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首页> 外文期刊>Forest Ecology and Management >Estimation of shrub biomass by airborne LiDAR data in small forest stands.
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Estimation of shrub biomass by airborne LiDAR data in small forest stands.

机译:利用小型森林林分的机载LiDAR数据估算灌木生物量。

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The presence of shrub vegetation is very significant in Mediterranean ecosystems. However, the difficulty involved in shrub management and the lack of information about behavior of this vegetation means that these areas are often left out of spatial planning projects. Airborne LiDAR (Light Detection And Ranging) has been used successfully in forestry to estimate dendrometric and dasometric variables that allow to characterize forest structure. In contrast, little research has focused on shrub vegetation. The objective of this study was to estimate dry biomass of shrub vegetation in 83 stands of radius 0.5 m using variables derived from LiDAR data. Dominant species was Quercus coccifera, one of the most characteristic species of the Mediterranean forests. Density of LiDAR data in the analyzed stands varied from 2 points/m2 to 16 points/m2, being the average 8 points/m2 and the standard deviation 4.5 points/m2. Under these conditions, predictions of biomass were performed calculating the mean height, the maximum height and the percentile values 80th, 90th, and 95th derived from LiDAR in concentric areas whose radius varied from 0.50 m to 3.5 m from the center of the stand. The maximum R2 and the minimum RMSE for dry biomass estimations were obtained when the percentile 95th of LiDAR data was calculated in an area of radius 1.5 m, being 0.48 and 1.45 kg, respectively. For this radius, it was found that for the stands (n=39) where the DTM is calculated with high accuracy (RMSE lower than 0.20 m) and with a high density of LiDAR data (more than 8 points/m2) the R2 value was 0.73. These results show the possibility of estimating shrub biomass in small areas when the density of LiDAR data is high and errors associated to the DTM are low. These results would allow us to improve the knowledge about shrub behavior avoiding the cost of field measurements and clear cutting actions.Digital Object Identifier http://dx.doi.org/10.1016/j.foreco.2011.07.026
机译:灌木植被的存在在地中海生态系统中非常重要。然而,灌木管理的困难和缺乏有关该植被行为的信息意味着这些地区经常被排除在空间规划项目之外。机载LiDAR(光探测和测距)已在林业中成功使用,以估计能够表征森林结构的树状和dasometric变量。相反,很少有研究集中在灌木植被上。这项研究的目的是使用从LiDAR数据得出的变量估算半径为0.5 m的83个林分中灌木植被的干生物量。主要物种是地中海栎(Quercus coccifera),是地中海森林中最具特色的物种之一。被分析林分中LiDAR数据的密度从2点/ m 2 变化到16点/ m 2 ,平均为8点/ m 2 ,标准偏差为4.5点/ m 2 。在这些条件下,对生物量进行了预测,计算了从LiDAR在同心区域半径范围为0.50 m至3.5 m的同心区域中从LiDAR得出的平均高度,最大高度和百分值80th,90th和95th。在半径为1.5 m的半径为0.48和1.45 kg的区域中计算LiDAR数据的第95个百分位数时,获得了干生物量估计的最大 R 2 和最小RMSE。 , 分别。对于这个半径,发现对于DTM的展台( n = 39),其DTM的计算精度很高(RMSE小于0.20 m),并且LiDAR数据的密度很高(大于8)。 points / m 2 ), R 2 值为0.73。这些结果表明,当LiDAR数据的密度较高且与DTM相关的误差较小时,可以在较小的区域估算灌木生物量。这些结果将使我们能够提高有关灌木行为的知识,而无需进行现场测量和明确的切割动作。数字对象标识符http://dx.doi.org/10.1016/j.foreco.2011.07.026

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