首页> 外文期刊>International Journal of Wildland Fire >Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA
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Time series of high-resolution images enhances efforts to monitor post-fire condition and recovery, Waldo Canyon fire, Colorado, USA

机译:高分辨率图像的时间序列增强了监控火灾后状态和恢复的工作,沃尔多峡谷火,科罗拉多州,美国

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摘要

Interpretations of post-fire condition and rates of vegetation recovery can influence management priorities, actions and perception of latent risks from landslides and floods. In this study, we used the Waldo Canyon fire (2012, Colorado Springs, Colorado, USA) as a case study to explore how a time series (2011-2016) of high-resolution images can be used to delineate burn extent and severity, as well as quantify post-fire vegetation recovery. We applied an object-based approach to map burn severity and vegetation recovery using Worldview-2, Worldview-3 and QuickBird-2 imagery. The burned area was classified as 51% high, 20% moderate and 29% low burn-severity. Across the burn extent, the shrub cover class showed a rapid recovery, resprouting vigorously within 1 year, whereas 4 years post-fire, areas previously dominated by conifers were divided approximately equally between being classified as dominated by quaking aspen saplings with herbaceous species in the understorey or minimally recovered. Relative to using a pixel-based Normalised Difference Vegetation Index (NDVI), our object-based approach showed higher rates of revegetation. High-resolution imagery can provide an effective means to monitor post-fire site conditions and complement more prevalent efforts with moderate-and coarse-resolution sensors.
机译:解释火灾后状态和植被恢复率可以影响山体滑坡和洪水潜在风险的管理优先事项,行动和对潜在风险的看法。在这项研究中,我们使用了Waldo Canyon Fire(2012年,科罗拉多斯普林斯,科罗拉多州,美国)作为案例研究,探讨了高分辨率图像的时间序列(2011-2016)如何用于描绘燃烧程度和严重程度,以及量化火药后植被恢复。我们应用了基于对象的方法来使用WorldView-2,WorldView-3和Quickbird-2图像映射烧伤严重程度和植被恢复。烧毁的区域被归类为51%高,20%中等和29%的低燃烧严重程度。在燃烧程度上,灌木覆盖类表现出快速恢复,在1年内重新排放,而火灾后4年,以前用针叶树支配的区域在被分类为主导的中,以通过在草本植物中爆炸虚拟化或最低恢复。相对于使用基于像素的归一化差异植被指数(NDVI),我们基于对象的方法显示了更高的再培训率。高分辨率图像可以提供有效的手段,以监控火灾后现场条件,并补充更普遍的努力与中等和粗分辨率传感器。

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