基于机载激光扫描数据的林冠高度模型的森林清查

IF 1.4 Q2 FORESTRY
Ivan Sačkov
{"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}
引用次数: 0

摘要

摘要机载激光扫描(ALS)已成为一种遥感技术,能够提供适用于推导所有类型高程模型的数据。林冠高度模型(CHM)是森林清单中最常用的模型,它表示地面以上物体(如树木)的绝对高度,单位为米。本研究的目的是使用ALS数据得出的CHM,评估覆盖17583公顷森林单位(斯洛伐克,中欧)的森林清查的准确性。这一目标还包括证明免费提供的数据和软件的适用性。具体而言,本研究使用了定期机载调查期间获得的ALS数据、QGIS软件和R环境的软件包。共使用了180个试验地块(5.6公顷)进行准确度评估。CHM预测和地面观测林分属性之间的差异在平均高度、平均直径和体积方面分别达到10.9%、23.1%和34.5%的相对均方根误差。此外,所有预测都是无偏的(p值<0.05),CHM预测与地面观测林分属性之间的关系强度相对较高(R2=0.7–0.8)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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).
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
3.20
自引率
6.20%
发文量
23
审稿时长
22 weeks
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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信