HeatMapApi.com is a new service which allows Google Maps mashups to integrate heat map representations easily. Heat maps,  or more generally point to raster interpolations allow the graphical representation of point patterns through the use of continuous colors identifying areas of higher or lower density of points. Areas where this has been employed are crime hotspots analysis or economic activity analysis.

A novel concept in Web 2.0 mashups, I was interested in finding out what the methodology was behind the generation of these rasters. Sadly, I couldn’t find a definitive answer on the algorithm that the website uses to generate its hotspot maps. They do expose in their API two variables that can influence the generation of the heatmaps, decay and boost, but without information on the algorithm behind it, the setting of these values remains a pure exercise in trial and error, and seeing what “looks” best. Also, because the parameters are set as “optional”, most developers will be tempted into a one size fits all approach, smoothing out interesting patterns in the data, or creating hotspots that are not statistically viable, creating masses of effectively meaningless maps.

Mashup developers thus will more than ever the spatial analysis literacy skills to understand the processes, models and algorithms that lie behind the pretty maps.

Note: This is not a new problem, but has been present all through the development of Exploratory Spatial Data Analysis over the past 20-30 years in academia and commercial settings, and a lot can be learned from this past experience.