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Curve Fit: a pixel-level raster regression tool for mapping spatial patterns

De Jager, N.R. and T. J. Fox.  2013.  Curve Fit: a pixel-level raster regression tool for mapping spatial patterns. Methods in Ecology and Evolution; British Ecological Society 2013. 4 pp. On-line first.

Abstract

Geographic patterns can change through time and/or across space, and these changes can lead to differences in the movement pattern and body condition of organisms, their interactions with each other and their environment, and ultimately lead to population and community-level changes. When quantifying landscape patterns using remotely sensed data, it is important to recognize that each pixel (i.e. picture element) has a temporal and spatial context. A pixel’s temporal context refers to its past and present classification. The spatial context of a pixel depends on the classification of neighbouring pixels, and the size of the area considered as the neighbourhood. Despite the fact that pixels are the basic unit of a map and that they have a spatial and temporal context, there is currently no software package or tool that can be used to quantify changes that take place at the pixel level with changes in time or spatial scale.

Curve Fit, an extension to the GIS application ArcMap, allows users to run regression analysis on a series of raster data sets. A full description of the extension, installation instructions and brief example of its use can be found at: http://www.umesc.usgs.gov/management/dss/curve_fit.html. Curve fit outputs characterize continuous spatial or temporal change across a series of raster data sets.  

Keywords

ArcMap, landscape assessment, landscape pattern, scale, UMRR-EMP LTRMP