A comparative study of commuting patterns in Dallas, TX and Washington, DC highlights the potential benefits of increasing housing density through the City of Dallas’ proposed inclusionary zoning initiative. Presented at the 2018 American Association of Geographers Annual Meeting. Click here for the presentation.
This interactive tool allows users to weigh the importance of five different indices related to the opportunity of one's neighborhood: jobs proximity, poverty, racial diversity, violent crime, and the cost to develop housing. The user can identify high-opportunity neighborhoods while also considering the cost of subsidizing housing there. Click here to see.
This bivariate choropleth map allows the user to view the overlap of poverty rates and racial diversity simultaneously at the census tract level. It's also searchable by city or state. Click here to see the map and here for a brief overview of methodology.
Emergency Call Boxes and Campus Safety on the UT Dallas Campus
Emergency call boxes boost safety by deterring crime and enabling rapid emergency response. UT Dallas should keep pace with campus construction and student body growth by installing new call boxes in strategic locations. This paper uses a viewshed analysis to propose the best places for UT Dallas to install future call boxes. Click here to see.
This project won first prize at a university GIS poster competition (November 2016). It used a simple land cover classification to estimate the population of Midland County, Texas. It combined work in ERDAS Imagine, ArcMap, and R. Overall, a linear regression model estimated the population within 0.425% of the actual value, while a spatial autoregressive model underestimated the population by 1.939%. Click here for a PDF of the poster.
When one studies racial and religious bias crime in the U.S., the differences between cities are stark: many cities report zero bias crimes, while a handful report hundreds each year. Why the disparity? This study employed a generalized estimating equation (GEE) model to make sense of the broad spatial and temporal differences in bias crime throughout 72 U.S. Combined Statistical Areas (CSAs) from 2006-2014.Click here for a PDF of the study.
Programming - Python
This project empowers users to access common-sense, credible, and easy-to-understand information about urban areas in the United States. Using Python programming and ArcGIS, the program generates choropleth maps, time series graphs, and basic statistical summaries on demand. All users have to do is input their geographical area and theme of interest. Click here for a PDF of the poster.
Published in Greater Greater Washington. The neighborhood you call home has the potential to help your economic mobility and your health and well-being. That’s why it’s important to create more chances for families with low incomes to live in areas that are close to jobs and transit, with low poverty and crime, and high-performing schools.
The World Economic Forum Water Initiative predicts "a 40% shortfall between water demand and available freshwater supply by 2030." This is a survey of the forces increasing global water demand, future stakes, and approaches to development and conservation. View here.