Ana de Lera Garrido, T. Gobakken, M. Hauglin, E. Næsset, O. Bollandsås
{"title":"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","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":"{\"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}","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}
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
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.
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.