1995 map of East Tennessee State University's VA Campus. Created 5/30/1995 by Johnson City GIS. Buildings can be identified using the building index on the left side of map. Parking info and the parking lot legend can be found on the bottom half. Some buildings are shaded using a colored pencil at an indeterminate time post publication. Physical copy resides with Johnson City, Geographic Information Systems Division. No scale is included. / https://dc.etsu.edu/rare-maps/1051/thumbnail.jpg

2005 map of East Tennessee State University's VA Campus. Created 12/9/2005 by Johnson City GIS. Buildings can be identified using the building index on the left side of map. Different types of buildings are denoted using a color scheme. Parking info and the parking lot legend can be found in the top left quadrant. Hydrants and related items are also included. The map is dated by a handwritten date in black ink in the bottom left corner. Physical copy resides with Johnson City, Geographic Information Systems Division. No scale is included. / https://dc.etsu.edu/rare-maps/1052/thumbnail.jpg

2013 map of East Tennessee State University's VA Campus. Created 12/4/2013 by Johnson City GIS. Buildings can be identified using the building index on the left side of map. Parking info and the parking lot legend can be found on the bottom right corner. Fire suppression system info is also included. Physical copy resides with Johnson City, Geographic Information Systems Division. No scale is included. / https://dc.etsu.edu/rare-maps/1053/thumbnail.jpg

General highway map for Washington County, Tennessee created August 4, 2010 by Johnson City GIS. Map features, the transportation key, and place/neighborhood names can be found in the lower right corner. A county road index which lists county roads alphabetically can be found along the left edge. Physical copy resides with Johnson City, Geographic Information Systems Division. Scale - 1" = 4700' / https://dc.etsu.edu/rare-maps/1069/thumbnail.jpg

NASCAR has become one of America's fastest growing spectator sports, and corporate sponsors have played an important part in this upsurge in popularity. Race teams, drivers, and sanctioning bodies use the income that sponsors provide to operate at NASCAR events. This study provides an analysis of how corporate sponsorships have changed the way that NASCAR is presented in print journalism. Using Burke's method of indexing, NASCAR-related titles in the New York Times and the Johnson City Press from 1950 to present day are analyzed. The analysis reveals not only a steady increase in the number of NASCAR-related titles, but 4 indices of meaning that are most often used (Specific Races/Locations, NASCAR, Specific Names, and Sponsors) and that organizations should consider before they plan to promote their products using NASCAR.

Improving Sinkhole Mapping Using LiDAR Data and Assessing Road Infrastructure at Risk in Johnson City, TN. Kingsley Fasesin1, Dr. Ingrid Luffman 1, Dr. Eileen Ernenwein 1 and Dr. Arpita Nandi1 1 Department of Geosciences, College of Arts and Sciences, East Tennessee State University, Johnson City, TN; Abstract Predicting infrastructure damage and economic impact of sinkholes along roadways requires mapping of sinkhole distribution and development of a model to predict future occurrences with high accuracy. The study is carried out to define the distribution of sinkholes in Johnson City, TN and risks they pose to roads in the city. The study made use of a 2.5 ft Digital Elevation Model (DEM) derived from Light Detection and Ranging (LiDAR) data acquired from Tennessee Geospatial clearing house (TNGIS) and an inventory of known sinkholes identified from topographic maps. Depressions were identified using the LiDAR-derived DEM by subtracting a filled-depressions DEM from the original study area DEM. Using a spatial join, mapped sinkholes were matched to depression polygons identified from the LiDAR-derived DEM. For all matched sinkhole-polygon pairs, three indices were calculated: circularity index, area ratio of minimum bounding rectangle, and proximity to train tracks and roads. The dataset was partitioned into training (70%) and validation (30%) subsets, and using the training dataset, thresholds for each index were selected using typical values for known sinkholes. These rules were calibrated using the 30% validation subset, and applied as filters to the remaining unmatched depression polygons to identify likely sinkholes. A portion of these suspected sinkholes were field checked. The future direction of this research is to generate a sinkhole formation model for the study area by examining the relationship between the mapped sinkhole distribution, and previously identified sinkhole formation risk factors. These factors include: proximity to fault lines, groundwater and streams; depth to bedrock; and soil and land cover type. Spatial Logistic Regression analysis will be used for model development, and results will be used to generate a sinkhole susceptibility map which will be overlain on the road network to identify the portions of interstate and state highways at risk of sinkhole destruction.

The Johnson City Community Health Center is one of over 1200 community health centers serving over 22 million patients across the United States. Community health centers primarily serve patients with low income or without health insurance, but most serve all the members of their communities. These centers provide many services and treat health problems in a holistic manner in order to improve the health of their communities and also allow the members of those communities to progress. The Johnson City Community Health Center is compared to successful CHCs from across the nation to determine if it has characteristics to be successful in this community. A SWOT Analysis is conducted by evaluating the Marketing Mix, or the Product, Price, Placement, and Promotion, of the center and also by examining the Political, Economic, Social, and Technological environments it operates in. This research determines the internal Strengths and Weaknesses and external Opportunities and Threats of the Johnson City Community Health Center and concludes that it does have the characteristics needed to be successful in the community. This research can be used by center management to improve services, but it can also be used by other researchers to continue evaluations of community health centers across the nation.