It is well established that national retail chains impact small, single location retail businesses in terms of revenue generation, retail structure, retail type diversity, and location. This study examines the retail structure and diversity of five retail districts in the City of Denton, Texas. The analysis focuses on one central business district (CBD), one traditional retail strip center (University Drive, also known as US HWY 380), one special retail district (Fry Street District), one traditional enclosed shopping mall and associated development (Golden Triangle Mall), and one power retail center (Denton Crossing). The empirical foundation for the investigation is a historical business database covering years 1997 to 2010, obtained from Info Group's Reference USA. This Reference USA database includes location, industry, and status (single versus chain location) information for each business. Retail diversity and evenness were measured for each of the five retail districts using the Simpson's Diversity Index and the Simpsons Measure of Evenness, leading to specification of the differences that exist in retail structure and diversity among the districts. Golden Triangle Mall and Denton Crossing were primarily chain location in composition while Fry Street District, the CBD, and University Drive were primarily single location in composition. Across all years, …

In 2006, the United States Congress passed the Pandemic All-Hazards Preparedness Act (PAHPA) which mandated that all emergency preparedness planning shall address at-risk populations. Further, in 2013, the reauthorization of this act, known as PAHPRA, defined at-risk individuals as "children, older adults, pregnant women, and individuals who may need additional response assistance." This vague definition leaves emergency managers, planners, and public health officials with the difficult task of understanding what it means to be at-risk. Further, once identified, the geographic location of at-risk individuals must be obtained. This research first uses the concept of social vulnerability to enhance the understanding of what it means to be "at-risk." Then, by comparing two data disaggregation techniques, areal weighted interpolation and dasymetric mapping, I demonstrate how error of estimation is affected by different scenarios of population distribution and service area overlap. The results extend an existing framework of vulnerability by stratifying factors into quantifiable and subjective types. Also, dasymetric mapping was shown to be a superior technique of data disaggregation compared to areal weighted interpolation. However, the difference in error estimates is low, 5 percent or less in 72 percent of the test cases. Only through local collaboration with community entities can emergency …