VAMLIS 2018 Winners

University of Richmond students from the Advanced Spatial Analysis course took home 1st, 2nd, and 3rd place in the Undergraduate Web Map competition at the 2018 VAMLIS Virginia GIS Conference in Virginia Beach. Congratulations to these amazing students!!!

Check out their web maps below!

Left to Right
Emily Routman (1st), Stanford Lee (2nd) and Conor Tenbus (3rd)

The winners with their Professor/Mentor Kim Browne, Director of the Spatial Analysis Lab



1st: Emily Routman ’20

Immigrants account for around 17% of Dallas’ population, and they have a big impact on local businesses, jobs, and more. I am going to analyze–by census tract–which immigrant populations (by country of origin) are more likely to cluster together, and which are less likely to.

2nd: Stanford Lee ’19

I used American Community Survey (ACS) 2016 data from the US Bureau of the Census and United States Geological Survey National Land Cover Database (NLCD) to create a weighted index model on the vulnerability of populations within the City of Richmond. This vulnerability index is my contribution to the Urban Heat Island Project collaboration with the Science Museum of Virginia. The vulnerability factors from the ACS data were: poverty rates, racial demographics, age demographics, education levels, and unemployment rates. Land cover data specifically aimed towards identifying land cover classes in the areas of the vulnerable populations will also be analyzed. The main objective of this project is to identify locations showing the most vulnerable areas within the City of Richmond so they can be compared with areas of extreme temperature.

3rd: Conor Tenbus ’18

GfK MRI is a survey and analytics company that completes an annual Survey of the American Consumer. Part of this survey includes MLB game attendance and an MLB “Super Fan” Poster/WebMap App Abstracts from the 2018 VA GeoCon 9 | Page designation. Using this data (provided by ArcGIS Business Analyst) at the county (maybe hex bins) level, I will analyze “fan-ship” intensity in relation to proximity to nearest MLB ballpark.