Showing posts with label GIS. Show all posts
Showing posts with label GIS. Show all posts

Saturday, May 11, 2013

KDE: 1854 LONDON CHOLERA OUTBREAK

Kernel Density Estimation (KDE), also known as a "heatmap," is a wonderful way to graphically convey epidemiological data for outbreaks of infectious disease. At a glance, one can discern likely points of origin, routes of transmission, and density by area. KDE maps are attractive and fairly easy to render in QGIS, but it can be exceedingly difficult to obtain spatial point data, which is necessary for creating the nodes used by the software to model density. For this KDE, the underlying raster image is John Snow's original 1854 map, with vector overlays of spatial point data showing water pumps and cholera deaths. The proportional mortality is most densely concentrated around the Broad Street pump (the source of infection as deduced by John Snow). For proper viewing, click HERE to enlarge.

Density radius: 30m
Decay rate: 0
Cell size X,Y: ~1,1
Global transparency: 20%
Pseudocolor


Snow's original map is available in a high resolution format here:
 http://upload.wikimedia.org/wikipedia/commons/2/27/Snow-cholera-map-1.jpg

Unfortunately I did not bookmark the site which offered the spatial point data for download, but if I can locate it again, I'll be sure to give appropriate credit here.

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Monday, May 6, 2013

H7N9 CHOROPLETH

After an extended hiatus, I've again taken to toying with QGIS. Below is a choropleth map that I made last week. It illustrates all reported cases of H7N9 in China, by province, as of 05/03/13. (Click to enlarge.)


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Saturday, April 28, 2012

LEARNING GIS

I figure that it's about time I get my feet wet with Geographic Information Systems (GIS). The eventual goal is to render original choropleth maps and compile epidemiological data in a graphic and useful way. Below are a couple of very rudimentary maps I authored with ArcGIS Online. The public feature layer sets seem pretty limited, so I'll probably just start making my own once I learn the software and acquire some relevant samples. I'm also playing around with Quantum GIS, GeoDa, and R. Details to follow. 


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Map 1: Greater Cleveland Area, USA Crime Index



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Map 2: Greater Cleveland Area, Populations of Individuals Aged 25+ who Lack College Degree