Estimating wood volume and basal area in forest compartments by combining satellite image data with field data

Landsat TM satellite image data and field data from the National Forest Inventory (NFI) were combined using the kNN method. Wood volume and basal area estimations were done for an area in western Sweden. For each pixel in the inventory area, the distance in feature space was calculated to each...

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Autor principal: Holmgren, Johan
Formato: Second cycle, A1E
Lenguaje:sueco
Inglés
Publicado: 2012
Materias:
Acceso en línea:https://stud.epsilon.slu.se/4374/
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author Holmgren, Johan
author_browse Holmgren, Johan
author_facet Holmgren, Johan
author_sort Holmgren, Johan
collection Epsilon Archive for Student Projects
description Landsat TM satellite image data and field data from the National Forest Inventory (NFI) were combined using the kNN method. Wood volume and basal area estimations were done for an area in western Sweden. For each pixel in the inventory area, the distance in feature space was calculated to each reference (NFI) plot. The estimation for each pixel in the inventory area could be determined by choosing attribute values for the k closest neighbours in feature space and weighting them with the inverse squared distances to the estimation pixel. Two distance functions were used; Mahalanobis distance and prediction difference. The pixels were aggregated into 296 validation compartments and an average for wood volume and basal area was derived. Validation data for the compartments was acquired from a field inventory conducted by STORA Forest and Timber. The main tree species were Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula spp.). Volume and basal area could be estimated with a standard error of 21 % by combining satellite image and NFI data for compartments in the study area that had a volume between 100 and 300 m3 /ha. The standard error was high and wood volume was strongly overestimated for volumes less then 100 m3 /ha. Wood volume was underestimated by 33 % for volumes greater then 300m3 /ha. Neither correcting of reflectance for topography nor adding temperature sum improved wood volume estimation accuracy in the validation compartments. However, wood volume and basal area estimation accuracy improved if site index, age and mean tree height were included. The standard error was then 12% for compartments with a volume between 100 and 300 m3 /ha. Using Prediction difference reduced the RMSE, compared to using Mahalanobis distance, if mean tree height was included as predicting variable.
format Second cycle, A1E
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institution Swedish University of Agricultural Sciences
language Swedish
Inglés
publishDate 2012
publishDateSort 2012
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spelling RepoSLU43742012-06-26T13:36:37Z https://stud.epsilon.slu.se/4374/ Estimating wood volume and basal area in forest compartments by combining satellite image data with field data Holmgren, Johan Forestry production Surveying methods Landsat TM satellite image data and field data from the National Forest Inventory (NFI) were combined using the kNN method. Wood volume and basal area estimations were done for an area in western Sweden. For each pixel in the inventory area, the distance in feature space was calculated to each reference (NFI) plot. The estimation for each pixel in the inventory area could be determined by choosing attribute values for the k closest neighbours in feature space and weighting them with the inverse squared distances to the estimation pixel. Two distance functions were used; Mahalanobis distance and prediction difference. The pixels were aggregated into 296 validation compartments and an average for wood volume and basal area was derived. Validation data for the compartments was acquired from a field inventory conducted by STORA Forest and Timber. The main tree species were Scots pine (Pinus sylvestris), Norway spruce (Picea abies) and birch (Betula spp.). Volume and basal area could be estimated with a standard error of 21 % by combining satellite image and NFI data for compartments in the study area that had a volume between 100 and 300 m3 /ha. The standard error was high and wood volume was strongly overestimated for volumes less then 100 m3 /ha. Wood volume was underestimated by 33 % for volumes greater then 300m3 /ha. Neither correcting of reflectance for topography nor adding temperature sum improved wood volume estimation accuracy in the validation compartments. However, wood volume and basal area estimation accuracy improved if site index, age and mean tree height were included. The standard error was then 12% for compartments with a volume between 100 and 300 m3 /ha. Using Prediction difference reduced the RMSE, compared to using Mahalanobis distance, if mean tree height was included as predicting variable. 2012-06-25 Second cycle, A1E NonPeerReviewed application/pdf sv https://stud.epsilon.slu.se/4374/1/holmgren_j_120411.pdf Holmgren, Johan, 1998. Estimating wood volume and basal area in forest compartments by combining satellite image data with field data : . Second cycle, A1E. Umeå: (S) > Dept. of Forest Resource Management <https://stud.epsilon.slu.se/view/divisions/OID-260.html> urn:nbn:se:slu:epsilon-s-1277 eng
spellingShingle Forestry production
Surveying methods
Holmgren, Johan
Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title_full Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title_fullStr Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title_full_unstemmed Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title_short Estimating wood volume and basal area in forest compartments by combining satellite image data with field data
title_sort estimating wood volume and basal area in forest compartments by combining satellite image data with field data
topic Forestry production
Surveying methods
url https://stud.epsilon.slu.se/4374/
https://stud.epsilon.slu.se/4374/