Hedonic pricing (HP) is an economic technique for placing monetary values upon costs or benefits which do not have market prices. This thesis applies the HP method to the valuation of road transport and visual disamenity impacts, as reflected in variations within property prices. In order to carry out such a study one has to determine not only the magnitude of the environmental impact at each property, but also structural, neighbourhood and accessibility variables characterising each property. These have to be controlled for before the portion of the property price attributable to the environmental variable can be observed. In the past all these variables have been calculated using labour intensive techniques such as house to house surveys. These led to high study costs and limited the scope of such research. This thesis circumvents these problems through the use of large scale digital data and a Geographical Information System (GIS). This study demonstrates how a GIS can significantly improve a HP study through the calculation of a wider range of more sophisticated variables. However the calculation of such a large number of variables causes difficulties when these data are modelled. This study illustrates how these problems can be overcome through a combination of Principal Components Analysis and a Multiple Regression. The final model had a higher degree of explanation and a lower incidence of collinearity than in previous research vindicating the use of GIS. Prices and values for a range of road transport and visual disamenity impacts are presented. The main limitations upon the research was the time and effort required to obtain data and to convert them into a GIS format. This took half of the research time. Various developments that might improve this situation in the future are presented, along with ways in which the study could be extended.

Road construction and maintenance throughout the country continues to be one of the largest contributors of sediment pollution to aquatic systems. Though impacts of road networks on aquatic systems can be potentially severe, little work has been performed to evaluate the effect that road spatial location within a watershed has on water quality. To address this issue from a quantitative perspective, a "Road Impact Factor" protocol was designed to identify potential erosion-prone segments of road networks based on road gradient, spatial location based on hydrologic flow length, surface composition, and water control installations. The protocol was developed for two regions in Central Idaho and Eastern Oregon. We then used the hydrologic travel time procedure, developed for use in the Hydrologic Engineering Center Hydrologic Modeling System (HEC-HMS) runoff and routing model, in order to characterize the spatial distribution of potential road runoff impacts within the study areas. Ten macroinvertebrate metrics sensitive to sedimentation (i.e. % Intolerant Taxa, Hilsenhoff Biotic Index, etc.) were analyzed to test the significance of the spatial distribution of Road Impact Factors. These 10 metrics were analyzed under the hypothesis that values will be lower for those study areas that have a higher degree of road impact and a lower distance between the road segments and stream reaches. Results of a quadrant analysis and hierarchical clustering analysis showed hypothesized trends for several metrics in Idaho, though the trends were not strong. No trends were observed in Oregon. The variability in results is likely due to limitations of the input datasets. / Master of Science

Habitat fragmentation and destruction caused by development of infrastructure such as roads threaten biodiversity. Roads act as barriers by impeding animal movements and restricting space use. Understanding factors that influence barrier effects is important to discern the impacts of habitat fragmentation and to develop appropriate mitigations. We combined telemetry and demographic data in 2008 to 2012 with remote sensing imagery to investigate barrier effects of forest roads and assess effects of traffic, road edges, and canopy gaps on space use of an endangered, endemic forest obligate, the Mt. Graham red squirrel (Tamiasciurus hudsonicus grahamensis). We mapped low to high traffic roads, road edges, canopy gaps, and random lines in forests to serve as references. We determined if red squirrels included these linear features in their total and core home ranges, and used this metric as an indicator of crossing and preference for habitat adjacent to the linear features. Forest roads acted as barriers regardless of traffic volume and had long-term impacts on animal space use. Animals did not avoid entering roadside areas, and probability of crossing linear features in the forest was not affected by distance to roads. In contrast, greater canopy cover increased probability of crossing, and gaps in canopy impeded animal movements. Higher likelihood of road crossing was associated with more variable tree height and mating activity. We demonstrated that narrow forest roads with low traffic volume were barriers for forest dependent species, and suggest that gap avoidance inhibits road crossings. (C) 2016 Published by Elsevier Ltd.

In a time when the concept of sustainability is gaining increasing attention among the public, as well as among stake holders and policy makers, informing people about what the most sustainable choice to make is, is crucial in leading people in the right direction.  Travelling is an activity requiring a traveller to make multiple choices, with one of the choices being which route between two places to take. The transport sector is also a strong contributing cause to global issues such as climate change, wherefore choices made in relation to transportation are highly relevant in regard to sustainable development.  Up until today, most traffic information systems for passenger car users, only provide travellers with suggestions about the fastest, or the shortest, route option. This study aims at proposing a modelling structure using GIS software, that could also return the most sustainable route alternative.  The complexity of the many spatial impacts of road transportation is thoroughly discussed in the literature review, together with dilemmas regarding route choice behaviours. A proposed modelling structure is presented, with the structure also empirically being examined as a “proof of concept”. The empirical work takes place in the urban area of Hörnefors, Sweden, and findings confirm the applicability of the proposed workflow.  In the specific case of Hörnefors, three distinct route options are investigated, in relation to four sustainability impact variables. The variables investigated are fuel consumption, air pollution, noise, and safety. Results show that the, by far, longest route, is in fact returned as the most sustainable route option. The other two route options exhibit impacts of around double the amount of impacts yielded by the most sustainable one. The generalised sustainability cost is significantly mostly determined by the air pollution variable, due to its far-reaching spatial dispersion patterns yielding impacts even at long distances from a road.  The potential application of the inclusion of sustainability in traffic information systems are additionally reviewed, according to the behavioural mechanisms mentioned in the literature 4review. Estimations of in what contexts “most sustainable route” suggestions are potentially most likely to yield behavioural changes, are also made, and assessed. Conclusions suggest that an inclusion of “most sustainable route option” modelling into travel information systems, have the highest potential to affect route choices when the user is driving at locations previously unvisited, due to the inexistence of a status quo route in such contexts.