I have a raster map of US Midwest which is very sparse, i.e. the pixels of interest are few enough to be almost invisible when viewed at a scale where all states of US Midwest are visible. I would like to follow the approach outlined in this PNAS paper (http://www.pnas.org/content/110/10/4134.full) to create a better map, but not sure how to replicate it in ArcGIS Desktop.
The PNAS paper outlines the steps as follows:
Because of the small sizes and scattered distribution of change areas, it was difficult to visualize regional patterns of LCLUC at the original 56-m spatial resolution. As a result, we used spatial smoothing techniques to create a regional change surface that highlighted local hotspots of change. Related approaches are used in fields such as spatial epidemiology to generate stable estimate of disease rates (48) but have not been broadly applied in the field of land change science. In our smoothing approach, change pixels at 56-m spatial resolution were first aggregated to the percentage of change at 560-m resolution. This was done by taking 10-by-10 blocks of 56-m pixels (i.e., 100 pixel blocks) and summing the binary change within each block (Fig. S4A). Next we used a 2D kernel smoother to compute a smoothed estimate of percent change for each of the 560-m resolution pixels (Fig. S4B). A quartic kernel function was used to calculate moving averages across the study area at a bandwidth of 10 km. The same quartic kernel function was used to smooth percent change from corn/soy in 2006 to grassland in 2011. Finally, we generated a smoothed map of grassland cover in 2006 by aggregating grassland presence at 56-m resolution to percent grassland cover at 560-m resolution, and then smoothing this aggregated cover layer by using the same 10-km quartic kernel. This smoothed grassland cover layer was subsequently used as the denominator in generating a map of relative rates of grassland conversion.
As far as I understand, this is the flowchart:
- Use block statistics in ArcGIS to sum 10x10 pixels of 56-m raster to 560m raster
- 2D kernel smoother: not sure how to do this
- Quartic kernel: not sure how to do this
Not sure how to progress beyond step 1