Accuracy assessment of the nationwide forest attribute map of Norway constructed by using airborne laser scanning data and field data from the national forest inventory

IF 1.8 3区 农林科学 Q2 FORESTRY
Ana de Lera Garrido, T. Gobakken, M. Hauglin, E. Næsset, O. Bollandsås
{"title":"Accuracy assessment of the nationwide forest attribute map of Norway constructed by using airborne laser scanning data and field data from the national forest inventory","authors":"Ana de Lera Garrido, T. Gobakken, M. Hauglin, E. Næsset, O. Bollandsås","doi":"10.1080/02827581.2023.2184488","DOIUrl":null,"url":null,"abstract":"ABSTRACT The aim of this study was to analyze the accuracy of predictions of dominant height, mean height, basal area, and volume from the nationwide forest attribute map (SR16). The analysis took advantage of field observations from 33 different forest inventory projects across Norway used for validation. Forest attributes for more than 5000 plots were predicted using non-stratified and stratified models of SR16 and the predictions were compared against corresponding ground reference values. Finally, the effect of different factors that might have influenced the prediction errors were analyzed using partial least squared regression (PLSR) to determine under which conditions the SR16 is less apt. The overall results across all plots were adequate (RMSE of 10%, MD of 2% for dominant and mean height; RMSE of 28%, MD of 4% for basal area; RMSE of 31%, MD of 5% for volume). However, when the accuracy was assessed locally for each inventory project, large differences in accuracy were observed. The MD% values for some inventory projects were substantial (>30% for basal area and volume). The results showed that stratification did not necessarily improve the results and that factors related to the forest structure had the greatest impact on the PLSR analysis.","PeriodicalId":21352,"journal":{"name":"Scandinavian Journal of Forest Research","volume":"38 1","pages":"9 - 22"},"PeriodicalIF":1.8000,"publicationDate":"2023-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scandinavian Journal of Forest Research","FirstCategoryId":"97","ListUrlMain":"https://doi.org/10.1080/02827581.2023.2184488","RegionNum":3,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"FORESTRY","Score":null,"Total":0}
引用次数: 1

Abstract

ABSTRACT The aim of this study was to analyze the accuracy of predictions of dominant height, mean height, basal area, and volume from the nationwide forest attribute map (SR16). The analysis took advantage of field observations from 33 different forest inventory projects across Norway used for validation. Forest attributes for more than 5000 plots were predicted using non-stratified and stratified models of SR16 and the predictions were compared against corresponding ground reference values. Finally, the effect of different factors that might have influenced the prediction errors were analyzed using partial least squared regression (PLSR) to determine under which conditions the SR16 is less apt. The overall results across all plots were adequate (RMSE of 10%, MD of 2% for dominant and mean height; RMSE of 28%, MD of 4% for basal area; RMSE of 31%, MD of 5% for volume). However, when the accuracy was assessed locally for each inventory project, large differences in accuracy were observed. The MD% values for some inventory projects were substantial (>30% for basal area and volume). The results showed that stratification did not necessarily improve the results and that factors related to the forest structure had the greatest impact on the PLSR analysis.
利用航空激光扫描数据和国家森林清查数据构建挪威全国森林属性图的精度评估
摘要本研究旨在分析利用全国森林属性图(SR16)预测优势高度、平均高度、基底面积和体积的准确性。该分析利用了挪威33个不同森林清查项目的实地观测资料,这些资料用于验证。利用SR16的非分层和分层模型对5000多个样地的森林属性进行了预测,并与相应的地面参考值进行了比较。最后,利用偏最小二乘回归(PLSR)分析了可能影响预测误差的不同因素的影响,以确定在哪些条件下SR16不太适合。所有样地的总体结果都是足够的(优势高度和平均高度的RMSE为10%,MD为2%;基底面积RMSE为28%,MD为4%;RMSE为31%,MD为5%。然而,当对每个库存项目的准确性进行局部评估时,观察到准确性存在很大差异。一些库存项目的MD%值相当可观(基底面积和体积的MD%)。结果表明,分层并不一定会改善结果,与森林结构相关的因素对PLSR分析的影响最大。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
CiteScore
3.00
自引率
5.60%
发文量
26
审稿时长
3.3 months
期刊介绍: The Scandinavian Journal of Forest Research is a leading international research journal with a focus on forests and forestry in boreal and temperate regions worldwide.
×
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