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首页> 外文期刊>Sustainability, Agri, Food and Environmental Research >Estimation of aerial biomass using discrete-wave LiDAR data in combination with different vegetation indices in plantations of Pinus radiata (D. DON), Región del Maule, Chile.
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Estimation of aerial biomass using discrete-wave LiDAR data in combination with different vegetation indices in plantations of Pinus radiata (D. DON), Región del Maule, Chile.

机译:利用离散波LiDAR数据结合不同植被指数估算智利松树雷松松人工林中的空中生物量。

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摘要

The aerial biomass of Pinus radiata plantations in the Región del Maule, Chile, was estimated from linear models using databases of LiDAR and multispectral LANDSAT ETM+. Six descriptive height variables were obtained from the LiDAR point cloud; the 25%, 50%, 75%, 95% and 100% percentiles and the mean height. Two variables associated with the density of points were also obtained, which relate the returns between fixed weighted intervals calculated as a function of the observed biomass. For multispectral variables we used NDVI, corrected NVDI (NDVIc) and the “Tasseled Cap”components brilliance, greenness and humidity. The results showed coefficients of determination (R2) between 0.801 and 0.814, with errors between 36.07 and 36.11 ton ha-1 for the models generated using height percentiles, and R2 from 0.807 to 0.823 with errors between 36.06 and 36.84 ton ha-1 for transformed LiDAR data. Finally, the stepwise model using all available variables had R2 of 0.821-0.835 with errors of 34.28 - 36.31ton ha-1.Key words:ALS, forest above ground biomass, point cloud density, LiDAR, NDVIc.
机译:使用LiDAR和多光谱LANDSAT ETM +数据库,通过线性模型估算了智利Regióndel Maule辐射松人工林的空中生物量。从LiDAR点云获得了六个描述性的高度变量; 25%,50%,75%,95%和100%百分位数以及平均身高。还获得了与点密度相关的两个变量,它们与固定加权区间之间的收益相关,该固定收益区间是根据观察到的生物量计算得出的。对于多光谱变量,我们使用了NDVI,校正后的NVDI(NDVIc)和“流苏帽”组件的亮度,绿色度和湿度。结果显示,使用高度百分位数生成的模型的确定系数(R2)在0.801至0.814之间,误差在36.07至36.11 ton ha-1之间,而变换后的模型,其R2从0.807至0.823在36.06至36.84 ton ha-1之间LiDAR数据。最后,使用所有可用变量的逐步模型的R2为0.821-0.835,误差为34.28-36.31ton ha-1。关键词:ALS,地上生物量森林,点云密度,LiDAR,NDVIc。

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