Abstract Burn severity maps based on remotely sensed reflectance data provide a useful way for land managers and researchers to represent and compare spatial variation in fire effects among wildfires and prescribed fires. A need exists for an objective and rigorous selection approach that ensures the best possible spatial predictions of burn severity. The aim of this study was to present and test a methodology for selecting the optimal burn severity index from a suite of calculation and validation options that can be used to produce data for more rigorously comparing ecological effects of fire that occur in contrasting phenologies. In our study, we cross-validated remote sensing data with field data and we tested the predictive ability of 12 cross-validated index calibrations that were generated using common statistical approaches, to predict field-measured burn severity indices collected at burned and unburned areas in New Jersey Pinelands National Reserve. We demonstrate the utility of our approach, provide convincing evidence for the use of CBI as a field-based index over WCBI, and provide a cross-validated method for calculating burn severity in this vegetation type that can be used by managers and researchers.

中文翻译：

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在森林景观中选择和验证燃烧严重程度指数的改进方法

摘要 基于遥感反射数据的烧伤严重程度图为土地管理者和研究人员提供了一种有用的方法来表示和比较野火和规定火灾之间火灾影响的空间变化。需要一种客观而严格的选择方法，以确保对烧伤严重程度进行最佳可能的空间预测。本研究的目的是提出并测试一种方法，用于从一组计算和验证选项中选择最佳烧伤严重程度指数，这些计算和验证选项可用于生成数据，以便更严格地比较在对比物候中发生的火灾的生态影响。在我们的研究中，我们将遥感数据与现场数据进行了交叉验证，并测试了使用常见统计方法生成的 12 个交叉验证指数校准的预测能力，预测在新泽西松林国家保护区的燃烧和未燃烧区域收集的现场测量的烧伤严重程度指数。我们证明了我们的方法的实用性，为使用 CBI 作为 WCBI 的基于现场的指数提供了令人信服的证据，并提供了一种交叉验证的方法来计算这种植被类型的烧伤严重程度，可供管理者和研究人员使用。