GIS Workshops: Home

Explored the distribution of TCEQ air monitoring stations in North Central Texas, and identified highway segments that traverse through the highest concentrations of ozone.

Used City of Arlington Police Department's data to examine the distribution of burglary arrests and devised a (simple) model explaining possible predictors of these crimes.

Identified areas in Texas with clusters of estimated cancer populations without easy access to treatment facilities by exploring the distribution of hospitals, cancer treatment facilities, estimated populations with cancer, concentrations of race groups, income, and health insurance data in Texas.

Identifed areas in Tarrant and Dallas County that would be most suitable for a new pizzeria using seven variables, including proximities to other pizzerias, major roads, and franchises; number of households frequenting pizzerias; and local area income.

Identified the watershed around a home address (or any address) in Tarrant or Dallas counties and then identified potential sources of pollution within or near this watershed using hydrology tools within ArcGIS Desktop, including fill, flow direction, and flow accumulation.

Taught how Geographic Information Systems and ESDA (Exploratory Spatial Data Analysis) can help to estimate ozone levels across the state. In addition to ESDA, this workshop covered the basics of kriging, a popular interpolation method. No GIS or statistical background required.

Used income, population density, presidential election result, and gubernatorial election result variables to identify the election patterns in Texas neighborhoods and then predict the percent likelihood that any given community will vote Republican in the upcoming Presidential elections. Results were then mapped within Google Earth.

Targeted participants with at least a basic understanding of ArcMap and taught the basics of creating a Python script. Assted participants in becoming familiar with the native Python environment IDLE and in learning how to call geoprocessing functions into scripts.

Taught how to use various government data sources to extract Barnett Shale-related data for use within Geographic Information Systems.

Identified the food deserts in Dallas and Tarrant Counties, using proximity to supermarkets, poverty levels, number of elderly, single parents, and car owners as variables.

Identified the happiest and saddest countries on Earth, using a combination of 15 variables. The top 10 results were then viewed online at ArcGIS.com.

Sylvia Rawlings, guest lecturer, presented background information on recent health care policy and its impact on rural Texas. Joshua Been led participants through a hands-on GIS exercise exploring healthcare in rural Texas.