[mapserver-users] Heatmap / choropleth from points attributes
outerspaceman81 at yahoo.com
Wed Feb 23 07:56:43 EST 2011
First, you have to turn your points into shapes, theres some algorithm that will turn points into polygons with borders midway between each point. Then, you have to add classes to the mapfile. Add one class per color. You have to calculate the bounds and color for each class like this:
CLASS EXPRESSION(([POPULATION] gt 90457) AND ([POPULATION] le 108397)) STYLE COLOR 10 20 50 ENDEND
If your CSV data isnt joined to the mapserver data, you have to calculate what shapes are in each bucket like this-
CLASS EXPRESSION(([NAME] = "Shape1") OR ([NAME] = "Shape2")) STYLE COLOR 10 20 50 ENDEND
--- On Tue, 2/22/11, Daniel Cole <daniel at southernsolutionsms.com> wrote:
From: Daniel Cole <daniel at southernsolutionsms.com>
Subject: [mapserver-users] Heatmap / choropleth from points attributes
To: mapserver-users at lists.osgeo.org
Date: Tuesday, February 22, 2011, 10:06 PM
I am a new mapserver user and have spent countless hours over the last month reading, trying code, etc. before posting here for help. I am trying to generate an image (non-interactive) on a webpage based off of attribute data in a points file. For example, 20 different points equally distributed in a field contain data about the moister level of the soil. I want to make the lowest levels blue and the highest levels yellow, or something like that with some gradients in between. If possible I want it to have interpolated data between them to show the gradual change, but that isn't a must. I also want to wrap it in a polygon that trims the edges.
I found some python code that I thought might do the trick , but it seems lots of heat maps are based off of how many points exist in a certain area, and thats now what I am doing.
My points contain numbers in the attributes, 5, 25, 92, 71, etc. I feel like I am missing some easy way to do this right in front of me with gdal or something. If someone has any direction or even demo code that would be greatly appreciated.
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