Generating a KML heatmap from given data set of [lat, lon, density]
I am looking to build a static KML (Google Earth markup) file which displays a heatmap-style rendering of a few given data sets in the form of [lat, lon, density] tuples.
A very straightforward data set I have is for population density.
My requirements are:
- Must be able to feed in data for a given lat, lon
- Must be able to specify the density of the data at that lat, lon
- Must export to KML
The requirements are language agnostic for this project as I will be generating these files offline in order to build the KML used elsewhere.
I have looked at a few projects, most notably heatmap.py, which is a port of gheat in Python with KML export. I have hit a brick wall in the sense that the projects I have found to date all rely on building the heatmap from the density of [lat, lon] points fed into the algorithm.
If I am missing an obvious way to adapt my data set to feed in just the [lat, lon] tuples but adjusting how I feed them using the density values I have, I would love to know!
Answer
Hey Will, heatmap.py is me. Your request is a common-enough one and is on my list of things to address. I'm not quite sure yet how to do so in a general fashion; in heatmap.py parlance, it would be straightforward to have a per-point dotsize instead of a global dotsize as it is now, but I'm not sure that will address the true need. I'm aiming for a summer 2010 release, but you could probably make this mod yourself.
You may try searching for Kernel Density Estimator tools; that's what the statisticians call heatmaps. R has some good built-in tools you can use that might satisfy your need more quickly.
good luck!