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作 者:杨枫[1] 邓青春[1] YANG Feng;DENG Qing-chun(School of Geographical Sciences,China West Normal University,Nanchong Sichuan 637009,China)
机构地区:[1]西华师范大学地理科学学院,四川南充637009
出 处:《西华师范大学学报(自然科学版)》2023年第3期279-289,共11页Journal of China West Normal University(Natural Sciences)
基 金:国家自然科学基金项目(41971015);西华师范大学校级科研项目(19E067)。
摘 要:通过有效点云数据构建高精度数字高程模型对浅沟形态演化过程进行量化研究,不仅保证了建模精度,还缩短了建模时间。本文基于5组元谋干热河谷浅沟点云数据,首先以序列抽稀简化的方式,对比了Random、Space以及Octree三种抽稀模式下点云构建DEM的精度,确定了最佳点云抽稀方法和参数取值;其次通过实测验证数据集和浅沟横剖面对比两种方法对DEM精度进行验证。结果表明:三种最优参数取值构建的DEM均满足精度的需要,且大大缩短了建模时间。其中(1)Random模式能便捷地保留所需点云数量,其最优抽稀率为10%;(2)Space模式能很好地保证点间距离,最优参数取值为最小间距0.005 m;(3)Octree模式在空间划分上具有很强的优势,最优抽稀参数取值为11层树深抽稀;(4)三种抽稀模式中最优选择是Space模式。研究结果可为高效、高精度地构建浅沟DEM及形态演化过程研究提供依据。To quantitatively study the morphological evolution process of shallow gully,the construction of a high-precision digital elevation model by effective point cloud data can not only ensures the modeling accuracy,but also shortens the modeling time.Based on five groups of shallow gully point cloud data of dry-hot river valleys,this paper firstly determines the optimal point cloud extraction method and parameter value by employing sequential extraction simplification to compare the accuracy of DEM constructed by point cloud under Random,Space and Octree extraction modes.Secondly,the accuracy of DEM is verified by the comparison of two methods:the actual data set and shallow gully cross section.The results show that DEM constructed by the three optimal parameter values have all met the requirements of accuracy and the modeling time has been greatly shortened.Among which,(1)Random model can conveniently retain the required number of point clouds,and its optimal extraction rate is 10%;(2)Space mode can well guarantee the distance between points,and the optimal parameter is the minimum distance of 0.005 m;(3)Octree mode has a strong advantage in spatial division,and the optimal extraction parameter is deep extraction of 11-layer tree;(4)Space mode is the best choice of the three extraction modes.The results can provide a basis for efficiently and accurately constructing shallow gully DEM and studying the morphological evolution process.
分 类 号:P217[天文地球—测绘科学与技术]
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