Spatial Analysis of High Resolution Aerial Photographs to Analyze the Spread of Mountain Pine Beetle Infestations

Eric Fox, Shivanand Balram, Suzana Dragicevic, Arthur Roberts

Abstract


Mountain pine beetle (Dendroctonus Ponderosae) infestations in Western Canada have reached alarming proportions. The spread of attacks has significantly impacted pine tree stocks, the forest ecosystem in general and the overall socio-economic condition of residents in communities that depend on the forest industry. The ability to track these attacks and anticipate their trajectories will allow forest managers to target intervention measures and improve mitigation efforts. Spatial analysis methods are well suited to characterize the dynamics of the mountain pine beetle attacks. This study implemented a multi-scale spatiotemporal analysis to describe the patterns of three consecutive attack years (2000-2002) for a 19 km2 study site in British Columbia, Canada. In the first stage, baseline complete spatial randomness (CSR) was examined using average nearest neighbour analysis and quadrat counts on infestation data extracted from 19 cm resolution black and white aerial photographs. In the second stage, global and local Moran’s I spatial autocorrelation statistics, Getis-Ord General G global high/low clustering and Getis-Ord G_i^* test statistic techniques were used to evaluate the spread patterns over time. The results show a significant clustering of attack sites in the first two years, with considerable changes in the attack spread in the third year. These changes were independent of the two levels of spatial resolution used. Knowledge about infestation patterns can be used to anticipate needed social and environmental assistance for affected communities. Further, the information can aid overall sustainable forestry management.


Full Text: PDF DOI: 10.5539/jsd.v5n9p106

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This work is licensed under a Creative Commons Attribution 3.0 License.

Journal of Sustainable Development   ISSN 1913-9063 (Print)   ISSN 1913-9071 (Online)

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