Abstract Widely recognized as one of the worst natural disaster in Puerto Rico's history, hurricane Maria made landfall on September 20, 2017 in southeast Puerto Rico as a high-end category 4 hurricane on the Saffir-Simpson scale causing widespread destruction, fatalities and forest disturbance. This study focused on hurricane Maria's effect on Puerto Rico's forests as well as the effect of landform and forest characteristics on observed disturbance patterns. We used Google Earth Engine (GEE) to assess the severity of forest disturbance using a disturbance metric based on Landsat 8 satellite data composites with pre and post-hurricane Maria. Forest structure, tree phenology characteristics, and landforms were obtained from satellite data products, including digital elevation model and global forest canopy height. Our analyses showed that forest structure, and characteristics such as forest age and forest type affected patterns of forest disturbance. Among forest types, highest disturbance values were found in sierra palm, transitional, and tall cloud forests; seasonal evergreen forests with coconut palm; and mangrove forests. For landforms, greatest disturbance metrics was found at high elevations, steeper slopes, and windward surfaces. As expected, high levels of disturbance were also found close to the hurricane track, with disturbance less severe as hurricane Maria moved inland. Results demonstrated that forest and landform characteristics accounted for 34% of the variation in spatial forest spectral disturbance patterns. This study demonstrated an informative regional approach, combining remote sensing with statistical analyses to investigate factors that result in variability in hurricane effects on forest ecosystems.

中文翻译：

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飓风玛丽亚对波多黎各森林影响的遥感和统计分析

摘要 飓风玛丽亚被公认为波多黎各历史上最严重的自然灾害之一，于 2017 年 9 月 20 日在波多黎各东南部登陆，是萨菲尔-辛普森规模的高端 4 级飓风，造成广泛的破坏、死亡和森林干扰。 . 这项研究的重点是飓风玛丽亚对波多黎各森林的影响，以及地貌和森林特征对观测到的干扰模式的影响。我们使用 Google Earth Engine (GEE) 使用基于 Landsat 8 卫星数据与飓风前和飓风后的复合数据的干扰度量来评估森林干扰的严重程度。森林结构、树木物候特征和地貌是从卫星数据产品中获得的，包括数字高程模型和全球森林冠层高度。我们的分析表明，森林结构以及森林年龄和森林类型等特征影响了森林干扰的模式。在森林类型中，最高的干扰值出现在棕榈、过渡和高云雾林中；椰子棕榈的季节性常绿森林；和红树林。对于地形，在高海拔、陡坡和迎风面发现了最大的扰动指标。正如预期的那样，飓风轨道附近也发现了高度干扰，随着飓风玛丽亚向内陆移动，干扰不那么严重。结果表明，森林和地貌特征占空间森林光谱扰动模式变化的34%。这项研究展示了一种信息丰富的区域方法，