Urban data visualisation in a web browser

Gaillard, Jérémy; Vienne, Alexandre; Baume, Rémi; Pedrinis, Frédéric; Peytavie, Adrien; Gesquière, Gilles

doi:10.1145/2775292.2775302

Cited by 28 publications

(25 citation statements)

References 8 publications

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“…Progressive loading and multi-resolution rendering algorithms help to avoid latency while loading huge 3D models (Ponchio and Dellepiane, 2016). Additionally, the model is processed server-side to multiple levels of detail (LOD) and segmented into tiles (Cozzi, 2015;Gaillard et al, 2015). In this approach, only 3D objects close to the camera are loaded and displayed in detail, while objects further away are smaller and less detailed.…”

Section: D Browsermentioning

confidence: 99%

Urban History in 4 Dimensions – Supporting Research and Education

Münster

Friedrichs

Kröber

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:The new research group on the four-dimensional research and communication of urban history (Urban History 4D) aims to investigate and develop methods and technologies to access extensive repositories of historical media and their contextual information in a spatial model, with an additional temporal component. This will make content accessible to different target groups, researchers and the public, via a 4D browser. A location-dependent augmented-reality representation can be used as an information base, research tool, and means of communicating historical knowledge. The data resources for this research include extensive holdings of historical photographs of Dresden, which have documented the city over the decades, and digitized map collections from the Deutsche Fotothek (German photographic collection) platform. These will lay the foundation for a prototype model which will give users a virtual experience of historic parts of Dresden.

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Section: D Browsermentioning

confidence: 99%

Urban History in 4 Dimensions – Supporting Research and Education

Münster

Friedrichs

Kröber

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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“…Recently several European cities like Berlin, Lyon, Wien and Rotterdam, for instance, have realized their official 3D city models as Open Data by means of LOD2/LOD3 textured CityGML models of the whole city (Prandi et al, 2015, Mao et al, 2014, Gaillard et al, 2015. Industry companies like Google, Apple and Here are also integrating 3D city models into their map services (Mao et al, 2014, Prandi et al, 2015.…”

Section: Motivationmentioning

confidence: 99%

“…(Rodrigues et al, 2013, Gaillard et al, 2015, Mao et al, 2012, Prandi et al, 2015, Chatuverdi, 2014. Hence, CityGML models are essential to represent and analyze 3D city objects, but not to present or visualize 3D city models directly (Rodrigues et al, 2013, Mao et al, 2012.…”

Section: City Modeling For Representationmentioning

confidence: 99%

“…Hence, CityGML models are essential to represent and analyze 3D city objects, but not to present or visualize 3D city models directly (Rodrigues et al, 2013, Mao et al, 2012. Additionally, the detailed and complex structure of CityGML based on heavy XML causes pressure for efficient visualization of CityGML files since reading XML based schemas is complex in JavaScript applications (Gaillard et al, 2015, Mao et al, 2012. In order to visualize CityGML data on the web, parsing methods capable of retrieve information from CityGML and recode it to a more presentation friendly format, namely X3D, JSON and KML/COLLADA, are used (Rodrigues et al, 2013, Chatuverdi, 2014 while maintaining the richness, in terms of semantic information, of models contained in CityGML files (Gaillard et al, 2015).…”

Section: City Modeling For Representationmentioning

confidence: 99%

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Rethinking GIS Towards The Vision Of Smart Cities Through CityGML

Güney

2016

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Smart cities present a substantial growth opportunity in the coming years. The role of GIS in the smart city ecosystem is to integrate different data acquired by sensors in real time and provide better decisions, more efficiency and improved collaboration. Semantically enriched vision of GIS will help evolve smart cities into tomorrow's much smarter cities since geospatial/location data and applications may be recognized as a key ingredient of smart city vision. However, it is need for the Geospatial Information communities to debate on "Is 3D Web and mobile GIS technology ready for smart cities?" This research places an emphasis on the challenges of virtual 3D city models on the road to smarter cities. MOTIVATIONIn many countries, addition to people chose to live in big cities, an increasing number of people from small towns and villages is moving into big cities. Globally more people live in urban areas than in rural areas. Production, processing, query, analysis, visualization, updating, maintaining and sharing of three dimensional (3D) geospatial data related to cities are very important tasks for managing the urban environments in 3D while the world continues population growth and urbanization.The possibility to visualize and interact with 3D city models on the Web is of interest for technicians, decision makers and citizens (Rodrigues et al., 2013). The accessibility of the online city models through web browsers can enlarge the audience of the 3D model to broad audience and professionals that typically are not expert on geospatial information but who can be benefit on their work from the usage of 3D city models (Prandi et al., 2015).There is a rapidly increasing need for 3D geospatial information and 3D city models for many different areas of application like urban planning, landscape planning, environmental planning, 3D cadaster, real-estate, public participation, facility management, disaster management, transportation, energy planning, tourism, simulation, and analysis. These application areas are also central to the very notion of a smart city.Today, more and more cities worldwide are undergoing transition from 2D Geospatial Information System (GIS) to 3D Web GIS, and using Web 3D city viewers or virtual globes. Recently several European cities like Berlin, Lyon, Wien and Rotterdam, for instance, have realized their official 3D city models as Open Data by means of LOD2/LOD3 textured CityGML models of the whole city (Prandi et al., 2015, Mao et al., 2014, Gaillard et al., 2015. Industry companies like Google, Apple and Here are also integrating 3D city models into their map services (Mao et al., 2014, Prandi et al., 2015. Volunteered Geographic Data/Information (VGI) communities such as Open Street Map (OSM) are building 3D city models as well (Mao et al., 2014). From this point of view opportunities to utilize 3D urban mapping and the volume of online virtual city models are expanding dramatically and virtual 3D city applications are increasingly employed in different domains.The successful ...

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“…A 2D grid manages the loading of data in (Chaturvedi et al, 2015b), (Gesquiere and Manin, 2012) or (Gaillard et al, 2015). While its simplicity can be attractive for web applications, the visual result is unsatisfactory: data is loaded non-uniformly, in chunks.…”

Section: State Of the Artmentioning

confidence: 99%

Data Structure for Progressive Visualisation and Edition Of Vectorial Geospatial Data

Gaillard

Peytavie

Gesquière

2016

ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:3D mock-ups of cities are becoming an increasingly common tool for urban planning. Sharing the mock-up is still a challenge since the volume of data is so high. Furthermore, the recent surge in low-end, mobile devices requires developers to carefully control the amount of data they process. In this paper, we present a hierarchical data structure that allows the streaming of vectorial data. Loosely based on a quadtree, the structure stores the data in tiles and is organised following a weight function which allows the most relevant data to be displayed first. The relevance of a feature can be measured by its geometry and semantic attributes, and can vary depending on the application or client type. Tiles can be limited in size (number of features or triangles) for the client to be able to control resource consumption. The article also presents algorithms for the addition or removal of features in the data structure, opening the path for the interactive edition of city data stored in a database.

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Urban data visualisation in a web browser

Cited by 28 publications

References 8 publications

Urban History in 4 Dimensions – Supporting Research and Education

Urban History in 4 Dimensions – Supporting Research and Education

Rethinking GIS Towards The Vision Of Smart Cities Through CityGML

Data Structure for Progressive Visualisation and Edition Of Vectorial Geospatial Data

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