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An Incremental and Philosophically Different Approach to Measuring Raster Patch Porosity

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  • Tarmo K. Remmel

    (Department of Geography, York University, 4700 Keele Street, Toronto, ON M3J 1P3, Canada)

Abstract

A new method for measuring the porosity of individual 2D raster patches in a GIS for characterizing the combined complexity of a shape’s edge in conjunction with its internal perforations is developed. The method is centered on comparing the number of cellular edge–edge joins relative to the theoretical maximum number of similar joins possible given a set number of cells comprising a landscape patch. As this porosity (Φ) increases, the patch (or shape) can be viewed as deviating from a maximally compact form, comprising higher edge complexity and internal heterogeneity (inclusion of perforations). The approach is useful for characterizing shapes for which a simple perimeter- or area-based metric misses the internal complexity and where the porosity of the patch may provide insight into spatial processes leading to the development of the landscape fabric. I present theoretical results to illustrate the mechanics of the approach and a small case study of boreal wildfire residual vegetation patches in Ontario, where real resulting wildfire process-driven landscape patches are assessed for their porosity at five spatial resolutions. The results indicate that naturally occurring and unsuppressed boreal wildfires in the study area typically produce residual vegetation patches with an average porosity of 17.6%, although this value varies slightly with the spatial resolution of the data representation.

Suggested Citation

  • Tarmo K. Remmel, 2018. "An Incremental and Philosophically Different Approach to Measuring Raster Patch Porosity," Sustainability, MDPI, vol. 10(10), pages 1-14, September.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:10:p:3413-:d:171928
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    References listed on IDEAS

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    1. Birch, Colin P.D. & Oom, Sander P. & Beecham, Jonathan A., 2007. "Rectangular and hexagonal grids used for observation, experiment and simulation in ecology," Ecological Modelling, Elsevier, vol. 206(3), pages 347-359.
    2. T.K. Remmel & F. Csillag, 2003. "When are two landscape pattern indices significantly different?," Journal of Geographical Systems, Springer, vol. 5(4), pages 331-351, December.
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