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EXTRACTION OF DIGITAL TERRAIN MODEL (DTM) OVER VEGETATED AREA IN TROPICAL RAINFOREST USING LIDAR

机译:利用激光雷达,在热带雨林中提取数字地形模型(DTM)植被区域

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This paper presents investigations on the combination effect of landcover types, ground filtering approach and interpolation methods on Digital Terrain Model (DTM) generated from airborne LiDAR over vegetated area in tropical environment. The study area is separated into three landcover types i.e. oil palm, mangrove and mixed forest. The LiDAR data is filtered based on: 1) Adaptive TIN (ATIN), 2) Progressive morphology (Morph), and 3) Elevation Threshold with Expand Window (ETEW). The DTMs are generated by interpolating the ground points using Ordinary Kriging and Inverse Distance Weighted (IDW) methods. The quality of DTMs is evaluated based on the combination of quantitative and qualitative approaches. The results show that combination of ATIN and Ordinary Kriging has produced DTMs with higher quality compared to other combination of filtering and interpolation technique. The smallest value of RMSE obtained for terrain covered by oil palm (0.21m) followed by mixed forest (0.25m) and mangrove (0.32m).
机译:本文提出了对热带环境中植物区植被区域生成的空中激光器中生成的数字地形模型(DTM)组合效应的调查。研究区分为三种Landcover类型,即油棕,红树林和混合森林。利用展开窗口(ETEW),基于以下:1)自适应锡(ATIN),2)逐步形态(变形)和3)升高阈值。通过使用普通的克里格化和逆距离加权(IDW)方法内插地点来产生DTM。基于定量和定性方法的组合来评估DTM的质量。结果表明,与其他过滤和插值技术的组合相比,ATIN和普通克里格的组合具有更高质量的DTM。由油棕(0.21米)覆盖的地形所获得的RMSE的最小值,然后是混合林(0.25米)和红树林(0.32米)。

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