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Detecting mountain pine beetle red attack damage with EO-1 Hyperion moisture indices

Detecting mountain pine beetle red attack damage with EO-1 Hyperion moisture indices
Detecting mountain pine beetle red attack damage with EO-1 Hyperion moisture indices
The mountain pine beetle (Dendroctonus ponderosae) is the most destructive insect of mature pine forests in western North America. Time series of wetness transformations generated from Landsat imagery have been used to detect mountain pine beetle red attack damage over large areas. With the recent availability of high spatial (QuickBird) and high spectral (Hyperion) resolution satellite sensor imagery, the relationship between spectral moisture indices and levels of red attack damage may be investigated. Six moisture indices were generated from Hyperion data and were compared to the proportion of the Hyperion pixel having red attack damage. Results indicate the Hyperion moisture indices incorporating both the shortwave infrared (SWIR) and near infrared (NIR) regions of the electromagnetic spectrum concurrently, such as the Moisture Stress Index, were significantly correlated to levels of damage (r =0.51; p=0.0001). The results corroborate the hypothesis that changes in foliage moisture resulting from mountain pine beetle attack are driving the broad-scale temporal variation in Landsat derived wetness indices. Furthermore, the results suggest that Hyperion data may be used to map low levels of mountain pine beetle red attack damage over large areas that are not consistently captured with Landsat data.
0143-1161
2111-2121
White, J.C.
2a3dffea-5fa9-4065-9e4d-34b7abafa1a0
Coops, N.C.
b10725db-8b4c-4338-92b8-ead49cebc80e
Hilker, T.
c7fb75b8-320d-49df-84ba-96c9ee523d40
Wulder, M.A.
e9b0e7a1-494e-40cf-a1e5-20f487f6c6ff
Carroll, A.L.
59957e0b-1ad8-4a37-a195-107bb017cf8a
White, J.C.
2a3dffea-5fa9-4065-9e4d-34b7abafa1a0
Coops, N.C.
b10725db-8b4c-4338-92b8-ead49cebc80e
Hilker, T.
c7fb75b8-320d-49df-84ba-96c9ee523d40
Wulder, M.A.
e9b0e7a1-494e-40cf-a1e5-20f487f6c6ff
Carroll, A.L.
59957e0b-1ad8-4a37-a195-107bb017cf8a

White, J.C., Coops, N.C., Hilker, T., Wulder, M.A. and Carroll, A.L. (2007) Detecting mountain pine beetle red attack damage with EO-1 Hyperion moisture indices. International Journal of Remote Sensing, 28 (10), 2111-2121. (doi:10.1080/01431160600944028).

Record type: Article

Abstract

The mountain pine beetle (Dendroctonus ponderosae) is the most destructive insect of mature pine forests in western North America. Time series of wetness transformations generated from Landsat imagery have been used to detect mountain pine beetle red attack damage over large areas. With the recent availability of high spatial (QuickBird) and high spectral (Hyperion) resolution satellite sensor imagery, the relationship between spectral moisture indices and levels of red attack damage may be investigated. Six moisture indices were generated from Hyperion data and were compared to the proportion of the Hyperion pixel having red attack damage. Results indicate the Hyperion moisture indices incorporating both the shortwave infrared (SWIR) and near infrared (NIR) regions of the electromagnetic spectrum concurrently, such as the Moisture Stress Index, were significantly correlated to levels of damage (r =0.51; p=0.0001). The results corroborate the hypothesis that changes in foliage moisture resulting from mountain pine beetle attack are driving the broad-scale temporal variation in Landsat derived wetness indices. Furthermore, the results suggest that Hyperion data may be used to map low levels of mountain pine beetle red attack damage over large areas that are not consistently captured with Landsat data.

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More information

Accepted/In Press date: 2 June 2006
Published date: 2007
Organisations: Earth Surface Dynamics

Identifiers

Local EPrints ID: 384703
URI: http://eprints.soton.ac.uk/id/eprint/384703
ISSN: 0143-1161
PURE UUID: ce88708d-ab94-4978-9f82-76e93a09336d

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Date deposited: 14 Apr 2016 14:32
Last modified: 14 Mar 2024 22:03

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Contributors

Author: J.C. White
Author: N.C. Coops
Author: T. Hilker
Author: M.A. Wulder
Author: A.L. Carroll

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