Variable raster scan patterns of 1024 × 64, 512 × 128, and 256 × 256 pixels (horizontal × vertical) can be selected.
Eqn (2) was calculated using the spatial analyst tools module based on spatialized variables in raster format data layers.
For the environmental variables available in raster format, this involved extracting the mean value of the pixels that fell within the polygon that defined the boundary of the postcode.
The dissection pattern is encapsulated by a continuous map of drainage density, a raster variable best suited for showing spatial variability of dissection.
All input files were manipulated in ArcGIS 10 (ESRI, Redlands, CA) to produce variable layers in raster format at 10 m resolution, except for the digital elevation model where the finest available resolution was 30 m. From the latter data, relative elevation was defined as the mean centered city-specific elevation.
Finally, we extracted values from the raster habitat variables to both used and available locations.
To briefly summarize the methodology described in Wilson et al. [13], CCA models were developed, based on a 1/8th subsample of the plots, that related the multivariate response variable measured on the field plots (live tree basal area by species) with the associated 21 predictor variables extracted from the raster stack at each plot location.
All environmental variables were resampled to raster data with a spatial resolution of 0.00833° (nearly 1 km).
To briefly summarize the methodology described in Wilson et al. [ 13], CCA models were developed, based on a 1/8th subsample of the plots, that related the multivariate response variable measured on the field plots (live tree basal area by species) with the associated 21 predictor variables extracted from the raster stack at each plot location.
Interpolation of the data transforms the point variables into spatial components in raster format as each pixel in the raster has its own value and represents a point recharge rate.
