Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory

Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models w...

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Main Authors: Bohlin, Jonas, Bohlin, Inka, Jonzén, Jonas, Nilsson, Mats
Format: Article
Language:English
Published: Finnish Society of Forest Science 2017-01-01
Series:Silva Fennica
Online Access:https://www.silvafennica.fi/article/2021
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spelling doaj-db81080c3bee43b783f8a07d6016f9db2020-11-25T02:06:39ZengFinnish Society of Forest ScienceSilva Fennica2242-40752017-01-0151210.14214/sf.2021Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventoryBohlin, JonasBohlin, InkaJonzén, JonasNilsson, Mats Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m à 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.https://www.silvafennica.fi/article/2021
collection DOAJ
language English
format Article
sources DOAJ
author Bohlin, Jonas
Bohlin, Inka
Jonzén, Jonas
Nilsson, Mats
spellingShingle Bohlin, Jonas
Bohlin, Inka
Jonzén, Jonas
Nilsson, Mats
Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
Silva Fennica
author_facet Bohlin, Jonas
Bohlin, Inka
Jonzén, Jonas
Nilsson, Mats
author_sort Bohlin, Jonas
title Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
title_short Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
title_full Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
title_fullStr Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
title_full_unstemmed Mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
title_sort mapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory
publisher Finnish Society of Forest Science
series Silva Fennica
issn 2242-4075
publishDate 2017-01-01
description Exploring the possibility to produce nation-wide forest attribute maps using stereophotogrammetry of aerial images, the national terrain model and data from the National Forest Inventory (NFI). The study areas are four image acquisition blocks in mid- and south Sweden. Regression models were developed and applied to 12.5 m à 12.5 m raster cells for each block and validation was done with an independent dataset of forest stands. Model performance was compared for eight different forest types separately and the accuracies between forest types clearly differs for both image- and LiDAR methods, but between methods the difference in accuracy is small at plot level. At stand level, the root mean square error in percent of the mean (RMSE%) were ranging: from 7.7% to 10.5% for mean height; from 12.0% to 17.8% for mean diameter; from 21.8% to 22.8% for stem volume; and from 17.7% to 21.1% for basal area. This study clearly shows that aerial images from the national image program together with field sample plots from the NFI can be used for large area forest attribute mapping.
url https://www.silvafennica.fi/article/2021
work_keys_str_mv AT bohlinjonas mappingforestattributesusingdatafromstereophotogrammetryofaerialimagesandfielddatafromthenationalforestinventory
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AT jonzenjonas mappingforestattributesusingdatafromstereophotogrammetryofaerialimagesandfielddatafromthenationalforestinventory
AT nilssonmats mappingforestattributesusingdatafromstereophotogrammetryofaerialimagesandfielddatafromthenationalforestinventory
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