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Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations

Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations
Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations
Assessment of the susceptibility of forests to mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation is based upon an understanding of the characteristics that predispose the stands to attack. These assessments are typically derived from conventional forest inventory data; however, this information often represents only managed forest areas. It does not cover areas such as forest parks or conservation regions and is often not regularly updated resulting in an inability to assess forest susceptibility. To address these shortcomings, we demonstrate how a geometric optical model (GOM) can be applied to Landsat-5 Thematic Mapper (TM) imagery (30 m spatial resolution) to estimate stand-level susceptibility to mountain pine beetle attack. Spectral mixture analysis was used to determine the proportion of sunlit canopy and background, and shadow of each Landsat pixel enabling per pixel estimates of attributes required for model inversion. Stand structural attributes were then derived from inversion of the geometric optical model and used as basis for susceptibility mapping. Mean stand density estimated by the geometric optical model was 2753 (standard deviation ± 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation ± 0.11) metres. When compared to equivalent forest inventory attributes, model predictions of stems per hectare and crown radius were shown to be reasonably estimated using a Kruskal–Wallis ANOVA (p < 0.001). These predictions were then used to create a large area map that provided an assessment of the forest area susceptible to mountain pine beetle damage.
forest health, forest inventory, geometric optical modelling, landsat, lodgepole pine, mountain pine beetle, susceptibility, western canada
0303-2434
444-452
Coggins, Sam B.
affb61d0-4d5e-4be3-8f62-d0fd0f90b5f8
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Wulder, Michael A.
13414360-db3d-4d88-a76d-ccffd69d0084
Coggins, Sam B.
affb61d0-4d5e-4be3-8f62-d0fd0f90b5f8
Coops, Nicholas C.
5511e778-fec2-4f54-8708-de65ba5a0992
Hilker, Thomas
c7fb75b8-320d-49df-84ba-96c9ee523d40
Wulder, Michael A.
13414360-db3d-4d88-a76d-ccffd69d0084

Coggins, Sam B., Coops, Nicholas C., Hilker, Thomas and Wulder, Michael A. (2013) Augmenting forest inventory attributes with geometric optical modelling in support of regional susceptibility assessments to bark beetle infestations. International Journal of Applied Earth Observation and Geoinformation, 21, 444-452. (doi:10.1016/j.jag.2012.06.007).

Record type: Article

Abstract

Assessment of the susceptibility of forests to mountain pine beetle (Dendroctonus ponderosae Hopkins) infestation is based upon an understanding of the characteristics that predispose the stands to attack. These assessments are typically derived from conventional forest inventory data; however, this information often represents only managed forest areas. It does not cover areas such as forest parks or conservation regions and is often not regularly updated resulting in an inability to assess forest susceptibility. To address these shortcomings, we demonstrate how a geometric optical model (GOM) can be applied to Landsat-5 Thematic Mapper (TM) imagery (30 m spatial resolution) to estimate stand-level susceptibility to mountain pine beetle attack. Spectral mixture analysis was used to determine the proportion of sunlit canopy and background, and shadow of each Landsat pixel enabling per pixel estimates of attributes required for model inversion. Stand structural attributes were then derived from inversion of the geometric optical model and used as basis for susceptibility mapping. Mean stand density estimated by the geometric optical model was 2753 (standard deviation ± 308) stems per hectare and mean horizontal crown radius was 2.09 (standard deviation ± 0.11) metres. When compared to equivalent forest inventory attributes, model predictions of stems per hectare and crown radius were shown to be reasonably estimated using a Kruskal–Wallis ANOVA (p < 0.001). These predictions were then used to create a large area map that provided an assessment of the forest area susceptible to mountain pine beetle damage.

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More information

Accepted/In Press date: 15 June 2012
e-pub ahead of print date: 10 September 2012
Published date: April 2013
Keywords: forest health, forest inventory, geometric optical modelling, landsat, lodgepole pine, mountain pine beetle, susceptibility, western canada
Organisations: Global Env Change & Earth Observation, Geography & Environment

Identifiers

Local EPrints ID: 384651
URI: https://eprints.soton.ac.uk/id/eprint/384651
ISSN: 0303-2434
PURE UUID: 923e905b-37ae-493a-94fe-028d9882d57f

Catalogue record

Date deposited: 27 Jan 2016 12:17
Last modified: 15 Jul 2019 20:55

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