Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland

The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We...

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Published in:Silva Fennica
Main Authors: Kotivuori, Eetu, Korhonen, Lauri, Packalen, Petteri
Format: Article in Journal/Newspaper
Language:English
Published: Finnish Society of Forest Science 2016
Subjects:
Online Access:https://doi.org/10.14214/sf.1567
https://doaj.org/article/fd3f3d300f514448b4e2ae558295b4f2
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author Kotivuori, Eetu
Korhonen, Lauri
Packalen, Petteri
author_facet Kotivuori, Eetu
Korhonen, Lauri
Packalen, Petteri
author_sort Kotivuori, Eetu
collection Directory of Open Access Journals: DOAJ Articles
container_issue 4
container_title Silva Fennica
container_volume 50
description The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We used field sample plots and airborne laser scanning data to create nationwide and regional models for each response variable. The final models had one or two ALS predictors, which were chosen based on the root mean square error (RMSE), and cross-validated. Finally, we tested how much predictions would improve if the nationwide models were calibrated with a small number of regional sample plots. Although forest structures differ among different parts of Finland, the nationwide volume and biomass models performed quite well (leave-inventory-area-out RMSE 22.3% to 33.8%, mean difference [MD] â13.8% to 18.7%) compared with regional models (leave-plot-out RMSE 20.2% to 26.8%). However, the nationwide dominant height model (RMSE 5.4% to 7.7%, MD â2.0% to 2.8%, with the exception of the Tornio region â RMSE 11.4%, MD â9.1%) performed nearly as well as the regional models (RMSE 5.2% to 6.7%). The results show that the nationwide volume and biomass models provided different means than real means at regional level, because forest structure and ALS device have a considerable effect on the predictions. Large MDs appeared especially in northern Finland. Local calibration decreased the MD and RMSE of volume and biomass models. However, the nationwide dominant height model did not benefit much from calibration.
format Article in Journal/Newspaper
genre Northern Finland
genre_facet Northern Finland
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doi:10.14214/sf.1567
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spelling ftdoajarticles:oai:doaj.org/article:fd3f3d300f514448b4e2ae558295b4f2 2025-01-16T23:52:40+00:00 Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland Kotivuori, Eetu Korhonen, Lauri Packalen, Petteri 2016-01-01T00:00:00Z https://doi.org/10.14214/sf.1567 https://doaj.org/article/fd3f3d300f514448b4e2ae558295b4f2 EN eng Finnish Society of Forest Science https://www.silvafennica.fi/article/1567 https://doaj.org/toc/2242-4075 2242-4075 doi:10.14214/sf.1567 https://doaj.org/article/fd3f3d300f514448b4e2ae558295b4f2 Silva Fennica, Vol 50, Iss 4 (2016) Forestry SD1-669.5 article 2016 ftdoajarticles https://doi.org/10.14214/sf.1567 2022-12-31T00:15:36Z The aim of this study was to examine how well stem volume, above-ground biomass and dominant height can be predicted using nationwide airborne laser scanning (ALS) based regression models. The study material consisted of nine practical ALS inventory projects taken from different parts of Finland. We used field sample plots and airborne laser scanning data to create nationwide and regional models for each response variable. The final models had one or two ALS predictors, which were chosen based on the root mean square error (RMSE), and cross-validated. Finally, we tested how much predictions would improve if the nationwide models were calibrated with a small number of regional sample plots. Although forest structures differ among different parts of Finland, the nationwide volume and biomass models performed quite well (leave-inventory-area-out RMSE 22.3% to 33.8%, mean difference [MD] â13.8% to 18.7%) compared with regional models (leave-plot-out RMSE 20.2% to 26.8%). However, the nationwide dominant height model (RMSE 5.4% to 7.7%, MD â2.0% to 2.8%, with the exception of the Tornio region â RMSE 11.4%, MD â9.1%) performed nearly as well as the regional models (RMSE 5.2% to 6.7%). The results show that the nationwide volume and biomass models provided different means than real means at regional level, because forest structure and ALS device have a considerable effect on the predictions. Large MDs appeared especially in northern Finland. Local calibration decreased the MD and RMSE of volume and biomass models. However, the nationwide dominant height model did not benefit much from calibration. Article in Journal/Newspaper Northern Finland Directory of Open Access Journals: DOAJ Articles Tornio ENVELOPE(24.147,24.147,65.848,65.848) Silva Fennica 50 4
spellingShingle Forestry
SD1-669.5
Kotivuori, Eetu
Korhonen, Lauri
Packalen, Petteri
Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title_full Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title_fullStr Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title_full_unstemmed Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title_short Nationwide airborne laser scanning based models for volume, biomass and dominant height in Finland
title_sort nationwide airborne laser scanning based models for volume, biomass and dominant height in finland
topic Forestry
SD1-669.5
topic_facet Forestry
SD1-669.5
url https://doi.org/10.14214/sf.1567
https://doaj.org/article/fd3f3d300f514448b4e2ae558295b4f2