{"title":"结合形态滤波和分布滤波对无人机-激光雷达点云密度进行滤波,建立数字地形模型","authors":"Anh Trung Tran, Hanh Tran, Tuan Manh Quach","doi":"10.46326/jmes.2022.63(5).01","DOIUrl":null,"url":null,"abstract":"Filtering the LiDAR point cloud based the Unmaned Aerial Vehilce (UAV - LiDAR) in the dense land cover areas to build a Digital Terrain Model (DTM) is a basic requirement of large-scale topographic mapping. The aim of this paper is to study the use of the Simple Morphological Filter (SMRF) with suitable parameters to separate the non-terrain points (trees, noise points, etc.) and the topographical points. The methods of this article are algorithmic programming and combining the two filtering algorithms including SMRF and distributed filtering. The various data input was studied in the Ba Be case study. These parameters include the grid width called Gcell (m), the radius of filters called nwd and the threshold of the feature elevation called Eth (m). The point cloud of the terrain obtained after applying the SMRF continues to be filtered using distributional filter with the algorithm keeping only minimum elevation in the filtering window in order to remove the locations of high density of points. Then, it will contribute to lighten the point capacity to build DTM, to accurately interpolate the contour lines and to ensure the aesthetics of large-scale topographic maps. The results of the study are the fomulas to estimate reasonable input parameters (Gcell = 3 m, nwd = 3, Eth = 0.2 m) of the two filters for the establishment of a topographic map of 1:2000 scale, 1 m level in the Ba Be national forest, Bac Kan province, Vietnam.","PeriodicalId":170167,"journal":{"name":"Journal of Mining and Earth Sciences","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Combination of morphological and distributional filtering for UAV - LiDAR point cloud density to establish the Digital Terrain Model\",\"authors\":\"Anh Trung Tran, Hanh Tran, Tuan Manh Quach\",\"doi\":\"10.46326/jmes.2022.63(5).01\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Filtering the LiDAR point cloud based the Unmaned Aerial Vehilce (UAV - LiDAR) in the dense land cover areas to build a Digital Terrain Model (DTM) is a basic requirement of large-scale topographic mapping. The aim of this paper is to study the use of the Simple Morphological Filter (SMRF) with suitable parameters to separate the non-terrain points (trees, noise points, etc.) and the topographical points. The methods of this article are algorithmic programming and combining the two filtering algorithms including SMRF and distributed filtering. The various data input was studied in the Ba Be case study. These parameters include the grid width called Gcell (m), the radius of filters called nwd and the threshold of the feature elevation called Eth (m). The point cloud of the terrain obtained after applying the SMRF continues to be filtered using distributional filter with the algorithm keeping only minimum elevation in the filtering window in order to remove the locations of high density of points. Then, it will contribute to lighten the point capacity to build DTM, to accurately interpolate the contour lines and to ensure the aesthetics of large-scale topographic maps. The results of the study are the fomulas to estimate reasonable input parameters (Gcell = 3 m, nwd = 3, Eth = 0.2 m) of the two filters for the establishment of a topographic map of 1:2000 scale, 1 m level in the Ba Be national forest, Bac Kan province, Vietnam.\",\"PeriodicalId\":170167,\"journal\":{\"name\":\"Journal of Mining and Earth Sciences\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Mining and Earth Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.46326/jmes.2022.63(5).01\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mining and Earth Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.46326/jmes.2022.63(5).01","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
在密集地物覆盖区内,利用无人机-激光雷达对激光雷达点云进行滤波,建立数字地形模型(DTM),是进行大尺度地形测绘的基本要求。本文的目的是研究使用简单形态滤波器(Simple Morphological Filter, SMRF)和合适的参数来分离非地形点(树木、噪声点等)和地形点。本文采用算法编程的方法,结合SMRF和分布式滤波两种滤波算法。在Ba Be案例研究中研究了各种数据输入。这些参数包括称为Gcell (m)的网格宽度,称为nwd的滤波器半径和称为Eth (m)的特征高程阈值。应用SMRF后得到的地形点云继续使用分布式滤波器进行滤波,算法在滤波窗口中只保持最小的高程,以去除高密度点的位置。从而减轻构建DTM的点容量,实现等高线的精确插值,保证大比例尺地形图的美观性。研究结果为建立越南北坎省巴别国家森林1 m水平1:2000比例尺地形图提供了估算两种滤波器合理输入参数(Gcell = 3 m, nwd = 3, Eth = 0.2 m)的公式。
Combination of morphological and distributional filtering for UAV - LiDAR point cloud density to establish the Digital Terrain Model
Filtering the LiDAR point cloud based the Unmaned Aerial Vehilce (UAV - LiDAR) in the dense land cover areas to build a Digital Terrain Model (DTM) is a basic requirement of large-scale topographic mapping. The aim of this paper is to study the use of the Simple Morphological Filter (SMRF) with suitable parameters to separate the non-terrain points (trees, noise points, etc.) and the topographical points. The methods of this article are algorithmic programming and combining the two filtering algorithms including SMRF and distributed filtering. The various data input was studied in the Ba Be case study. These parameters include the grid width called Gcell (m), the radius of filters called nwd and the threshold of the feature elevation called Eth (m). The point cloud of the terrain obtained after applying the SMRF continues to be filtered using distributional filter with the algorithm keeping only minimum elevation in the filtering window in order to remove the locations of high density of points. Then, it will contribute to lighten the point capacity to build DTM, to accurately interpolate the contour lines and to ensure the aesthetics of large-scale topographic maps. The results of the study are the fomulas to estimate reasonable input parameters (Gcell = 3 m, nwd = 3, Eth = 0.2 m) of the two filters for the establishment of a topographic map of 1:2000 scale, 1 m level in the Ba Be national forest, Bac Kan province, Vietnam.