Z. Hui, Lei Lin, Shuanggen Jin, Yuanping Xia, Yao Yevenyo Ziggah
{"title":"A Reliable DBH Estimation Method Using Terrestrial LiDAR Points through Polar Coordinate Transformation and Progressive Outlier Removal","authors":"Z. Hui, Lei Lin, Shuanggen Jin, Yuanping Xia, Yao Yevenyo Ziggah","doi":"10.3390/f15061031","DOIUrl":null,"url":null,"abstract":"Diameter at breast height (DBH) is a crucial parameter for forest inventory. However, accurately estimating DBH remains challenging due to the noisy and incomplete cross-sectional points. To address this, this paper proposed a reliable DBH estimation method using terrestrial LiDAR points through polar coordinate transformation and progressive outlier removal. In this paper, the initial center was initially detected by rasterizing the convex hull, and then the Cartesian coordinates were transformed into polar coordinates. In the polar coordinate system, the outliers were classified as low and high outliers according to the distribution of polar radius difference. Both types of outliers were then removed using adaptive thresholds and the moving least squares algorithm. Finally, DBH was estimated by calculating the definite integral of arc length in the polar coordinate system. Twenty publicly available individual trees were adopted for the test. Experimental results indicated that the proposed method performs better than the other four classical DBH estimation methods. Furthermore, several extreme cases scanned using terrestrial LiDAR in practice, such as cross-sectional points with lots of outliers or larger data gaps, were also tested. Experimental results demonstrate that the proposed method accurately calculates DBH even in these challenging cases.","PeriodicalId":12339,"journal":{"name":"Forests","volume":null,"pages":null},"PeriodicalIF":2.4000,"publicationDate":"2024-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Forests","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.3390/f15061031","RegionNum":2,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 0
Abstract
Diameter at breast height (DBH) is a crucial parameter for forest inventory. However, accurately estimating DBH remains challenging due to the noisy and incomplete cross-sectional points. To address this, this paper proposed a reliable DBH estimation method using terrestrial LiDAR points through polar coordinate transformation and progressive outlier removal. In this paper, the initial center was initially detected by rasterizing the convex hull, and then the Cartesian coordinates were transformed into polar coordinates. In the polar coordinate system, the outliers were classified as low and high outliers according to the distribution of polar radius difference. Both types of outliers were then removed using adaptive thresholds and the moving least squares algorithm. Finally, DBH was estimated by calculating the definite integral of arc length in the polar coordinate system. Twenty publicly available individual trees were adopted for the test. Experimental results indicated that the proposed method performs better than the other four classical DBH estimation methods. Furthermore, several extreme cases scanned using terrestrial LiDAR in practice, such as cross-sectional points with lots of outliers or larger data gaps, were also tested. Experimental results demonstrate that the proposed method accurately calculates DBH even in these challenging cases.
期刊介绍:
Forests (ISSN 1999-4907) is an international and cross-disciplinary scholarly journal of forestry and forest ecology. It publishes research papers, short communications and review papers. There is no restriction on the length of the papers. Our aim is to encourage scientists to publish their experimental and theoretical research in as much detail as possible. Full experimental and/or methodical details must be provided for research articles.