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Abstract This study evaluates the accessibility impact of future high speed rail (HSR) corridor on the Piedmont Atlantic Megaregion (PAM) in the United States. A geographic information system (GIS) tool is used to conduct the accessibility assessment. The door-to-door approach is adopted to evaluate the multimodal (including roadways and HSR) travel time. Three accessibility indicators are selected, including the weighted average travel time (WATT), daily accessibility (DA), and potential accessibility (PA). The selected accessibility indicators are calculated by using the estimated travel time at the geographical level. The average accessibility scores of the counties in the PAM during peak and off-peak hours are estimated and compared. The results indicate that the building of the HSR corridor within the PAM will improve the accessibility at the megaregional level. However, the coefficient of variation results indicate that the inequality will also increase due to the new HSR corridor. The relationships between megaregional accessibility scores (i.e., WATT) and HSR services (such as headway and speed) are explored. Several policy implications are drawn in terms of enhancing the megaregional accessibility. Highlights • The accessibility impact of high speed rail (HSR) on the Piedmont Atlantic Megaregion (PAM) is evaluated. • A door-to-door approach is adopted to estimate travel time. • Accessibility scores of the future HSR corridor during peak and off-peak hours are estimated and compared. • Policy implications on the future HSR project in terms of enhancing megaregional accessibility in the PAM are drawn. [ABSTRACT FROM AUTHOR]

In the past 20 years, considerable progress has been made to improve urban air quality in the EU. However, road traffic still contributes considerably to the deterioration of urban air quality to below standards, which requires a method to measure properly and model pollution levels resulting from road traffic. In order to visualize the geographical distribution of pollution concentration realistically, we applied the Land Use Regression (LUR) model to the urban area of Gothenburg. The NO 2 concentration was already obtained by 25 samplers through the urban area during 7-20 May, 2001. Predictive variables such as altitude, density, roads types, traffic and land use were estimated by geographic information system in buffers ranging 50 to 500 m-radii. Linear regression (α=5%) between NO 2 and every predictive variable was calculated, and the most robust variables and without collinearity variables were selected to the multivariate regression model. The final formula was applied using Kriging in a grid map to estimate NO 2 levels. The average of measurements was 23.5 μg/m 3 (± 6.8 μg/m 3 ) and 180 predictive variables were obtained. The final model explained 59.4% of the variance of NO 2 concentration with presence of altitude and sum of traffic within 150 m around the sampler sites as predictor variables. The correlation measured versus predicted levels of NO 2 was r = 0.77 (p < 0.001). These results highlight the contribution of traffic in air pollution concentration, although the model is not precise in regions outside the urban area (e.g. islands and rural area). Moreover, future analyses should include meteorological data to improve the LUR modelling. [ABSTRACT FROM AUTHOR]

The evolution of GIS-T is characterized in three stages: the map view, the navigational view, and the behavioral view. The static nature of the map view favors applications related to inventory and description, and raises difficult questions of accuracy and interoperability. The navigational view adds concerns for connectivity and planarity, and the storage of time-dependent attributes. Navigation also raises issues of representation related to scale, including the need for lane-level connectivity. The behavioral view stems from the work of Hägerstrand, treating transportation events as dynamic and occurring within the largely static transportation space. Appropriate representations for the behavioral view have still to be worked out. In all three cases the legacies of prior technologies and perspectives are still evident. The paper presents a series of research challenges, dealing with standards, representation, unambiguous communication, economic models, response to new technologies, and application of knowledge gained from GIS-T and ITS research to other fields. [ABSTRACT FROM AUTHOR]