{"title":"利用激光雷达数据定位树木和估算直径的程序","authors":"I. A. Grishin, V. Terekhov","doi":"10.1109/REEPE57272.2023.10086843","DOIUrl":null,"url":null,"abstract":"Segmentation of a forest area with high accuracy is a non-trivial task. In this paper, the authors examined the procedure for determining the coordinates of the location of trees and their diameters in order to obtain an initial idea of the structure and quantitative filling of the forest area. To conduct the study, LiDAR data were collected from a mixed forest located in Russia with a high density of trees with a total area of about 1 hectare. The proposed procedure provides detection of 97.5% of trees. Several methods are used: covariance analysis and k-d-tree partitioning, hierarchical and non-hierarchical DBSCAN segmentation algorithm, HyperLS circle point approximation method, as well as other algorithms. All the data obtained is planned to be used for further segmentation of the forest area.","PeriodicalId":356187,"journal":{"name":"2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Procedure for Locating Trees and Estimating Diameters Using LiDAR Data\",\"authors\":\"I. A. Grishin, V. Terekhov\",\"doi\":\"10.1109/REEPE57272.2023.10086843\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Segmentation of a forest area with high accuracy is a non-trivial task. In this paper, the authors examined the procedure for determining the coordinates of the location of trees and their diameters in order to obtain an initial idea of the structure and quantitative filling of the forest area. To conduct the study, LiDAR data were collected from a mixed forest located in Russia with a high density of trees with a total area of about 1 hectare. The proposed procedure provides detection of 97.5% of trees. Several methods are used: covariance analysis and k-d-tree partitioning, hierarchical and non-hierarchical DBSCAN segmentation algorithm, HyperLS circle point approximation method, as well as other algorithms. All the data obtained is planned to be used for further segmentation of the forest area.\",\"PeriodicalId\":356187,\"journal\":{\"name\":\"2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"volume\":\"95 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-03-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/REEPE57272.2023.10086843\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 5th International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/REEPE57272.2023.10086843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Procedure for Locating Trees and Estimating Diameters Using LiDAR Data
Segmentation of a forest area with high accuracy is a non-trivial task. In this paper, the authors examined the procedure for determining the coordinates of the location of trees and their diameters in order to obtain an initial idea of the structure and quantitative filling of the forest area. To conduct the study, LiDAR data were collected from a mixed forest located in Russia with a high density of trees with a total area of about 1 hectare. The proposed procedure provides detection of 97.5% of trees. Several methods are used: covariance analysis and k-d-tree partitioning, hierarchical and non-hierarchical DBSCAN segmentation algorithm, HyperLS circle point approximation method, as well as other algorithms. All the data obtained is planned to be used for further segmentation of the forest area.