Future City Pilot 1 Engineering Report

The following documents are referenced in this document. For dated references, subsequent amendments to, or revisions of, any of these publications do not apply. For undated references, the latest edition of the normative document referred to applies.

For the purposes of this report, the definitions specified in Clause 4 of the CityGML Encoding Standard [OGC 12-019] shall apply.

This ER is a starting point to understand the Dynamizer concept. The concept has been implemented as an Application Domain Extension (ADE) of the CityGML standard. The ER describes the overall development and implementation process of this concept in order to solve the real life issues identified within the scope of the FCP1 scenarios.

The main document starts with a short overview of the FCP1, the scenarios put forward by the pilot sponsors, and the respective solutions developed by the pilot participants. However, the details of each solution are provided in the individual ERs prepared by the participants as mentioned in Chapter 5. This ER focuses on the scenario requiring the support of real-time sensor observations and other time-dependent properties within semantic 3D city models. Chapter 6 provides an overview of the new concept 'Dynamizer' which has been conceptualized in order to extend semantic 3D city models by representing highly dynamic data in different ways and providing a method for injecting dynamic variations of city object properties into the static representation. The Dynamizer concept has been implemented as an ADE of the CityGML standard. During the pilot, the UML model of the Dynamizer ADE was developed. The details and explanations of each UML class have been described in Chapter 7. Chapter 8 shows the XML schema definition files derived from the UML model. The XML schema definition files were used for creation of the CityGML instance documents used in the pilot. Chapter 9 lists the components and the software systems used within the pilot, followed by the implementations which were used for the result demonstrations. In the end, Chapter 10 provides an outlook on the achievements and future activities that require more research to further increase the usability of dynamizers in different applications.

This section provides a brief overview of different scenarios and objectives defined within the FCP1. The objective of the OGC pilot project was to demonstrate how the use of the international standards such as CityGML and IFC together can provide stakeholders with information, knowledge and insight which enhances financial, environmental, and social outcomes for citizens living in cities. During the pilot, three scenarios were set up based on the real-world requirements put forward by the pilot sponsors and solutions were developed and demonstrated by the pilot participants. A short overview of the FCP1 scenarios is provided below.

The current generation semantic 3D city models are static in nature and do not support time-dependent properties. Apart from the scenarios mentioned in Chapter 5, there are many other application and simulation scenarios (e.g., environmental simulations, disaster management, training simulators), where time plays an important role. It is also important to distinguish between different types of changes that take place in cities over time. Some of these changes may be slower in nature, e.g., (i) history or evolution of cities such as construction or demolition of buildings and (ii) managing multiple versions of the city models. [2] propose an approach based on the CityGML standard to manage versions and history within semantic 3D city models. Some of the changes may also represent high frequency or dynamic variations of object properties, e.g., variations of (i) thematic attributes such as changes of physical quantities (energy demands, temperature, solar irradiation levels); (ii) spatial properties such as change of a feature’s geometry with respect to shape and location (moving objects); and (iii) real-time sensor observations (e.g., air quality sensors, weather stations, or smart meters). In this case, only some of the properties of otherwise static objects need to represent such time-varying values. Dynamizer is a new concept supporting the latter types of changes. Within the FCP1, the concept has been implemented to extend the CityGML information model using the built-in mechanism of the Application Domain Extension (ADE) in order to dynamize features and properties allowing for enriching the city model by data from dynamic data feeds.

Within the FCP1, dynamizers were implemented as an ADE for the CityGML standard. The ADE mechanism allows for the systematic extension of each CityGML object type by additional attributes as well as the introduction of new object types. This implementation allows dynamizers to be used with the current version of the CityGML standard (version 2.0).

Figure 2 shows the complete UML model of the Dynamizer ADE. The color scheme paints classes in different colors, depending on the UML package they belong to, and is defined as follows. A Class painted in yellow belongs to a CityGML UML package. A Class painted in light blue belongs to the GML package different to that associated with the yellow color. Classes painted in orange are newly introduced classes implemented as an ADE of the CityGML standard. However, there are two new classes which are not a part of [OGC 12-019] and belong to other OGC standards. Classes shown in dark blue represent OGC TimeseriesML 1.0 [OGC 15-043r3] and classes in pink belong to OGC Sensor Observation Service [OGC 12-006].

The individual components of the Dynamizer ADE UML model are explained in the following sub-sections.

This section includes the XML schema definition for the Dynamizer ADE. For the conceptual schema development, the model driven approach based on the ISO 19100 series of standards is applied, which allows for automatically deriving the XML schema documents from the conceptual schema. Upon development of the UML conceptual schema of the Dynamizer ADE, the XML schema was derived using the tool ShapeChange (see section 9.1.2). The details of the automatic derivation of the XML schema will be published in [OGC 16-130]. Based on the XML schema documents, valid CityGML Dynamizer ADE instance documents were developed according to specified use cases and used for the demonstrations as described in section 9.2.

Header of the Dynamizer ADE Schema definition file

DynamizerPropertyType

DynamizerType, Dynamizer

SensorConnectionType, SensorConnection

AbstractTimeseriesType, AbstractTimeseries

AtomicTimeseriesType, AtomicTimeseries

CompositeTimeseriesType, CompositeTimeseries

TimeseriesComponentType, TimeseriesComponent

This section provides a brief overview of the components used and the solutions developed for demonstrating the FCP1 scenarios.

The work has been partly funded by the OGC and the sponsors of the FCP1. We thank the OGC and all the FCP1 sponsors for supporting this work. For the use cases, the CityGML datasets were provided by Ordnance Survey Great Britain and Institut National de l’Information Géographique et Forestière (IGN), France. We thank virtualcitySYSTEMS GmbH, Germany for setting up the virtualcityMAP web application for one of the demonstrations. We also acknowledge the Climate-KIC of the European Institute of Innovation and Technology (EIT). The real-time sensor observations used in the FCP1 demonstration were retrieved from the project Smart Sustainable Districts funded by the Climate-KIC.

Human, natural, and physical systems interact in space and time and digital systems in cities will become increasingly diverse and numerous, with many actors. Cities therefore need a neutral, open platform, and standards for communicating spatial and temporal data. The Open Geospatial Consortium (OGC®) Future Cities Pilot 1 (FCP1) shows how cities can begin to adapt. The goal of this pilot project is to help cities around the world benefit from modern standards for geospatial technologies. The European-based pilot demonstrates and enhances the ability of cities to use different interoperable geospatial technologies to deliver better quality of life and civic initiatives in order to improve the resilience of society.

With the theme of climate change, the resilience to the risks of flooding is becoming more and more imminent. The management of the urban or peri-urban territory is characterized by complexity and requires the collaboration of all the actors to make the right decisions when managing the risks of flooding based on data of various origins created using different software. This risk management requires setting up tools and methods for the proper coordination of the actions of the various players. Flood mitigation and crisis management, as well as recovery, involve communities at different levels. Collaboration between government departments, local authorities and public and private actors (citizens, businesses, etc.) is therefore necessary to protect people and properties.

Cities need to take into account urban planning and management, the implementation of flood levees and protection structures, and address the ecological functionality of rivers and urban wetland areas. These efforts must be complemented by numerical model simulations of floods across 2-D floodplains.

For a more advanced analysis and visualization of the numerical simulations as well as to support the actors in the management of the risks of flooding and mitigation, we proposed a flood inundation scenario for the cities of Rennes and Greenwich, in collaboration with flood experts at Rennes Métropole and the University of Bristol, respectively. The purpose of the “inundation scenario” of the FCP1 pilot project is to transform the mapping of the results of flood modeling into CityGML format in order to add such simulations to existing 3D City Model databases (figure 15). This will enable cities to manage urban and environmental data more efficiently, interoperably and sustainably.

For the demonstration of the Rennes flood scenario in CityGML, we used the TELEMAC-2D software which solves the Saint-Venant equations in two dimensions [24]. Typically, results from this state-of-the-art model are, at each point of the resolution mesh, the height of water and the mean velocity in the vertical, and are commonly presented in a Geographic Information System (GIS) as points X, Y, and Z. For Rennes, we used an existing simulation of a flood of a return time of 1:100 years (provided by Artelia Engineering). The transformation from “traditional” flood model outputs to CityGML was achieved by first creating a triangular irregular network (TIN) with the X, Y and Z points to produce a high-resolution raster.

For the Greenwich “scenario”, we used an existing 1:200-year flood return period simulated by the 2-D LISFLOOD-FP flood model of the University of Bristol [25]. This model solves for the hydrodynamic forcing terms of the full Saint-Venant equations, except for convection, on a regular grid and decoupled on the computational faces of the water flux. For the Greenwich use case, this model was employed to simulate an “undefended” flood scenario of the River Thames. Given that for this regular-grid model, the typical outputs are provided in the form of an ASCII raster grid, transformation to a TIN was not necessary.

However, since the CityGML format requires input data as a “feature,” the raster of flood heights for both scenarios was first converted into a vector using the classification scheme as shown in figure 16 and figure 17.

Below are the specifications of a possible/suggested CityGML encoding for flood depths (provided by TUM) and figure 18 shows the application of both the Rennes and Greenwich inundation scenarios in the interactive 3D City Model of the TUM.

CityGML formatting for one polygon patch sample of the Rennes “flood scenario”

Furthermore, in order to present and process simulations of the TELEMAC-2D in CityGML for the Rennes project (as shown in figure 19), Rennes Métropole and IGN have made available several types of geospatial data, including a high-resolution numerical terrain model, river bathymetric data, details of 3-D infrastructures (flood levees, residential, industrial and commercial buildings), and aerial photographs of the city. All of these geospatial data comply with OGC standards and protocols, thus allowing more efficient interoperability.

Finally, figure 20 illustrates a possible wiring diagram scenario using OGC standards of how the CityGML encoding within a 3D City Model could benefit society and more specifically flood disaster response assistance, particularly in urban areas where most assets at risk of flooding are located.

[1] IFC: Industry Foundation Classes (IFC) Overview Summary, http://www.buildingsmart-tech.org/specifications/ifc-overview/ifc-overview-summary.

[2] Chaturvedi, K., Smyth, C.S., Gesquière, G., Kutzner, T., Kolbe, T.H.: Managing Versions and History Within Semantic 3D City Models for the Next Generation of CityGML. In: Abdul-Rahman, A. (ed.) Advances in 3D Geoinformation, pp. 191–206. Springer International Publishing, Cham (2017), https://mediatum.ub.tum.de/node?id=1276238.

[3] Chaturvedi, K.,Kolbe, T.H.: Integrating Dynamic data and Sensors with Semantic 3D City Models in the context of Smart Cities. In: ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. IV-2-W1vol. , pp. 31–38. Copernicus GmbH (2016), https://mediatum.ub.tum.de/node?id=1276240.

[4] Chaturvedi, K.,Kolbe, T.H.: Dynamizers - Modeling and Implementing Dynamic Properties for Semantic 3D City Models. In: Filip Biljecki, Vincent Tourre (eds.) Eurographics Workshop on Urban Data Modelling and Visualisation. The Eurographics Association (2015), https://diglib.eg.org/handle/10.2312/udmv20151348.

[5] W3C Recommendation: XML Path Language (XPath) 2.0 (Second Edition), http://www.w3.org/TR/xpath20.

[6] Kutzner, T.: Geospatial Data Modelling and Model-driven Transformation of Geospatial Data based on UML Profiles, pp. 75-111, PhD Thesis, Ingenieurfakultät Bau Geo Umwelt, Technische Universität München (2016), https://mediatum.ub.tum.de/node?id=1341432.

[7] EA: Enterprise Architect - UML Design Tools and UML CASE tools for software development, http://www.sparxsystems.com/products/ea.

[8] ShapeChange: ShapeChange - Processing application schemas for geographic information, http://shapechange.net.

[9] FME: Safe Software FME Integrate Data, Applications, Web Services, http://www.safe.com.

[10] citygml4j: citygml4j - The Open Source Java API for CityGML, https://github.com/citygml4j.

[11] 3DCityDB: 3D City Database (3DCityDB) Homepage, http://www.3dcitydb.org/3dcitydb/3dcitydbhomepage.

[12] Chaturvedi, K., Yao, Z., Kolbe, T.H.: Web-based Exploration of and Interaction with Large and Deeply Structured Semantic 3D City Models using HTML5 and WebGL. In: Kersten, T.P. (ed.) Bridging Scales - Skalenübergreifende Nah- und Fernerkundungsmethoden, 35. Wissenschaftlich-Technische Jahrestagung der DGPF, 24. Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V, Köln (2015), https://mediatum.ub.tum.de/node?id=1245285.

[13] virtualcityMAP: virtualcityMAP, http://www.virtualcitysystems.de/en/products/virtualcitymap.

[14] 3DCityDB-Web-Map: Cesium-based 3D viewer and JavaScript API for the 3D City Database, https://github.com/3dcitydb/3dcitydb-web-map.

[15] Cesium: Cesium - WebGL Virtual Globe and Map Engine, https://cesiumjs.org.

[16] Willenborg, B., Sindram, M., Kolbe, T. H.: Applications of 3D City Models for a better understanding of the Built Environment: (accepted). In Martin Behnisch, Gotthard Meinel (Eds.): Trends in Spatial Analysis and Modelling. Berlin, Heidelberg: Springer (Geotechnologies and the Environment) (2017), https://mediatum.ub.tum.de/node?id=1348882.

[17] 52°North SWE: 52N Sensor Web Community - Sensor Observation Service, http://52north.org/communities/sensorweb/sos.

[18] SSD: Smart Sustainable Districts, http://www.climate-kic.org/programmes/smart-sustainable-districts.

[19] Fusion Tables: Google Fusion Tables Help, https://support.google.com/fusiontables.

[20] virtualcityMAP: virtualcityMAP, http://www.virtualcitysystems.de/en/products/virtualcitymap.

[21] Yao, Z., Kolbe, T.H.: Dynamically Extending Spatial Databases to support CityGML Application Domain Extensions using Graph Transformations. In: Kersten, T.P. (Ed.), Kulturelles Erbe erfassen und bewahren - Von der Dokumentation zum virtuellen Rundgang, 37. Wissenschaftlich- Technische Jahrestagung der DGPF. Deutsche Gesellschaft für Photogrammetrie, Fernerkundung und Geoinformation e.V, Würzburg, pp. 316–331 (2017), http://www.dgpf.de/src/tagung/jt2017/proceedings/proceedings/papers/30_DGPF2017_Yao_Kolbe.pdf.

[22] OpenSensorHub: OpenSensorHub – Software for building smarter sensor networks, https://opensensorhub.org.

[23] FIWARE: FIWARE, https://www.fiware.org.

[24] Ata, R., Goeury, C., Hervouet, J.M.: TELEMAC MODELLING SYSTEM: 2D hydrodynamics TELEMAC-2D Software Release 7.0 User Manual. EDF-R&D, France (2014), http://www.opentelemac.org/downloads/MANUALS/TELEMAC-2D/telemac-2d_user_manual_en_v7p0.pdf

[25] Fewtrell, T.J., Bates, P.D., de Wit, A., Asselman, N., Sayers, P.B.: Comparison of varying complexity numerical models for the prediction of flood inundation in Greenwich, UK. In: FLOODrisk 2008, 30 September - 2 October 2008, Keble College, Oxford, UK (2008).