Journal of Urban Planning and Development

This analysis examines the historical relationship between land-use changes and the location of capacity-increasing highway projects in Oregon from 1970 to 1990. Aerial photography for 15 cities was used to delineate the extent of urban development for the 20-year time period. A geographic information system was used to assemble these data. A logit regression model tested the significance of geographic variables such as proximity to highway projects, land-use zoning classification, city size, and other spatial characteristics. The results suggest that for the 15 selected cities, the spatial measures performed well in predicting the location of urban development from 1970 to 1990. In addition, the results of the logit regression model indicated that, controlling for other location factors, urban development impacts near state highway project corridors have produced a significant gradient of land-use change compared to the gradient for all highway facilities.

The latest Clean Air Act Amendments mandate that every area in the nation meet standards for six criteria pollutants—ozone, sulfur dioxide, carbon monoxide, nitrogen dioxide, lead, and particulate matter—both with an aerodynamic diameter less than 10 μm $\left({\mathrm{PM}}_{10}\right)$ and with an aerodynamic diameter less than 2.5 μm $\left({\mathrm{PM}}_{2.5}\right)\text{.}$ Regions in nonattainment of these standards must produce an emission inventory for the violating pollutant. By both California and federal air quality standards, all counties in the San Joaquin Valley (SJV) air basin were ${\mathrm{PM}}_{10}$ nonattainment areas in 2001. Reentrained dust created by vehicles is considered a large contributor to ${\mathrm{PM}}_{10}$ emissions in the SJV. However, current methods used to estimate ${\mathrm{PM}}_{10}$ emissions from vehicle activity on unpaved roads do not account for spatial or seasonal variability. Using statistical models and GIS, we introduce a new framework for estimating vehicle miles traveled on unpaved roads. Because a large portion of the SJV contains agricultural land, our models distinguish between vehicular traffic on unpaved roads associated with harvest and nonharvest activities. Using the method on counties in the SJV, we find that the new methodology results in approximately 29% less vehicle miles traveled on unpaved roads in San Joaquin County than calculated by the current California Air Resources Board (CARB) method, and approximately 40% less vehicle miles traveled in Fresno County. Furthermore, the results indicate that integrating GIS methods in ${\mathrm{PM}}_{10}$ inventory procedures greatly enhanced the overall process of model development and estimation.

This work analyzes certain influences of climatological variables on the city, as well as the main interactions between green spaces and the environmental parameters that form the urban environment. Several comfort indices were used in different parts of the eight districts most representative of the urban complex. The formulation of these indices was statistically correlated with the green zone areas, in order to find out the surface area of these areas that the city should have in order for this to be considered theoretically comfortable. The scenario for the study was in all cases the city of Valencia, Spain, taken as a prototype of the Mediterranean city.

The redevelopment of former industrial sites can have positive impacts on the environment, economic development, and quality of life in a given community. The federal brownfields initiative of the 1990s was intended to encourage environmental remediation of properties that are typically less contaminated than Superfund sites. Additionally, states have adopted programs that limit environmental liability and allow for risk-based cleanup standards, both of which should encourage a would-be investor or developer. Based on the statistical analysis of data collected from two nationwide surveys, this research shows that factors other than environmental concerns can impact the successful redevelopment of a brownfield. Analyses of the data using descriptive statistics, exploratory data analysis, factor analysis, and hypothesis testing indicate that the following are also influential factors: time to occupancy, total development costs, community support, proposed land use, condition of the local infrastructure, willingness of lending institutions to participate in the financing, support of local politicians, availability of financial incentives, and number of jobs to be created. These results support the idea that successful brownfield development cannot be accomplished by simply addressing the environmental issues.

Brownfield development can be a “win-win” situation for the majority of the stakeholders that have an interest in the near- and long-term use of a currently unrealized asset. Further, brownfield development is a complex and time-consuming problem, only part of which is related to environmental concerns. Whereas there seems to be a flurry of brownfield development, both nationally and internationally, tools are lacking that can help to support complex decision making and ultimately expedite site remediation and development. In this research, we have collected data from 75 brownfields in the United States, analyzed the data to be able to distinguish “successful” from “not-so-successful” sites, and developed a logit model that may be used to estimate the probability of development outcomes. Much of the brownfield literature focuses on anecdote and qualitative descriptions of experiences. Therefore this research, which is based on empirical analyses, contributes to the literature by proposing a predictive model that may support rational decision making. Additionally, this research provides recommendations for application and improvement of the model.