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首页> 外文期刊>IEEE Transactions on Geoscience and Remote Sensing. >Polarimetric Radar Vegetation Index for Biomass Estimation in Desert Fringe Ecosystems
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Polarimetric Radar Vegetation Index for Biomass Estimation in Desert Fringe Ecosystems

机译：极化雷达植被指数用于沙漠边缘生态系统生物量估计

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摘要

Biomass estimation of eastern Mediterranean shrublands was investigated using PALSAR full- and dual-polarization L-band and Sentinel-1 dual-polarization C-band data. First, we conducted an empirical assessment of single and multiple regressions between polarized backscattering coefficients and shrubland biomass distribution along the climatic gradient between semiarid and arid regions. We then found that the PALSAR L-band HV-polarized backscattering coefficient has higher biomass information content than Sentinel-1 C-band data. Based on a theoretical volume scattering model and a semiempirical model, we propose a new polarimetric radar vegetation index (PRVI) that utilizes the degree of polarization and the cross-polarized backscattering coefficient. The relationship between the new index and the biomass was assessed with reference to normalized difference vegetation index-based biomass estimates calculated using Landsat imagery. The PRVI was found to have higher correlation with biomass compared with other radar polarization parameters, in general, and an existing radar vegetation index (RVI), in particular. Assessment of PRVI-based biomass predictions compared with allometric data extracted from air photographs, Lidar, and field data for 67 sites across the desert fringe zone indicated moderate performance with an RMSE of 0.329 kg/m2, while an RVI-based biomass estimation had an RMSE of 0.439 kg/m2.
机译：使用PALSAR全极化和双极化L波段和Sentinel-1双极化C波段数据研究了地中海东部灌木丛的生物量估计。首先，我们对沿半干旱和干旱地区之间的气候梯度极化反向散射系数与灌木生物量分布之间的一次和多次回归进行了经验评估。然后，我们发现PALSAR L波段HV极化后向散射系数比Sentinel-1 C波段数据具有更高的生物量信息含量。基于理论体积散射模型和半经验模型，我们提出了一种新的极化雷达植被指数（PRVI），该指数利用了极化程度和交叉极化后向散射系数。参照使用Landsat影像计算得出的基于归一化差异植被指数的生物量估计值评估新指数与生物量之间的关系。与其他雷达极化参数相比，特别是与现有雷达植被指数（RVI）相比，发现PRVI与生物量的相关性更高。与从空中照片，激光雷达和沙漠边缘地区67个站点的野外数据中提取的异速测量数据相比，对基于PRVI的生物量预测进行了评估，结果表明性能中等，RMSE为0.329 kg / m n 2 n，而RVI基于生物量的估计的RMSE为0.439 kg / m n 2 n。

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