摘要：AbstractA public transit system consists of various components in which all must be considered together in order to develop an efficient and sustainable transit network. Providing convenient access to public transit enhances the service performance, reliability and will also result in higher public usage. Conventionally transit stop locations and spacing are determined based on aggregate measures of population density on a zonal basis using simple buffer analysis. This method has been criticized as inaccurate, as the population is rarely uniformly distributed over zones. In this research, transit stop access coverage is estimated using building geometric information accurately extracted from the LiDAR data collected in the City of Fredericton, Canada. LiDAR data is mostly used for flood hazard studies but can also be used for other purposes such as 3D building modeling. Through this approach building floorspace information and therefore a much more accurate measurement of transit stop coverage based on the building floorspace is obtained at disaggregate spatial level and compared with the conventional buffer-density approach through a real example in the City of Fredericton. Overall, it is found that this approach can provide transit planners with much more improved building and population distribution information at a very precise spatial level, in order to set the transit stops at their optimal locations.
