2021/10/05 by Robert Jeansoulin, Jeansoulin, Robert
Economics, Econometrics and Finance · Engineering · Social Sciences · #Artificial Intelligence (cs.AI) #Aviation Industry Analysis and Trends #Computer Vision and Pattern Recognition (cs.CV) #Databases (cs.DB) #Diverse Cultural and Historical Studies #FOS: Computer and information sciences #FOS: Physical sciences #French Urban and Social Studies #Physics and Society (physics.soc-ph) #Railway Systems and Energy Efficiency
paper · pdf · doi:10.48550/arxiv.2111.03433
openalex publication_date 2021/10/05 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
The reconstruction of geographical data over a century, allows to figuring out the evolution of the French railway landscape, and how it has been impacted by major events (eg.: WWII), or longer time span processes : industry outsourcing, metropolization, public transport policies or absence of them. This work is resulting from the fusion of several public geographical data (SNCF, IGN), enriched with the computer-assisted addition of multiple data gathered on the Internet (Wikipedia, volunteer geographic information). The dataset compounds almost every rail stations (even simple stops) and railway branch nodes, whose link to their respective rail lines allows to build the underlying consistent graph of the network. Every rail line has a "valid to" date (or approx) so that time evolution can be displayed. The present progress of that reconstruction sums up to roughly 90% of what is expected (exact total unknown). This allows to consider temporal demographic analysis (how many cities and towns served by the railway since 1925 up on today), and environmental simulations as well (CO2 cost by given destination ).