In order to do that, we need three rasters: a water mask raster, a patch IDs raster, and a patch cover raster.
For that, we have extended raster image correlation spectroscopy (RICS) protocols to be able to discriminate the anisotropy in the diffusion coefficient tensor.
Contradicting what we would expect from the raster plots we find that the avalanche sizes are smaller (on average) in the supercritical system.
To do a shear operation on a raster image (that is to say, a bitmap), we just shift all the pixels in a given row (column) by an easy-to-calculate displacement.
To ensure the accuracy of the data we overlaid the geolocated occurrence points with a raster that distinguished land from water.
The raster map of PD risk that we produced made it possible to identify local "cold" (green color) and "hot" spots (red color) of PD risk in the area where PD outbreaks area commonly occurring.
Recently several algorithms have been developed to calculate the solar photovoltaic (PV) potential on the basis of 2.5D raster data that can capture urban morphology.
Data is available in raw.fif format or in Matlab raster format that is compatible with the neural decoding toolbox (readout.info).info
See Homer et al. (2012) Percent bare ground Estimated percent of each pixel comprising the raster surface that is bare ground.
See Homer et al. (2012) Percent litter Estimated percent of each pixel comprising the raster surface that is herbaceous litter.
