Retrieval of leaf fuel moisture contents from hyperspectral indices developed from dehydration experiments
Retrieval of leaf fuel moisture contents from hyperspectral indices developed from dehydration experiments
复制标题
DOI：
10.1080/22797254.2017.1274571
复制
发表时间：
2017-01
影响因子：
4
通讯作者：
Zhenxing Cao;Quan Wang
中科院分区：
文献类型：
--
作者：
Zhenxing Cao;Quan Wang
摘要燃料含水率（FMC）是火灾行为预测中的一个重要参数。虽然遥感是估算FMC时空变化的有效方法，但现有的光谱指数大多面向活燃料。对废燃料的估计通常用天气指数来代替。本研究设计了活凋落叶和死凋落叶的脱水实验，通过跟踪两种燃料材料随时间变化的含水量，确定不同燃料类型的最佳高光谱指数。确定的FMC包括两种燃料类型的最佳指标是dND（1900, 2095）的导数光谱归一化指数（dND）， R2为0.85，RMSE为32%。通过将dND（1900, 2095）与NDVI (（dND-NDVI)/(dND+NDVI)）归一化，可以很好地分离两种燃料类型的FMC估计。此外，还为必须考虑大气水汽吸收的实际大规模应用确定了新的指标。所有推荐的指标都需要在未来更多的植物种类中进行验证。
ABSTRACT Fuel moisture content (FMC) is a critical parameter in fire behavior prediction. Although remote sensing is an efficient way to estimate the spatial and temporal variations of FMC, most of the existing spectral indices are oriented to live fuels. Estimation of dead fuels is commonly done using weather indices instead. In this study, dehydration experiments were designed for both live and dead fallen litter leaves in order to determine the best hyperspectral indices for different fuel types by tracking the time-varying water contents of both fuel materials. The identified best index for FMC including both fuel types was a derivative spectra-based normalized index (dND) of dND(1900, 2095) with an R2 of 0.85 and an RMSE of 32%. Estimation of FMC in both fuel types were well separated by normalizing dND(1900, 2095) combined with NDVI ((dND-NDVI)/(dND+NDVI)). In addition, new indices were also identified for practical large scale applications when atmospheric water vapor absorption must be taken into account. All the recommend indices should be validated with more plant species in the future.