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Multitemporal remote sensing of landscape pattern dynamics resulting from mountain pine beetle infestation and timber harvest Gillanders, Steve Neil

Abstract

Occurring over multiple years and impacting an area over 13 million hectares to date, the current epidemic of mountain pine beetle (Dendroctonus ponderosae Hopkins) in British Columbia lends itself to the use of remote sensing technologies for monitoring purposes. Change detection procedures based upon spectral values are common; however, monitoring changes in landscape pattern presents opportunities for the generation of unique and ecologically important information. Furthermore, while the use of two images may provide the means to identify change, the use of more than two images affords the ability for long-term monitoring and characterization of processes such as change rates and dynamics. The initial component of this study consists of a literature review undertaken to investigate and summarize methods and applications of landscape pattern analysis using three or more image dates. This information was in turn used to make recommendations for the application of landscape pattern analysis of a time-series of remotely-sensed data to a case study involving mountain pine beetle infestation and timber harvesting. Following the review, we focused on the detection and monitoring of lodgepole pine stands in order to quantify the progression of forest fragmentation and loss of connectivity as a result of mountain pine beetle infestation and timber harvest. This was accomplished using a key set of landscape pattern indices applied to six Landsat satellite images spanning 1993 to 2006. Through our analysis we found that the impacts of the mountain pine beetle on forest spatial pattern consist of an increase in the number of forest patches, shape complexity, and patch isolation, and a decrease in forest patch size and interspersion. In addition, we determined that in a spatial context, mountain pine beetle infestation plays a significantly greater role in forest fragmentation and loss of connectivity than timber harvest. However, we also discuss the limitations of these findings due to the differences between natural and anthropogenic disturbances and the inability of Landsat data to detect patch-level dynamics. This research demonstrates the unique information available from satellite image time-series combined with landscape pattern analysis to better understand the combined effects of insect infestation and forest harvesting.

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Attribution-NonCommercial-NoDerivatives 4.0 International

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