The growing interest on combining spatial data and time-varying transit data sets provides an opportunities for precise assessment of spatial disparity in mobility services and settlement structures. Previous research shows potential to use standards open data such as General Transit Feed Specification (GTFS) data with the most up-to-date trip schedules for small scale spatial analysis and visualization in relation to functional settlement structure. However, there are several challenges in data preparation, harmonization, analysis and other uncertainties due to the lack of cross-border route information in the border area or the different time references even to in case of a single transport service area (Sikder et al., 2020).

Specific Tasks:

• A systematic literature review on open mobility data for spatial disparity and settlement structure research in German and international context
• Data extraction use source API: https://gtfs.de/de/feeds
• Development of an reproducible workflow/tool for qualifying spatial-temporal indicator and dynamic visualization
• Perform sensitivity/uncertainty analysis and test the workflow/tool with multiple input parameters

Expected Output:

• State of art in using open mobility data for spatial disparity
• Potential application of open data platforms for analysis of public sector mobility services
• Assessment of the potentials for analysis of spatial disparities in relation to land use and settlement structure
• Prototype toolbox for extraction, assessment and visualization of multidimensional dataset
• A written master thesis

Key Requirements:
Familiar with open data platforms and willingness to explore on data extraction workflow using GIS environments. Some knowledge on scripting and statistical languages like R, SQL, Python (ArcPy) as well as good English skills for review of international literature.

Supervisors:
Prof. Dirk Burghardt (TUD), Dr. Sujit Sikder (IOR)

Contact at IÖR:
Dr. Sujit Sikder, Tel: +49-0351/4679-273, E-Mail: s.sikder@ioer.de