Deciphering Active Wildfires in the Southwestern USA Using Topological Data Analysis
Deciphering Active Wildfires in the Southwestern USA Using Topological Data Analysis
复制标题
使用拓扑数据分析解读美国西南部活跃的野火
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
C. Vogel
中科院分区：
文献类型：
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作者：
Hannah Kim;C. Vogel
最近美国西南部的干旱导致野火风险增加，对地区和国家经济和安全构成多重威胁。野火在旱季会造成严重的空气质量问题，并会在随后的任何雨季增加泥浆和山体滑坡的数量。然而，虽然野火往往与温暖和干燥的气候相关，但这种关系并不是线性的，这意味着可能还有其他因素影响这些火灾。这项研究的目的是通过对不同的天气变量应用拓扑数据分析(TDA)来检测和分类天气数据中的任何非线性模式，例如温度、相对湿度和降水量，以及由中分辨率成像光谱仪(MODIS)有效火灾产品确定的五个最强烈和最不强烈的夏季火灾季节。除了TDA，持续性图和频率图也被用来比较美国西南部的火灾季节和地区。活跃的火灾季节更有可能在天气变量和野火之间有显著的相关性，仅凭火灾天气指数(FWI)不能准确预测加利福尼亚州和内华达州的野火，火灾天气高度依赖于地区和季节。
The recent droughts in the American Southwest have led to increasing risks of wildfires, which pose multiple threats to the regional and national economy and security. Wildfires cause serious air quality issues during dry seasons and can increase the number of mud and landslides in any subsequent rainy seasons. However, while wildfires are often correlated with warm and dry climates, this relationship is not linear, implying that there may be other factors influencing these fires. The objective of this study was to detect and classify any nonlinear patterns in weather data by applying Topological Data Analysis (TDA) to various weather variables, such as temperature, relative humidity, and precipitation, and the five most and least intense summer fire seasons as determined by the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire products. In addition to TDA, persistence diagrams and frequency plots were also used to compare fire seasons and regions in the American Southwest. Active fire seasons were more likely to have a significant correlation between the weather variables and wildfires, the Fire Weather Index (FWI) alone was not an accurate predictor for wildfires in California and Nevada, and fire weather is highly dependent upon the region and season.