1. 西北农林科技大学 资源环境学院, 陕西 杨凌,712100
2. 陕西省土地工程建设集团,陕西,西安,710000
纸质出版:2015
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魏舟, 李光录, 任磊. 微地形DEM的最佳点云密度选取[J]. 水土保持通报, 2015,35(6):155-158.
WEI Zhou, LI Guanglu, REN Lei. Ascertainment of Optimum Point Cloud Density for Microtopography DEM[J]. Bulletin of Soiland Water Conservation, 2015, 35(6): 155-158.
魏舟, 李光录, 任磊. 微地形DEM的最佳点云密度选取[J]. 水土保持通报, 2015,35(6):155-158. DOI: 10.13961/j.cnki.stbctb.2015.06.027.
WEI Zhou, LI Guanglu, REN Lei. Ascertainment of Optimum Point Cloud Density for Microtopography DEM[J]. Bulletin of Soiland Water Conservation, 2015, 35(6): 155-158. DOI: 10.13961/j.cnki.stbctb.2015.06.027.
[目的] 通过对微地形DEM的最佳点云密度进行分析研究
从中选取出最佳点云密度
以实现高效、快速获取地表微地形观测结果的目的
既可降低计算成本
又能够保证观测精度。[方法] 通过对多个扫描测次的点云数据进行深入的研究
确定出针对该数据最佳DEM水平分辨率为4 mm
对原数据进行7种等级的压缩生成对应的DEM。采用平均误差、中误差、标准差3种最常见的DEM精度指标对生成的DEM进行精度评价分析。[结果] (1)在点云压缩程度>15%时
随着点云密度的减小
平均误差基本没有变化
维持在极低的数值上;点云压缩程度<15%时
平均误差随着点云密度的减小而迅速的增大。(2)在点云压缩程度>10%时
随着点云密度的减小
标准差基本没有变化;点云压缩程度<10%时
标准差随着点云密度的减小而迅速增大。(3)在点云压缩程度>20%时
随着点云密度的减小
中误差基本没有变化
维持在极低的数值上;点云压缩程度<20%时
中误差随着点云密度的减小而迅速的增大。[结论] 对比验证分析结果表明
20%的点云压缩密度为生成微地形DEM最佳的点云密度。
[Objective] Through the analysis and research for optimal point cloud density mico DEM
this paper aimed to select the best point cloud density from it to achieve efficient
rapid access to micro-surface topography observations purpose. Upon which the computational cost was expected to be reduced under the precondition of observation accuracy.[Methods] Previous research of point cloud data proved that the optimal level of resolution about the data was 4 mm. The raw data were compressed by 7 ratings:100%
75%
50%
25%
10%
5% and 1% to generate the corresponding DEM. Three most common DEM accuracy indicators:average error
root mean square error
standard deviation were used to evaluate the accuracy of the DEM above.[Results] (1) When the point cloud compression level was set above 15%
the average error unchanged and maintained at a low value with the decrease of point cloud density
when it was compressed <15%
the average error increased rapidly with the decrease of point cloud density.(2) When the compression of the point cloud was >10%
standard deviation was in a flat status with the decrease of the point cloud density. When it was <10%
the standard deviation of point cloud density decreases rapidly with the increasing of point cloud density.(3) When point cloud was compressed over 20%
with the decrease of the point cloud density
root mean square error was in the flat segmentation; when it was <20%
the root mean square error rapidly increased with the decrease of point cloud density.[Conclusion] The comparison of different compression ratings verified that the optimal compression level to generate micro-topography DEM should be 20%.
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