The college town of State College, PA, is home to The Pennsylvania State University (PSU) and its many facilities. Our research interest was in understanding the influence of the newly developed Arboretum at Penn State (APSU) on nearby housing values in State College over time. Current sales transaction data were gathered and a pooled crosssectional regression analysis approach utilized. Contrary to the literature, our findings suggested proximity to the APSU as well as three other nearby open spaces had no significant influence on the value of homes nearest it. Further, proximity to PSU's main campus was negatively associated with housing values. Neither of these patterns varied over time. To further explore these results, the study area was expanded beyond the neighborhoods most proximate to the APSU to the balance of the borough. These results replicated the earlier findings, confirming that living close to PSU's campus was negatively associated with housing values community-wide. Practically, these findings disconfirm the common assumption that the State College market places a premium on proximity to the town's major employment center (PSU campus) and a significant landmark (APSU). The findings suggest that housing markets in similar college towns would likely not reflect typical residential areas and may require alternative evaluation considerations that accounts for regional housing and land cover trends. Highlights We modeled the influences of land use and sociodemographic factors on residential property value in a college town. Unexpectedly, proximity to open space and a community landmark (an arboretum) do not significantly influence residential value. Also unexpectedly, proximity to the college campus decreases residential value. The results of the model are consistent at a second expanded (borough-wide) study area. These findings are contrary to urban real estate evaluation literature and suggest that college towns, especially in rural areas, require a unique approach.
Through the lens of ecologically based planning and design decisions for a renewable energy infrastructure, our project investigates a pilot method that assesses ecological, geographic, and sociopolitical opportunities and constraints. This method couples an application of the University of Pennsylvania Suitability Analysis Method, more commonly known as the McHarg Method, and a statistical analysis of the Appalachian Mountain Region of Pennsylvania in the United States. Despite the region's high-quality natural resources, persistent reliance on coal industries has resulted in disadvantaged socioeconomic distress and risk. By unraveling linkages between socio-ecological systems and governance actions, the results of our pilot described challenges for the Appalachian Mountain Region in transitioning to a renewable energy infrastructure, while also formulating the basis for county-level strategies that may encourage the pro-environmental governance necessary to promote renewable energy initiatives. We find that Appalachian counties' relatively low levels of infrastructure density, solar irradiation, population growth, limited access to education centers, and high-quality forests present challenges to allocating suitable areas for solar infrastructure. However, clusters of moderately suitable areas are identifiable throughout the region. Yet such opportunities may struggle to support solar energy initiatives as the region suffers from limited pro-environmental governance, particularly in areas with low-density infrastructure and historically higher levels of dependence on natural resource industries. Above all, our findings identify that the relationship between socio-ecological conditions and pro-environmental governance is complex and often in conflict in key areas of the region.
Although collective action is needed to address many environmental challenges, it cannot proceed in the absence of collective identity. The current study sought to address the question of whether or not a collective identity exists among residents of the Chesapeake Bay Watershed and, if so, what it might look like. The raw data were news stories drawn from local papers published in municipalities located at the headwaters of the Susquehanna River, midway down the Susquehanna, and where the river meets the bay. Computerized content analysis assessed the frequency with which the Chesapeake Bay and watershed were mentioned alongside a set of keywords thought to represent different facets of identity (e.g, agriculture, fishing, swimming). The results showed substantial variation in frequency across time and place, but, low absolute levels of coverage of the bay and the watershed. Multidimensional scaling revealed different structures to collective identity as a function of place. These differences in content may be attributable to varying demographic and environmental characteristics. Proximity to the bay may partially explain some of these differences, but, to the extent that a collective watershed identity exists at all, it is complex and heterogeneous.
Although collective action is needed to address many environmental challenges, it cannot proceed in the absence of collective identity. The current study sought to address the question of whether or not a collective identity exists among residents of the Chesapeake Bay Watershed and, if so, what it might look like. The raw data were news stories drawn from local papers published in municipalities located at the headwaters of the Susquehanna River, midway down the Susquehanna, and where the river meets the bay. Computerized content analysis assessed the frequency with which the Chesapeake Bay and watershed were mentioned alongside a set of keywords thought to represent different facets of identity (e.g, agriculture, shing, swimming). The results showed substantial variation in frequency across time and place, but, low absolute levels of coverage of the bay and the watershed. Multidimensional scaling revealed different structures to collective identity as a function of place. These differences in content may be attributable to varying demographic and environmental characteristics. Proximity to the bay may partially explain some of these differences, but, to the extent that a collective watershed identity exists at all, it is complex and heterogeneous.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.