Estimating tree volume based on crown mapping by UAV pictures in the Amazon Forest

H. F. Veras, E. M. D. Cunha Neto, Iací Dandara Santos Brasil, João Paulo Sardo Madi, Emmanoella Costa Guaraná Araujo, J. Camaño, E. O. Figueiredo, D. Papa, Matheus Pinheiro Ferreira, A. P. D. Corte, C. Sanquetta
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Abstract

The use of remote sensing images obtained by unmanned aerial vehicle (UAV) systems enables measuring the morphometry of the tree canopy to estimate the volume stock in the Amazon Forest. In this study, we used RGB images from a low-cost UAV to map tree species and extract volumetric stock estimates in an Amazonian Forest. Individual tree crowns (ITC) were outlined in the UAV images and identified to the species level using forest inventory data. The average diameter and crown area of the trees were measured to estimate the volume, basal area and DBH per diameter class for 260 ha of tropical forest. The RMSE volume adjustment for the separate field inventory dataset was 19.31% with an R2 of 0.967. The UAV system images has the potential to map tree species and estimate tree biometry in the Amazon Forest, providing valuable insights for forest management and conservation.
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基于无人机影像树冠测绘的亚马逊森林树木体积估算
利用无人机(UAV)系统获得的遥感图像,可以测量树冠的形态,以估计亚马逊森林的蓄积量。在这项研究中,我们使用来自低成本无人机的RGB图像来绘制亚马逊森林的树种和提取体积储量估算。在无人机图像中勾勒出单个树冠(ITC),并利用森林清查数据将其识别到物种水平。测定了260 ha热带森林树木的平均直径和树冠面积,估算了森林的体积、基面积和每直径级胸径。单独实地库存数据集的RMSE体积调整为19.31%,R2为0.967。无人机系统图像具有绘制亚马逊森林树种和估计树木生物特征的潜力,为森林管理和保护提供有价值的见解。
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0.00%
发文量
105
审稿时长
15 weeks
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