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UID:pretalx-foss4g-2026-KS97DK@talks.osgeo.org
DTSTART;TZID=JST:20260901T173000
DTEND;TZID=JST:20260901T180000
DESCRIPTION:This study calculated the travel times to medical institutions 
 in a regional city in Japan using GTFS (General Transit Feed Specification
 ) data to enable a more precise geographic accessibility assessment. It fo
 cuses on comparing and validating tools that utilize open data and FOSS4G 
 (Free and Open Source Software for Geospatial). This study reviews previou
 s studies and evaluates GTFS-based route search services\, including FOSS4
 G tools. Based on this review\, we developed a QGIS plugin to facilitate p
 articipation not only by researchers\, but also by practitioners and polic
 ymakers.\n\nAccording to Park (2021)\, the emergence of sophisticated tran
 sportation databases\, such as GTFS\, enables the estimation of travel tim
 es across different transportation modes (e.g.\, public transit and privat
 e automobiles)\, as well as dynamic travel times under time-variant traffi
 c conditions. The increased availability of dynamic mobility data has ther
 efore facilitated the implementation of time-sensitive accessibility measu
 res.\n\nIn Japan\, Tanimoto (2020) pointed out that discussions on the sel
 ection of analytical methods for accessibility analysis remain insufficien
 t in two respects. First\, there has been insufficient discussion on metho
 d selection that considers the difficulty and cost of acquiring\, preparin
 g\, and manipulating data for analysis. Second\, there has been insufficie
 nt discussion on the effectiveness of the tools in relation to the subject
  of analysis. Sekine (2018) also highlighted the difficulty of creating ge
 ospatial data for intermodal travel chains\, although this study was publi
 shed before the emergence of GTFS data.\n\nWithin Japanese geography\, the
  only previous study utilizing GTFS data is Kasahara et al. (2021)\, who a
 nalyzed the spatiotemporal patterns of delay times using Sendai City Bus t
 imetable data. Given the absence of GTFS-based accessibility studies in Ja
 panese geography\,. Furthermore\, while attempts have been made to compare
  tools enabling GTFS-based route search services (e.g.\, Higgins et al.\, 
 2021)\, these studies primarily verified correlations between numerical ou
 tputs across tools\, rather than validating results in terms of shortest r
 outes or route correctness. In this study\, we evaluated the tools in term
 s of runtime\, agreement in travel time estimates\, and route validity (e.
 g.\, rule violations in GTFS).\n\nWe compared and evaluated three tools\, 
 ArcGIS\, OpenTripPlanner (OTP)\, and R5\, capable of measuring the shortes
 t paths using GTFS. OTP and R5 are FOSS4G tools\, whereas ArcGIS is a prop
 rietary software. To examine accessibility challenges in regional cities i
 n Japan\, we selected the area around Yamagata City as a case study. Altho
 ugh the study area has an intricate network of railway and bus routes\, au
 tomobile dependence remains high\; therefore\, improving public transport 
 services is an important local challenge. Using each tool\, we measured th
 e shortest path travel times to medical institutions and compared and vali
 dated the results.\n\nIn our evaluation\, approximately one million origin
 –destination (OD) pairs were generated and analyzed using each tool in t
 he same computing environment. ArcGIS required approximately 10 min to cal
 culate one million OD pairs\, OTP required over 60 min\, and R5 required a
 pproximately 5 seconds. These figures are broadly similar to those reporte
 d by Higgins et al. (2021)\, confirming R5’s substantial speed advantage
 .\n\nFor R5 and OTP\, the distribution of travel times per OD pair was nea
 rly identical\, with 93.2% falling within a 5-minute difference. By contra
 st\, ArcGIS had a match rate of less than 50%. Furthermore\, the cases in 
 which only ArcGIS derived the shortest path were limited to paths that vio
 lated operational rules\, such as boarding at a GTFS-registered stop desig
 nated for drop-off. R5 and OTP search for the shortest path at each depart
 ure time\, whereas ArcGIS first determines the single shortest path and th
 en checks whether a journey exists at that departure time along that path.
  Consequently\, ArcGIS has difficulty in producing accurate results for OD
  pairs with multiple feasible routes or stops.\n\nOTP and R5 travel time e
 stimates matched those from a popular Japanese route search service in app
 roximately 70% of cases\, calculated shorter travel times in approximately
  25% of cases\, and produced longer travel times for the remaining 5%. Mos
 t discrepancies were due to different definitions of walking distance to s
 tops\, and the differences were within an acceptable margin (often within 
 ±3 minutes).\n\nAlthough OTP and R5 produced accurate results in most cas
 es\, travel times differed by more than five minutes in 6.8% of cases. Mos
 t of these discrepancies were resolved by shifting the analysis time by a 
 few minutes. R5 calculated the shortest time in most cases\; however\, whe
 n boarding or alighting at stops more than 300 m from the origin or destin
 ation\, OTP identified the shortest paths. This appears to be due to R5 pr
 ioritizing stops within 300 m and searching further if no route is found.\
 n\nOverall\, OTP and R5 are suitable tools for measuring shortest-path tra
 vel times using GTFS. OTP can calculate the highest number of shortest pat
 hs. However\, because OTP is substantially slower than R5\, testing many s
 cenarios using R5 may be more practical for exploring improvements in acce
 ssibility. Accordingly\, when R5 cannot calculate the shortest identifiabl
 e pathh.\n\nThese results enable the calculation of reachable populations 
 based on arrival times at each medical institution\, for example\, using R
 5’s high-speed and precise travel time estimation. As a result\, we prov
 ided a QGIS plugin utilizing R5. The plugin constructs OD tables through g
 raphical user interface (GUI) operations\, eliminating the need for comman
 ds and adding statistical values such as travel times to the QGIS as GIS d
 ata.
DTSTAMP:20260717T234902Z
LOCATION:Cosmos1
SUMMARY:Tool Selection for Detailed Accessibility Analysis Using GTFS Data:
  The Case of the Yamagata Urban Area - Shota Yamamoto
URL:https://talks.osgeo.org/foss4g-2026/talk/KS97DK/
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