I recentley graduated from the Geographic Information Science and Tecnology (GIST)
program at the Spatial Sciences Institute (SSI) at the University of Southern California (USC).

The intent of the thesis research was to rethink data silos and avoid the modifieable areal unit problem, MAUP. I investigated food accessibility in Lane County, OR calculating distances between residential addresses and different types of food outlets using Dun and Bradstreet's business data available in Business Analyst (Esri) and address points from the local GIS department. The top three take aways from the program overall were: 1) Web map applications that work with all available toolsets across all platforms will change the work; 2) Python scripts for multi-step GIS production are essential, thank you Guido van Rossum; and 3) Data transformations, ahem -- yes!

Maps Splash

Address point cell counts

A 10 X 10 mile grid overlays the distribution of address points.

Food outlet distribution

Food outlet geolocations obtained from Business Analyst.

Large supermarket distances from addresses

Distance classifications aligned with past food access research.

Aggregated distances

CBGs number labels are at distances over the 10 mile threshold.

Minority composition and deprivation index

Social demographic and econmic variables mapped.

Two mile distance band

Presence and absence anlysis.

Get In Touch

Discussions @ networks, fractal art made using GIS, and Raspberry PI are shuffled to the top of the heap.

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    100 Percent Lane
    Springfield, OR 97477
    United States
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