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Local indicators for categorical data: impacts of scaling decisions

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Abstract:

When the geographic distribution of landscape pattern varies, global indices fail to capture the spatial nonstationarity within the dataset. Methods that measure landscape pattern at a spatially local scale are advantageous, as an index is computed at each point in the dataset. The geographic distribution of local indices is used to discover spatial trends. Local indicators for categorical data (LICD) can be used to statistically quantify local spatial patterns in binary geographic datasets. LICD, like other spatially local methods, are impacted by decisions relating to the spatial scale of the data, such as the data grain (p), and analysis parameters such as the size of the local neighbourhood (m). The goal of this article is to demonstrate how the choice of the m and p parameters impacts LICD analysis. We also briefly discuss the impacts spatial extent can have on analysis; specifically the local composition measure. An example using 2006 forest cover data for a region in British Columbia, Canada where mountain pine beetle mitigation and salvage harvesting has occurred is used to show the impacts of changing m and p. Selection of local window size (m = 3,5,7) impacts the prevalence and interpretation of significant results. Increasing data grain (p) had varying effects on significant LICD results. When implementing LICD the choice of m and p impacts results. Exploring multiple combinations of m and p will provide insight into selection of ideal parameters for analysis.

Keywords: Analyse spatiale; Dendroctonus ponderosae; composition; configuration; dendroctone du pin ponderosa; forme spatiale; fragmentation; mountain pine beetle; spatial analysis; spatial pattern

Document Type: Research Article

DOI: https://doi.org/10.1111/j.1541-0064.2009.00300.x

Affiliations: 1: Spatial Pattern Analysis and Research (SPAR) Laboratory, Department of Geography, University of Victoria, Victoria, British Columbia, Canada V8W 3R4 ( ), Email: jlong@uvic.ca 2: Spatial Pattern Analysis and Research (SPAR) Laboratory, Department of Geography, University of Victoria, Victoria, British Columbia, Canada V8W 3R4 ( ), Email: trisalyn@uvic.ca 3: Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, British Columbia, Canada V8Z 1M5 ( ), Email: mwulder@pfc.cfs.nrcan.gc.ca

Publication date: 2010-03-01

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