Model Data as Open Digital Commons: A Case Study of Openness in Japan's Digital Twin "Project PLATEAU" Toshikazu Seto* Ph.D. (tosseto) Taichi Furuhashi (Aoyama Gakuin Univ.) and Yuya Uchiyama (Ministry of Land, Infrastructure, Transport and Tourism) *: Associate Professor Department of Geography, Komazawa University / OSGeo.JP (OSGeo Charter member) A02 KOMAZAWA UNIVERSITY Visual Identity Guidelines จϩΰλΠϓ ,ϚʔΫʴจϩΰλΠϓͷΈ߹Θͤ ɺ ࠨͷछͰ͢ɻ ԣ جຊܗͱ͠ɺ ༏ઌతʹ༻͠·͢ɻ ԣ ϫϯϙΠϯτͳͲɺ ʮԣʯ ͕ஔ͠ʹ͍͘ ߹ʹ༻͠·͢ɻ ॎ ॎܕαΠϯͳͲɺ ࡉ͍ஔʹ༻͠·͢ɻ ඞͣϚελʔσʔλΛ༻͍ͯͩ͘͠͞ɻ ࠨهҎ֎ͷΈ߹ΘͤΛ࡞͠ͳ͍Ͱ ͍ͩ͘͞ɻ ʣ ॎ Project PLATEAU CC-BY 4.0, ODC BY and ODbL
Background of “Project PLATEAU” 3. 3DCMs Development and Converge in PLATEAU • CityGML • PLATEAU building data coverage in Japanese Cities • Comparison of PLATEAU and OSM building in Tokyo 4. Development of PLATEAU View by FOSS4G 5. Trends of Use-case Projects using PLATEAU Data and FOSS4G Tools 6. Findings and Future Works UBT D / N112 - Second Floor: GENERAL TRACK • 16:00pm Open data of digital twin city models in CityGML format and their import into OpenStreetMap (Taichi Furuhashi) • 16:30pm Project PLATEAU ～The initiative of Digital Twin in Japan～ (Yuya Uchiyama)
Digital Technology & Advanced Data Utilization: Crucial for solving urban problems and improving citizen services. • Digital Twins: Virtual representations of physical urban environments with wide- ranging applications, but with associated technical challenges. • 3D City Models (3DCMs): A growing need in the era of smart cities and key to achieving seamless visualization of city data. • Quantitative & Qualitative Analysis: The paper presents a detailed examination of the development and use of 3D city models in Japan. Caprari, G.; Castelli, G.; Montuori, M.; Camardelli, M.; Malvezzi, R. Digital Twin for Urban Planning in the Green Deal Era: A State of the Art and Future Perspectives. Sustainability 2022, 14, 6263. https://doi.org/10.3390/su14106263
in PLATEAU • CityGML: A format for 3D city models used by PLATEAU, encompassing geometric and semantic elements, providing multiscale data in a single format. ØThe format, which can describe the entire urban space, allows for different Levels of Detail (LOD) and can include an Application Domain Extension (ADE) for region-specific attributes, making it particularly useful in urban planning and disaster simulations. ØThe unique approach of PLATEAU in providing a comprehensive dataset that includes diverse information beyond building data. ØThe utilization of various formats to visualize data in different platforms, from GIS software to web applications and modeling tools like Blender and Unity. http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.005
data coverage in Japanese Cities 1.The Level of Detail 1 (LOD1) building data in Project PLATEAU, mostly created using survey data from 2019 to 2021, covers 150 cities or about 11% of Japan's total cities, representing about 40% of Japan's population. 2.The city with the most extensive LOD1 data coverage is central Tokyo, with large cities of over 500,000 inhabitants covering about half the area, primarily in urban planning areas. This coverage represents about 55% of the total area. 3.A comparison with OpenStreetMap (OSM) data shows that the cities covered by Project PLATEAU have more detailed building data. The number of buildings represented in the OSM within the PLATEAU-covered cities is approximately 31% of the total number of buildings maintained in LOD1. Category Unit > 500,000 pop. Cities > 200,000 pop. Cities Tokyo's 23 Wards General Cities Total Selected Cities cities 17 26 23 84 150 Total Population 2020 pop. 24,574,264 9,116,039 9,733,276 6,358,667 49,782,246 City Areas sq. km 10,392 9,226 623 15,463 35,704 OSM Buildings objects 2,896,476 916,057 731,374 1,122,159 5,666,066 sq. km 4,830 4,886 623 9,254 19,593 objects 7,776,703 4,691,285 1,768,252 4,073,643 18,309,883 sq. km 71 80 23 133 307 objects 181,978 161,884 31,082 222,712 597,656 Buildings LOD2 Buildings LOD1
OSM building in Tokyo • To compare the spatial distribution trends of building data from LOD1 of PLATEAU and OSM, the number of buildings was counted in 23 wards of central Tokyo (Seto, 2022), where the coverage of both data was high. • The numbers of objects for each building dataset in the entire area were 731,374 objects for OSM and 1,768,252 objects for PLATEAU. If the number of objects in PLATEAU is considered the total, the number of buildings in OSM is approximately 40%. • • Tokyo Station • Shibuya Station Shinjuku Station
OSM building in Tokyo • Compare microscopic spatial units, the number of units in each building data was tabulated for each of the 3,190 city blocks, and the percentage of OSM data with PLATEAU data as the population was calculated. • The results indicated that 1548 city blocks had less than 50% OSM data. However, in 502 (approximately 15.7%) city blocks, the OSM data exceeded the LOD1 data, with most located around the Tokyo Station or in the western part of the city. • As a factor in this discrepancy, a historical analysis of the timestamps and versions of the OSM building data (approximately 80,000 objects) not available in PLATEAU revealed that most data were created more than 2 years before the LOD1 data and have never been updated. • Therefore, LOD1 data with an update history older than 2020 may need to be replaced to keep the data updated, even in areas with relatively suitable coverage of OSM data.
by FOSS4G • PLATEAU VIEW: A web application that enables visualization of various PLATEAU-related datasets. • The viewer architecture, called "Re:Earth", is based on CesiumJS, supports 3D tiles and CZML animations natively, and includes WebAssembly plug-ins for functional extensions. • Available from Github under Apache- 2.0 license, it works with two systems, CMS and Editor, as well as Viewer. https://github.com/Project-PLATEAU/PLATEAU-VIEW-2.0
by FOSS4G 1.CMS - A new system that allows non- technical users to manage 3D city model data, including upload, quality check, viewer customization, and data publication. 2.Integration - 'Re:Earth CMS' offers improved architectural capabilities, promoting integration with other platforms like FME and PLATEAU SDKs for data format conversion. 3.Open resources - available under Apache-2.0 license. And construction manual also CC-BY 4.0. https://www.mlit.go.jp/plateau/file/libraries/doc/plateau_doc_0009_ver03.pdf
Bicycle Operation Status LEGEND: ex. Color coding based on building use ↓ Office Commercial Hotel Commercial complex Residential Apartment complexes Residences with stores, etc. 〃 〃 Government facilities welfare facilities Stations Factory Agriculture facilities Co-processing facilities Defense Facilities Others Unknown Button: Catalog search and URL screen sharing functions ↓ STORY mode↑
Tools (16 open source/33 regional projects) https://github.com/Project-PLATEAU id field project title tools area github lang id field project title tools area github lang uc22-010 Disaster Simulation simulation of the quantity of disaster waste generating QGIS large city ◦ Python uc22-003 Urban Modeling Floor-Area-Ratio 3D visualization simulation system ArcGIS CesiumJS Babylon.js local ◦ TypeScript uc22-018 Disaster Simulation Development of a Plug- in System to Support Community Disaster Management CesiumJS local ◦ JavaScript uc22-020 Urban Modeling Methodology on Urban Structure Simulation ArcGIS Pro QGIS R city ◦ Python uc22-027 Disaster Simulation Snow Risk Management Support Tool OpenFOAM ParaView QGIS Unity Blender local ◦ C++ uc22-023 Urban Modeling System of Pedestrian Traffic Simulation QGIS Unity local ◦ Python uc22-030 Disaster Simulation Digital transformation of area management for disaster prevention CesiumJS Unreal Engine Rhinocerous Blender Revit local ◦ C++ uc22-011 Urban Planning Gamification Methodology for Community Building with Citizen Engagement Cities:Skylines Mapbox local ◦ C++ uc22-039 Disaster Simulation Simulation system of evacuation behavior (by car or foot) during floods R CesiumJS local ◦ JavaScript uc22-012 Urban Planning DX of development permission CesiumJS TerriaJS GeoServer PostGIS city ◦ TypeScript uc22-041 Disaster Simulation Development of a Flood Risk Management Application via WebGIS Technology CesiumJS PostGIS ARCore Unity ArcGIS local ◦ JavaScript uc22-028 Urban Planning Development of Area Management Dashboard CesiumJS TerriaJS GeoServer PostGIS pgrouting local ◦ Clojure uc22-035 Urban Planning Development of an immersive urban planning tool using XR technology Next.js AR.js Three.js Unity OpenCV local ◦ JavaScript uc22-013 Environment Modeling Carbon Neutrality Policy Promotion Support System QGIS FZKViewer city ◦ C++ uc22-040 Urban Planning Smart Planning Methods for Walkable Design QGIS Shade3D GAUSS local ◦ Python uc22-045 Urban Planning Landscape planning support tools Unity local ◦ Unity
• "Simulations" - Over half of the projects involve simulations, predominantly disaster-related. • "Evacuation and Reconstruction" - Key topics of focus, including traffic simulation for evacuation and planning for the reconstruction phase. • ”Spatial Analysis" - A common platform for developing these tools as plugins, used more than PLATEAU VIEW for such purposes. https://www.mlit.go.jp/plateau/use-case/ UC22-010-QGIS-DisasterWastePlugin UC22-039-evacuation-simulation-tools
"XR technology" - Used to engage citizens in urban planning. • "Workshops" - Utilized VR glasses and AR applications to discuss future concepts based on fieldwork data. • "PLATEAU VIEW 2.0" - Platform where results of these citizen engagement activities are shared. https://www.mlit.go.jp/plateau/use-case/
•Digital Commons: Central to PLATEAU's mission, creating a universally accessible and standardized environment. •User-Centric: Essential for broadening the project's appeal and user base, requiring further improvement in usability and data accessibility. •Continuous Updating and Nationwide Coverage: Key challenges for the project's future, with the need for incentivizing local governments for wider data coverage and ongoing updates. Map the New World.
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