北京测绘2025，Vol.39Issue(4)：522-527,6.DOI:10.19580/j.cnki.1007-3000.2025.04.020
森林场景下不同径向基函数插值DEM精度的分析
Analysis of DEM accuracy using different radial basis function interpolation in forest scenarios
摘要
Abstract
High-precision digital elevation model(DEM)are of great significance in areas such as forest resource surveys,terrain analysis,and environmental monitoring.However,the canopy cover in forests causes airborne light detection and ranging(LiDAR)to obtain sparse and unevenly distributed ground point cloud data,which poses challenges in DEM construction.Therefore,selecting an appropriate interpolation method is crucial for obtaining a high-precision forest DEM.This study aims to analyze the applicability and accuracy of different radial basis function(RBF)interpolation methods for constructing DEM in forest scenarios and explore the impact of canopy density on interpolation results.Four forest areas with varying canopy densities were selected as test regions,and airborne LiDAR was used to acquire ground point cloud data.In the experiment,five different radial basis function(RBF)kernels(thin plate spline(TPS),tension spline(ST),compactly supported radial spline(CRS),multiquadric(MQ),and inverse multiquadric(IMQ))were used to interpolate 90%of the ground point cloud,with the remaining 10%used as a validation set to evaluate interpolation accuracy.The results show that canopy density significantly affects DEM interpolation accuracy.As canopy density increases,the DEM interpolation error also increases.Among the five RBF kernels,the TPS and ST functions yielded the highest DEM accuracy,while the CRS function produced the lowest accuracy.Considering both accuracy and efficiency,the TPS function is the most suitable kernel for DEM interpolation in forest environments.This study provides important insights for DEM construction in forest scenes and recommends prioritizing the use of the TPS function for RBF interpolation in forest environments while paying attention to canopy density and controlling ground point density to improve DEM interpolation accuracy.关键词
径向基函数(RBF)/机载激光雷达(LiDAR)/数字高程模型(DEM)/插值Key words
radial basis function(RBF)/airborne light detection and ranging(LiDAR)/digital elevation model(DEM)/interpolation分类
天文与地球科学引用本文复制引用
张先慧,杨飞..森林场景下不同径向基函数插值DEM精度的分析[J].北京测绘,2025,39(4):522-527,6.基金项目
贵州省地质矿产勘查开发局地质科研项目(黔地矿科合[2022]21号) （黔地矿科合[2022]21号）
