Geography 4427 Geography 4427, Advanced GIS II is the capstone undergraduate GIS course at Texas State University-San Marcos. In this course students worked as teams on real-world GIS projects. These projects were designed and conducted by the students under the direction of Yongmei Lu and Matthew Connolly. This course helps students develop and demonstrate competence in applying GIS techniques to actual geographic questions. Click on the links below to find detailed information about each of the groups and their projects.
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| Although much has been done to understand, quantify, and delineate the natural and environmental hazards affecting the Greater Houston area, there have not been any efforts to spatially display the shelter network that is utilized by the Greater Houston Area Chapter of the American Red Cross (GHAC). Emergency Management Solutions Group (E.M.S. Group) set out to give the GHAC a tool that could be used to save lives. Utilizing geographic information systems (GIS),we gave the GHAC a very detailed and organized geographic information system that we felt would best serve not only the community, but also the GHAC organization. In our research we looked at multiple shelter sites, floodplain information, socioeconomic factors as well as hurricane surge zones, and chemical plants. It is our hope that the work we invested will streamline efficiency and decision making process of the GHAC staff and volunteers when an event occurs as well as plan for and coordinate during a disaster event. | T.A.G.S produced a project entitled Analysis of Texas Fatal Traffic Crashes. The project identifies spatial trends and patterns of fatal traffic crashes in the state of Texas for 2008 by looking at several different factors specific to the vehicle drivers, driver age groups, roadway conditions, roadway types, various driver factors and other related issues involved in the fatal crashes. The study focuses on using geographic analysis through the use of Geographic Information Systems in conjunction with various traffic accident datasets in order to draw conclusions and provide a spatial visualization of the fatal crashes and the factors involved. The project is intended to provide helpful information and analysis to public and private sectors in order to gain a better understanding of fatal traffic crashes and the factors involved in the crashes. Along with the tragic loss of lives it is also important to study and analyze fatal crashes because of the annual cost to the state of Texas. This study identifies some problem areas and factors that can be looked at in order to aid in the development of preventative measures and policy-making decisions. |
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| Geo Planning Solutions is working with The City of Martindale to build on past projects in order to produce growth and enforce the current ordinances. Projects include creating an inventory of all private signs with the city limits and ETJ. New federal regulations related to sign reflectivity have called for The City of Martindale to ask for Geo Planning Solutions?assistance in creating a second inventory of all regulatory and public information signs in order for the city to create a replacement schedule. In addition, we created an inventory of all fire hydrants with the city limits to plan for future expansion based on standard recommendations related to distance and accessibility. Finally, we developed a GIS layer of current paying wastewater customers in order to figure which customers are in the system. | Capital Area Tracking Services?Digitization, Analysis, and Prediction of feral Cat Colonies in San Marcos, Hays County, Texas project worked with nonprofit organization San Marcos TNRM to create a geodatabase from them to help them to meet compliance with City of San Marcos code requiring feral cat colony listings. To complete this, we took hard copy data records of cats for Hays County, aggregated cat listings into ‘colonies? a location where the cats are centered. Our group took this spatial data, performed an analysis on it to determine any correlation between cat colony location and other variables for the area, including land use, population density, and median income for the area. With this data, we were able to discern the environments feral cats were most compatible with and were able to predict locations of future cat colonies. |
