{"title":"基于机载激光扫描数据的林冠高度模型的森林清查","authors":"Ivan Sačkov","doi":"10.2478/forj-2022-0013","DOIUrl":null,"url":null,"abstract":"Abstract Airborne laser scanning (ALS) has emerged as a remote sensing technology capable of providing data suitable for deriving all types of elevation models. A canopy height model (CHM), which represents absolute height of objects above the ground in metres (e.g., trees), is the one most commonly used within the forest inventory. The aim of this study was to assess the accuracy of forest inventory performed for forest unit covered 17,583 ha (Slovakia, Central Europe) using the CHM derived from ALS data. This objective also included demonstrating the applicability of freely available data and software. Specifically, ALS data acquired during regular airborne survey, QGIS software, and packages for R environment were used for purpose of this study. A total of 180 testing plots (5.6 ha) were used for accuracy assessment. The differences between CHM-predicted and ground-observed forest stand attributes reached a relative root mean square error at 10.9%, 23.1%, and 34.5% for the mean height, mean diameter, and volume, respectively. Moreover, all predictions were unbiased (p-value < 0.05) and the strength of the relationships between CHM-predicted and ground-observed forest stand attributes were relative high (R2 = 0.7 – 0.8).","PeriodicalId":45042,"journal":{"name":"Central European Forestry Journal","volume":"68 1","pages":"224 - 231"},"PeriodicalIF":1.4000,"publicationDate":"2022-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Forest inventory based on canopy height model derived from airborne laser scanning data\",\"authors\":\"Ivan Sačkov\",\"doi\":\"10.2478/forj-2022-0013\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract Airborne laser scanning (ALS) has emerged as a remote sensing technology capable of providing data suitable for deriving all types of elevation models. A canopy height model (CHM), which represents absolute height of objects above the ground in metres (e.g., trees), is the one most commonly used within the forest inventory. The aim of this study was to assess the accuracy of forest inventory performed for forest unit covered 17,583 ha (Slovakia, Central Europe) using the CHM derived from ALS data. This objective also included demonstrating the applicability of freely available data and software. Specifically, ALS data acquired during regular airborne survey, QGIS software, and packages for R environment were used for purpose of this study. A total of 180 testing plots (5.6 ha) were used for accuracy assessment. The differences between CHM-predicted and ground-observed forest stand attributes reached a relative root mean square error at 10.9%, 23.1%, and 34.5% for the mean height, mean diameter, and volume, respectively. Moreover, all predictions were unbiased (p-value < 0.05) and the strength of the relationships between CHM-predicted and ground-observed forest stand attributes were relative high (R2 = 0.7 – 0.8).\",\"PeriodicalId\":45042,\"journal\":{\"name\":\"Central European Forestry Journal\",\"volume\":\"68 1\",\"pages\":\"224 - 231\"},\"PeriodicalIF\":1.4000,\"publicationDate\":\"2022-10-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Central European Forestry Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2478/forj-2022-0013\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"FORESTRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Central European Forestry Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/forj-2022-0013","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
Forest inventory based on canopy height model derived from airborne laser scanning data
Abstract Airborne laser scanning (ALS) has emerged as a remote sensing technology capable of providing data suitable for deriving all types of elevation models. A canopy height model (CHM), which represents absolute height of objects above the ground in metres (e.g., trees), is the one most commonly used within the forest inventory. The aim of this study was to assess the accuracy of forest inventory performed for forest unit covered 17,583 ha (Slovakia, Central Europe) using the CHM derived from ALS data. This objective also included demonstrating the applicability of freely available data and software. Specifically, ALS data acquired during regular airborne survey, QGIS software, and packages for R environment were used for purpose of this study. A total of 180 testing plots (5.6 ha) were used for accuracy assessment. The differences between CHM-predicted and ground-observed forest stand attributes reached a relative root mean square error at 10.9%, 23.1%, and 34.5% for the mean height, mean diameter, and volume, respectively. Moreover, all predictions were unbiased (p-value < 0.05) and the strength of the relationships between CHM-predicted and ground-observed forest stand attributes were relative high (R2 = 0.7 – 0.8).
期刊介绍:
Central European Forestry Journal (published as Lesnícky Èasopis - Forestry Journal until 2016) publishes novel science originating from research in forestry and related braches. Central European Forestry Journal is a professional peer-reviewed scientific journal published 4-time a year. The journal contains original papers and review papers of basic and applied research from all fields of forestry and related disciplines. The editorial office accepts the manuscripts within the focus of the journal exclusively in English language. The journal does not have article processing charges (APCs) nor article submission charges. Central European Forestry Journal, abbreviation: Cent. Eur. For. J., publishes original papers and review papers of basic and applied research from all fields of forestry and related scientific areas. The journal focuses on forestry issues relevant for Europe, primarily Central European regions. Original works and review papers can be submitted only in English language.