Coffield Shane R, Graff Casey A, Chen Yang, Smyth Padhraic, Foufoula-Georgiou Efi, Randerson James T
Department of Earth System Science, Croul Hall, University of California, Irvine, CA 92697, USA.
Department of Computer Science, Donald Bren Hall, University of California, Irvine, CA 92697, USA.
Int J Wildland Fire. 2019 Sep 17;28(11):861-873. doi: 10.1071/wf19023.
Fires in boreal forests of Alaska are changing, threatening human health and ecosystems. Given expected increases in fire activity with climate warming, insight into the controls on fire size from the time of ignition is necessary. Such insight may be increasingly useful for fire management, especially in cases where many ignitions occur in a short time period. Here we investigated the controls and predictability of final fire size at the time of ignition. Using decision trees, we show that ignitions can be classified as leading to small, medium or large fires with 50.4 ± 5.2% accuracy. This was accomplished using two variables: vapour pressure deficit and the fraction of spruce cover near the ignition point. The model predicted that 40% of ignitions would lead to large fires, and those ultimately accounted for 75% of the total burned area. Other machine learning classification algorithms, including random forests and multi-layer perceptrons, were tested but did not outperform the simpler decision tree model. Applying the model to areas with intensive human management resulted in overprediction of large fires, as expected. This type of simple classification system could offer insight into optimal resource allocation, helping to maintain a historical fire regime and protect Alaskan ecosystems.
阿拉斯加北方森林火灾正在发生变化，威胁着人类健康和生态系统。鉴于随着气候变暖火灾活动预计会增加，有必要深入了解从点火之时起对火灾规模的控制因素。这种深入了解对于火灾管理可能会越来越有用，尤其是在短时间内发生多次点火的情况下。在此，我们研究了点火之时最终火灾规模的控制因素和可预测性。通过决策树，我们表明点火事件可被分类为导致小型、中型或大型火灾，准确率为50.4±5.2%。这是通过两个变量实现的：水汽压亏缺和点火点附近云杉覆盖比例。该模型预测，40%的点火事件会导致大型火灾，而这些大型火灾最终占总燃烧面积的75%。我们还测试了其他机器学习分类算法，包括随机森林和多层感知器，但它们的表现均未超过更简单的决策树模型。正如预期的那样，将该模型应用于人类管理密集的地区会导致对大型火灾的过度预测。这种简单的分类系统可以为优化资源分配提供见解，有助于维持历史火灾格局并保护阿拉斯加的生态系统。
