首页> 外文期刊>Forests >Estimating Soil Displacement from Timber Extraction Trails in Steep Terrain: Application of an Unmanned Aircraft for 3D Modelling
【24h】

Estimating Soil Displacement from Timber Extraction Trails in Steep Terrain: Application of an Unmanned Aircraft for 3D Modelling

机译:估算陡峭地形中木材提取路径的土壤位移:无人飞机在3D建模中的应用

获取原文
           

摘要

Skid trails constructed for timber extraction in steep terrain constitute a serious environmental concern if not well planned, executed and ameliorated. Carrying out post-harvest surveys in monitoring constructed trails in such terrain is an onerous task for forest administrators, as hundreds of meters need to be surveyed per site, and the quantification of parameters and volumes is largely based on assumptions of trail symmetry and terrain uniformity. In this study, aerial imagery captured from a multi-rotor Unmanned Aerial Vehicle was used in generating a detailed post-harvest terrain model which included all skid trails. This was then compared with an Airborne Laser Scanning derived pre-harvest terrain model and the dimensions, slopes and cut-and-fill volumes associated with the skid trails were determined. The overall skid trail length was 954 m, or 381 m·ha−1 with segments varying from 40–60 m, inclinations from 3.9% to 9.6%, and cut volumes, from 1.7 to 3.7 m3 per running meter. The methods used in this work can be used in rapidly assessing the extent of disturbance and erosion risk on a wide range of sites. The multi-rotor Unmanned Aerial Vehicle (UAV) was found to be highly suited to the task, given the relatively small size of harvested stands, their shape and their location in the mountainous terrain.
机译:如果规划,执行和改善得不好,在陡峭地形上用于木材采伐的滑道会严重影响环境。对林区管理员来说,在监视此类地形中的已建小径时进行收获后调查是一项艰巨的任务,因为每个站点需要调查数百米,参数和体积的量化主要基于小径对称性和地形均匀性的假设。在这项研究中,从多旋翼无人机拍摄的航空影像用于生成详细的收获后地形模型,其中包括所有滑道。然后将其与机载激光扫描得出的收割前地形模型进行比较,并确定与滑道相关的尺寸,坡度和填挖量。整体滑道长度为954 m,即381 m·ha −1 ,路段范围为40-60 m,倾斜度从3.9%到9.6%,切割体积从1.7到3.7 m <每跑步米sup> 3 。这项工作中使用的方法可用于快速评估各种场所的干扰和侵蚀风险。由于收获的林分相对较小,林分的形状和在山区的位置,发现多旋翼无人机非常适合这项任务。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号