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首页> 外文期刊>Remote Sensing of Environment: An Interdisciplinary Journal >Detecting tree mortality with Landsat-derived spectral indices: Improving ecological accuracy by examining uncertainty
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Detecting tree mortality with Landsat-derived spectral indices: Improving ecological accuracy by examining uncertainty

机译:用Landsat衍生的光谱指标检测树死亡率:通过检查不确定性提高生态学准确性

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摘要

Satellite-derived fire severity metrics are a foundational tool used to estimate fire effects at the landscape scale. Changes in surface characteristics permit reasonably accurate delineation between burned and unburned areas, but variability in severity within burned areas is much more challenging to detect. Previous studies have relied primarily on categorical data to calibrate severity indices in terms of classification accuracy, but this approach does not readily translate into an expected amount of error in terms of actual tree mortality. We addressed this issue by examining a dataset of 40,370 geolocated trees that burned in the 2013 California Rim Fire using 36 Landsat-derived burn severity indices.
机译:卫星衍生的火灾严重性指标是用于估算景观量表的火灾效应的基础工具。 表面特征的变化允许在燃烧和未燃烧区域之间合理准确描绘,但烧毁区域内严重程度的可变性更具挑战性。 以前的研究主要依赖于分类数据,以便在分类准确性方面校准严重性指数,但这种方法在实际树死亡率方面不容易转化为预期的误差。 我们通过审查2013年加利福尼亚州RIM火灾中燃烧的40,370棵Geolocated树的数据集使用36 Landsat衍生的烧伤严重程度指数来解决这一问题。

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