BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-2026//talk//DCRXWD BEGIN:VTIMEZONE TZID:JST BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:JST TZOFFSETFROM:+0900 TZOFFSETTO:+0900 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2026-DCRXWD@talks.osgeo.org DTSTART;TZID=JST:20260901T143000 DTEND;TZID=JST:20260901T150000 DESCRIPTION:Proximity-based community planning has emerged as an important approach for improving urban livability by ensuring that essential service s are accessible within short travel distances. Rather than relying solely on administrative boundaries\, this planning approach focuses on the spat ial organization of everyday urban activities and the accessibility of key services such as healthcare\, education\, retail\, and public facilities. \n\nHowever\, operationalizing proximity-based planning requires analytic al frameworks capable of integrating large-scale mobility data\, accessibi lity modelling\, and spatial optimization. In many cities\, these analytic al components remain fragmented across different tools and datasets\, maki ng it difficult to develop reproducible and scalable workflows for urban a nalysis. At the same time\, recent advances in open geospatial technologie s provide new opportunities to build transparent\, interoperable\, and rep roducible analytical systems that support data-driven planning practices.\ n\nThis research proposes an open geospatial analytical framework for prox imity-based community planning that integrates mobility data\, open-source geospatial software\, and spatial optimization techniques into a unified and reproducible analytical workflow. The framework is designed to support two key planning tasks: \n\nthe identification of functional urban commun ities based on observed mobility patterns\, and the evaluation of spatial strategies for improving equitable access to essential urban services. \n\ nBy combining multiple open geospatial technologies\, the proposed framewo rk aims to provide a flexible analytical approach that can be applied acro ss different urban contexts while maintaining transparency and reproducibi lity.\n\nThe analytical framework consists of three core components that c orrespond to different stages of proximity-based planning analysis.\n\nThe first component focuses on the delineation of functional urban communitie s using mobility-based community detection. Large-scale telecom mobility d ata are used to construct origin–destination interaction networks betwee n spatial units\, represented as a grid-based spatial system. These mobili ty networks capture aggregated daily travel patterns between locations and provide a behavioral representation of urban spatial structure. Community detection algorithms from network science are applied to these networks i n order to identify clusters of spatial interaction that represent functio nal communities emerging from mobility patterns. Unlike traditional planni ng units that rely on administrative boundaries\, these mobility-derived c ommunities reflect actual patterns of urban activity and interaction. As a result\, the framework allows planners to identify spatial units that fun ction as integrated communities in terms of daily mobility and service acc ess.\n\nThe second component performs multimodal accessibility analysis at a high spatial resolution using open geospatial routing tools. Accessibil ity is calculated on a 250 m grid by combining telecom-derived origin–de stination mobility flows with network-based travel times. Road-based acces sibility is estimated using open routing engines such as OSRM\, which comp ute travel distances and travel times along road networks derived from ope n geospatial data sources. In addition\, public transport accessibility is computed using the R5 routing engine through the r5py Python interface. T he R5 engine enables multimodal routing that integrates pedestrian network s\, road networks\, and public transport schedules derived from GTFS data. This approach allows the framework to calculate multimodal travel times a cross different transport modes\, including walking\, road-based transport \, and public transit. The use of R5 and r5py also supports efficient comp utation of accessibility metrics for large-scale urban datasets\, enabling the evaluation of accessibility patterns at a fine spatial resolution. By integrating multiple travel modes\, the framework provides a more realist ic representation of accessibility conditions in dense urban environments where public transport plays a significant role in daily mobility.\n\nThe third component incorporates facility allocation models based on linear pr ogramming in order to optimize the spatial distribution of urban services. The optimization model uses accessibility indicators derived from the mul timodal analysis to evaluate potential service locations and allocation st rategies. The objective function simultaneously considers equity and econo mic efficiency in service provision\, allowing the model to identify spati al configurations that improve service accessibility while minimizing spat ial inequality and redundant infrastructure investment. The allocation mod el can therefore support planning decisions related to the placement of pu blic facilities\, community services\, and other urban amenities that are critical for proximity-based community planning.\n\nA key contribution of this study lies in the integration of multiple open geospatial tools into a unified analytical workflow. Rather than introducing a single standalone software package\, the framework combines several existing open-source ge ospatial technologies\, including Python-based network analysis libraries\ , open routing engines\, and geospatial data processing tools. This integr ation demonstrates how different open geospatial components can be combine d to support complex urban analytics tasks. Furthermore\, the computationa l workflow is designed to support reproducible research practices by docum enting analytical steps and enabling the release of scripts\, models\, and computational procedures under open-source principles. Such reproducibili ty is essential for ensuring transparency and enabling other researchers a nd practitioners to replicate and extend the analytical framework.\n\nThe framework is demonstrated through an empirical case study in Busan\, South Korea\, where telecom mobility data are used to analyze community structu res and evaluate alternative service distribution scenarios. The case stud y illustrates how mobility-derived communities differ significantly from c onventional administrative planning units and provide a more realistic rep resentation of urban spatial interaction. The integration of multimodal ac cessibility analysis and spatial optimization further allows planners to e xamine how alternative facility configurations influence accessibility out comes across the urban population. These results highlight the potential o f combining open geospatial technologies with mobility data to support evi dence-based urban planning.\n\nThis study contributes to the open geospati al research community in several ways. \n\nFirst\, it demonstrates how ope n geospatial technologies can support integrated urban analytics workflows for community-level planning. \n\nSecond\, it connects methods from netwo rk science\, multimodal accessibility modelling\, and spatial optimization within a reproducible open-source analytical framework. \n\nThird\, it hi ghlights how open geospatial ecosystems enable transparent and collaborati ve approaches to urban analysis and planning. \n\nBy presenting a reproduc ible analytical framework for proximity-based community planning built on open geospatial technologies\, this research contributes to ongoing effort s within the FOSS4G community to advance open\, scalable\, and collaborati ve geospatial solutions for sustainable urban development. DTSTAMP:20260717T225737Z LOCATION:Cosmos1 SUMMARY:An Open Geospatial Framework for Proximity-Based Community Planning :
Integrating Mobility-Based Community Detection\, Multimodal Accessibil ity\, and Facility Allocation Optimization - Junyoung CHOI URL:https://talks.osgeo.org/foss4g-2026/talk/DCRXWD/ END:VEVENT END:VCALENDAR