基于无人机影像快速估算矿山排土场边坡土壤侵蚀速率的方法
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四川省应用基础研究计划项目“攀枝花矿区弃渣场水土流失机理及植被恢复治理模式研究”(2014JY0067);国家自然科学基金项目(41401313)


Method of Soil Erosion Rate Estimation on Mineland Dump Slope Based on Unmanned Aerial Vehicle Image
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    [目的] 探究无人机高清影像快速估算矿山排土场边坡土壤侵蚀速率的方法,为无长期地形监测地区的土壤侵蚀强度估算提供了新方法。[方法] 通过无人机和RTK-GPS分别获取研究区影像及地面控制点坐标,利用Agisoft PhotoScan Professional 1.1.2软件生成研究区空间点云,利用ArcGIS 10.3生成高精度DEM,通过目视遥感解译和现场调查,快速估算研究区土壤侵蚀速率。[结果] 本研究区排土场边坡土壤流失面积11 052.53 m2,土壤侵蚀总体积835.41 m3,土壤侵蚀速率为4 043.82 t/(km2·a)。使用普通克里金法插值生成DEM数据精度为0.26 m。[结论] 通过本研究方法计算出的排土场土壤侵蚀强度属于中度侵蚀,土壤侵蚀速率较为符合实际情况,精度也满足了本研究的需要,同时,在高密度点存在的情况下,各种插值方法生成DEM数据误差相差不大,使用普通克里金法能够使结果最优。

    Abstract:

    [Objective] Soil erosion rate of mineland dump slope was estimated using high resolution image of unmanned aerial vehicle(UAV) which provided a new method to estimate the soil erosion rate in the area without long-term topography monitoring.[Methods] The images of study area and spatial coordinates of the ground control points were acquired using UAV and RTK-GPS, respectively. The dense point clouds and high resolution digital elevation models(DEMs) were generated using Agisoft PhotoScan Professional 1.1.2 and Arc GIS 10.3, respectively. Upon which, the soil erosion rate was estimated by visual imagery interpretation and field survey.[Results] The soil erosion area and soil erosion volume in the mineland dump slope were estimated at 11 052.53 m2 and 835.41 m3, respectively. The soil erosion rate was estimated at 4 043.82 t/(km2·a). The RMSE of the DEM was 0.26 m using Ordinary Kriging method.[Conclusion] The soil erosion rate of the study area belonged to middle soil erosion, which were thought consisted with factual situations. And hence, the precision of DEM satisfied the request of the study. Although no significant differences in the DEM accuracy could be found among various interpolation methods due to the high density of cloud data, Ordinary Kriging performed best among different interpolation methods.

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杨超,苏正安,马菁,苏志满,徐霞,孔祥周.基于无人机影像快速估算矿山排土场边坡土壤侵蚀速率的方法[J].水土保持通报,2016,36(6):126-130

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  • 收稿日期:2016-02-04
  • 最后修改日期:2016-06-08
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  • 在线发布日期: 2017-01-13
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