Food is of great importance to daily life. Food stores and supermarkets are the key places to get food for both the urban and rural populations. This study presents the accessibility of urban and rural food stores in Västerbotten County. A GIS-based analysis created service areas around the food stores using the road network in Västerbotten. These service areas were created for two different forms of transport, driving and public transport. The public transport service areas made us of the GTFS tool within ArcGIS pro. The population within and not within these service areas were counted as having access and not having access to the food stores in the time cost model. Compared to the urban population, the rural population has less access to the food stores in both the driving and public transport service areas. For both the urban and rural populations, accessibility with the car is higher than when taking public transport options.

Until recently, transit data lacked a common data format that could be used to share and integrate information among multiple agencies. In 2005, however, Google worked with Tri-Met in Oregon to create the General Transit Feed Specification (GTFS), an open data format now used by all transit agencies that participate in Google Maps. GTFS feeds contain data for scheduled transit service including stop and route locations, schedules and fare information. The broad adoption of GTFS by transit agencies has made it a de facto standard. Those agencies using it are able to participate in a host of traveler services designed for GTFS, most notably transit trip planners. Still, analysts have not widely used GTFS as a data source for transit planning because of the newness of the technology. The objectives of this project are to demonstrate that GTFS feeds are an efficient data source for calculating key transit service metrics and to evaluate the validity of GTFS feeds as a data source. To demonstrate GTFS feeds’ analytic potential, the author created a tool called GTFS Reader, which imports GTFS feeds into a database using open-source products. GTFS Reader also includes a series of queries that calculate metrics like headways, route lengths and stop-spacing. To evaluate the validity of GTFS feeds, annual vehicle revenue miles and hours from the National Transit Database (NTD) are compared to the calculated values from agencies whose GTFS feeds are available. The key finding of this work is that well-formed GTFS feeds are an accurate representation of transit networks and that the method of aggregation presented in this research can be used to effectively and efficiently calculate metrics for transit agencies. The daily aggregation method is more accurate than the weekly aggregation method, both introduced in this thesis, but practical limitations on processing time favor the weekly method. The reliability of GTFS feed data for smaller agencies is less conclusive than that of larger agencies because of discrepancies found in smaller agencies when their GTFS-generated metrics were compared to those in the NTD. This research will be of particular interest to transit and policy analysts, researchers and transit planners.