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Applied Analysis Inc.
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Billerica, MA 01821
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 PH: 978-663-6828
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Pest Infestation Studies

Can you measure pest infestation over wide inaccessible areas?
The study area was located on the Manti-LaSal National Forest in east central Utah on a high plateau known as the Wasatch Plateau. The area was experiencing extensive mortality in the Engelmann spruce type due to an ongoing spruce beetle outbreak. Ground and aerial survey information on the outbreak collected during the same time as the acquired Landsat TM imagery was available.

IMAGINE Subpixel Classifier did!


Project area within the Wasatch Plateau

Objective
The purpose of the project was to investigate the utility and potential application of sub-pixel processing and analysis for forest health protection applications. The scope of the effort included not only the project, but also an evaluation of how subpixel analysis could potentially fit into the workflow associated with a project involving standard image processing.

Approach
Three dates of Landsat Thematic Mapper images, from 1985, 1988, and 1993, were acquired to have imagery of the area prior to the outbreak, at the initial stage of the outbreak, and during the ongoing outbreak of spruce beetle infestation. The imagery was processed using IMAGINE Subpixel Classifier software. The results were compared with existing ground survey reports conducted in 1992 and 1994 with aerial photographs flown of the area in 1991.

Challenges
· Sketch mapping and ground survey have limited utility in wilderness areas where ground access is difficult and aerial mapping too costly

· The original study area consists of separated stands of spruce in different states and environments – different facing slopes and meadows, no greater than 60 percent canopy closure on average in major spruce stands, and abundant exposed bedrock

· The project required an examination of scene-to-scene migration of the derived reference signatures

Conclusions
"Based on the preliminary results…subpixel analysis can be applied to forest pest management situations. However, the application should be handled on a pest-by-pest basis, as it is definitely not a blanket approach to all the pests that impact the forest health. It should be viewed as a supplement to existing means of detecting and evaluating pest infestations.

IMAGINE Subpixel Classifier MOI classification on a southern portion of the study area using signatures derived from 2 spectral clusters with a Mean Material Fraction (MMF) of 0.50. Note the correspondence between the classification and the sketch map ploygons. Polygons and trees per acre mortality counts are from 1993 aerial sketch mapdata of the Wastach Plateau area.

"There are several application areas in forest health monitoring where subpixel analysis can play a role. In terms of large area assessment, it could be used to monitor areas where aerial sketch mapping and ground surveys are not conducted. Signatures could be developed using known areas of infestation, then migrated and applied to satellite imagery covering remote areas. In cases where pest infestations are too extensive to map with aerial sketch mapping, subpixel analysis of satellite imagery could be used to supplement infestation estimates. …

"For more species specific applications, Abies species and some Pinus species hold discolored needles for long time periods following pest attack. Such pests would allow for the potential development of unique signatures specific to the infestation."

Acknowledgement
Images, information, and quoted text in the Pest Infestation section are courtesy of USDA Forest Service and investigation participants: Forest Health Technology Enterprise Team, Forest Health Protection, Manti-LaSal National Forest and the Remote Sensing Applications Center. For futher information see "An Evaluation of the Utility of Sub-Pixel Analysis of Thematic Mapper Imagery for the Spruce Beetle Outbreak on the Manti-LaSal National Forest".

 



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External Links
· Leica-Geosystems
· Space Imaging
· DigitalGlobe
· SPOT Image
· ORBIMAGE
· USGS EarthExplorer
· USGS Landsat 7
· GeoCommunity
· Geography Network
· Flight Landata


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