independently mapped wildfires) had a median predicted burn probability of 81%, while the median burn probability for unburned forest area was 19%. This paper demonstrates the potential to generate detailed and spatially-explicit burn probability maps from time series remote sensing data to inform wildland fire risk modeling, management, and mitigation.

中文翻译：

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使用遥感和辅助数据对野火燃烧概率进行空间显式预测

摘要 野火是塑造加拿大西部森林景观结构和组成的关键过程。使用遥感数据估计的空间明确的森林干扰历史和森林结构能够表征燃烧概率，定义为景观随时间推移对火灾危险的敏感性。在这项研究中，我们利用 Landsat 档案来确定土地覆盖的容量、森林结构和森林干扰信息，以及辅助数据，以估计燃烧概率。我们分析了许多促成因素之间的相互作用，并确定了加拿大萨斯喀彻温省森林生态系统中极有可能被烧毁的景观。总体而言，我们发现由针叶树种组成的森林，树木较短（<3 m），冠层高度变异性低，开放式林分结构（<10% 的树冠覆盖）和低木材体积（<50 m3/ha）具有更高的燃烧概率。2015 年的燃烧概率图表明，2015 年确实燃烧的森林（使用独立映射的野火确定）的预测燃烧概率中值为 81%，而未燃烧森林面积的燃烧概率中值为 19%。本文展示了从时间序列遥感数据生成详细且空间明确的燃烧概率图的潜力，为野地火灾风险建模、管理和缓解提供信息。而未燃烧森林面积的中位数燃烧概率为 19%。本文展示了从时间序列遥感数据生成详细且空间明确的燃烧概率图的潜力，为野地火灾风险建模、管理和缓解提供信息。而未燃烧森林面积的中位数燃烧概率为 19%。本文展示了从时间序列遥感数据生成详细且空间明确的燃烧概率图的潜力，为野地火灾风险建模、管理和缓解提供信息。