Suchergebnisse

In this study, we empirically model the interactions between 2D and 3D geospatial information and both daytime and nighttime urban heat islands, and estimate the relative importance of various urban heat islands drivers. While previous studies have explored the relationship between the urban heat islands and 2D urban features, the interactions with 3D urban features and neighboring surface characteristics have not been adequately explored. This paper specifies the impacts of these urban features on the urban heat islands intensity during daytime and nighttime, which tend to be quite different. The empirical evidence from this study suggests that while vegetation is the dominant factor for urban heat islands intensity during daytime, the urban canyon has stronger impacts on the urban heat islands than vegetation at night. In addition, adjacent surfaces are more likely to influence nighttime surface temperatures. These results could be used to develop urban design solutions for mitigating the urban heat islands.

Fracking is used in the extraction of crude oil and natural gas from deep seated sedimentary rocks. The ubiquitous use of heavy trucks in fracking leads to traffic congestion and damages to the existing infrastructure in energy producing corridors. This makes driving hazardous for drivers of both commodity and passenger carriers, leading to traffic crashes near fracking sites. In this exploratory study, the case of Eagle Ford Shale of Texas has been analyzed to determine the impacts if any, of the variables of energy production, truck vehicle miles traveled, and other socio-economic factors on traffic crashes. Using both descriptive and statistical analyses of data, it has been found that some of the aforementioned variables have an impact on traffic crashes in the energy producing corridor. Based on the study's findings, appropriate recommendations to reduce traffic crashes in this energy corridor have been made.

Particulate matter (PM) 2.5 generates a variety of negative effects on health, such as heart and lung disease, asthma, and respiratory symptoms. The pollutants in the atmosphere primarily result from human activities, and, in urban settings, increases in traffic volume and higher building density can elevate the level of PM2.5. Building on previous research, this study primarily focuses on two highly developed urban areas in the Texas Triangle region: Travis County in the Austin Metropolitan Area and Harris County in the Greater Houston Area. It explores different types of urban features, such as urban structures, land use/land cover, traffic volume, and distance from roads, that affect the PM2.5 concentration in urban environments at the local scale. Throughout this study, we use various research methods, including geographically weighted regression, to estimate the PM2.5 concentrations at local scales, 3D city models to derive urban characteristics, and the random forest algorithm to predict the effects of urban features on PM2.5 concentrations. Our findings suggest that developed land use, tall buildings in dense areas, and major traffic networks are the key contributors to PM2.5. However, we also find that tree canopy cover can significantly reduce PM2.5 concentrations.