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首页> 外文期刊>Ecosystems >Differing Sensitivities to Fire Disturbance Result in Large Differences Among Remotely Sensed Products of Vegetation Disturbance
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Differing Sensitivities to Fire Disturbance Result in Large Differences Among Remotely Sensed Products of Vegetation Disturbance

机译：在植被障碍的远程感测产品中导致火灾干扰的不同敏感性导致巨大差异

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Recent advances in high-performance computing (HPC) have promoted the creation of standardized remotely sensed products that map annual vegetation disturbance through two primary methods: (1) conventional approaches that integrate remote sensing-derived vegetation indices with field data and other data on disturbance events reported by public agencies on a year-to-year basis, and (2) "big'' data approaches using HPC to automate algorithms and workflows across an entire time series. Given the recent proliferation of these annual products and their potential utility for understanding vegetation dynamics, it is important for product end users (that is, practitioners and researchers in domains other than remote sensing) to understand the differences in their representations of disturbance and the conditions under which they report it. We use fire in California as a case study to compare reported disturbance across three widely used vegetation disturbance products-LANDFIRE (representing the conventional approach), Hansen Global Forest Change (GFC), and North America Forest Dynamics (NAFD), the latter two created from automated approaches. Using Google's Earth Engine, we compared their total and annual amounts of fire and non-fire disturbance for 2001-2010 and examined the products' reported disturbance across different environmental and burn conditions. We found that GFC and NAFD reported similar amounts of disturbance that were consistently much lower than LANDFIRE's reported disturbance across all years, regions, and habitats. We also found that despite the differences in amounts of reported disturbance, the products identified disturbance in similar ranges of bioclimatic conditions and habitat types, and thus, differing environmental conditions in areas reported as disturbed were not the drivers of the difference. Rather, we found that lower sensitivity to fire disturbance for GFC and NAFD, as compared to LANDFIRE, was a key driver of the overall differences in the amounts and locations of reported disturbance; both GFC and NAFD reported much lower amounts of fire disturbance than LANDFIRE across all burn conditions. Furthermore, the difference in reported disturbance between LANDFIRE and GFC/NAFD was greater for fire disturbance than for non-fire disturbance; LANDFIRE reported more than double the total amounts of fire disturbance of GFC and NAFD in the study period. Based on our results, we encourage end users to choose the appropriate disturbance product based not only on spatial extent and habitat but also on the disturbance type of interest (that is, fire and non-fire). Overall, rather than focusing on accuracy, our study quantifies the extent to which the products exhibited differences in the amounts and locations of reported disturbance to provide insight into these products' representations of disturbance and help end users evaluate and choose the most appropriate product for their needs.
机译：高性能计算（HPC）的最新进展促进了通过两种主要方法展示了将年度植被障碍造影的标准化远程感测的产品：（1）将遥感衍生植被指数与现场数据和其他干扰数据进行整合的常规方法公共机构报告的事件一年到一年到一年，（2）“大”数据方法使用HPC自动化整个时间序列的算法和工作流程。鉴于这些年度产品的最近扩散及其潜在效用了解植被动态，对产品最终用户来说很重要（即，遥感的域名的从业者和研究人员），以了解他们对干扰的陈述和报告条件的差异。我们在加利福尼亚州使用火灾案例研究比较三种广泛使用的植被扰动产品的扰动 - 兰德（代表）常规方法），汉森全球森林变革（GFC）和北美森林动态（NAFD），后者由自动化方法创建。使用谷歌的地球发动机，我们对2001 - 2010年的总量和年度火灾和非火灾干扰进行了比较，并在不同环境和烧伤条件下检测了产品报告的障碍。我们发现GFC和NAFD报告了类似的扰动量，持续低于地雷在整个年份，地区和栖息地的干扰。我们还发现，尽管报告的干扰量的差异，但产品鉴定了类似的生物恐子病症和栖息地类型的障碍，因此，由于扰乱的地区报告的区域不同的环境条件不是差异的驱动因素。相反，我们发现与Landfire相比，与Landfire相比，对GFC和NAFD的消防扰动的敏感性较低，是报告障碍的数量和地点的总体差异的关键驱动因素; GFC和NAFD都报告了比所有烧伤条件的土地损坏的较低量较低。此外，由于非火灾干扰，地雷和GFC / NAFD之间报告的扰动的差异更大; Landfire报道了GFC和NAFD在研究期间的两倍多。根据我们的结果，我们鼓励最终用户不仅根据空间范围和栖息地选择适当的干扰产品，而且还要对疾病类型的兴趣类型（即火和非火）基于。总体而不是专注于准确性，我们的研究量化了产品在多大程度上表现出报告的障碍的差异，以便为这些产品的干扰陈述提供了解，并帮助最终用户评估和选择最合适的产品需要。

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