Managing Versions and History Within Semantic 3D City Models for the Next Generation of CityGML

Chaturvedi, Kanishk; Smyth, Carl Stephen; Gesquière, Gilles; Kutzner, Tatjana; Kolbe, Thomas H.

doi:10.1007/978-3-319-25691-7_11

Cited by 47 publications

(65 citation statements)

References 8 publications

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“…In addition, more thorough tests are required to evaluate application outputs against all different types of geometrical deviations. Finally, the methods and algorithms proposed in this research can be extended and applied to enable a version control system for collaborative work in modelling and storing digital 3D city models in the future (Chaturvedi et al, 2015).…”

Section: Discussionmentioning

confidence: 99%

“…This way, older datasets can both be updated and still retain their respective core structure, including own rules of syntax and internal object references. This plays a key role in enabling a version control system for collaborative work in modelling and storing digital 3D city models (Chaturvedi et al, 2015). Moreover, the number of transactions required for a WFS-enabled database is also reduced significantly.…”

Section: Introductionmentioning

confidence: 99%

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Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

Nguyen¹,

Yao²,

Kolbe³

2017

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

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ABSTRACT:A city may have multiple CityGML documents recorded at different times or surveyed by different users. To analyse the city's evolution over a given period of time, as well as to update or edit the city model without negating modifications made by other users, it is of utmost importance to first compare, detect and locate spatio-semantic changes between CityGML datasets. This is however difficult due to the fact that CityGML elements belong to a complex hierarchical structure containing multi-level deep associations, which can basically be considered as a graph. Moreover, CityGML allows multiple syntactic ways to define an object leading to syntactic ambiguities in the exchange format. Furthermore, CityGML is capable of including not only 3D urban objects' graphical appearances but also their semantic properties. Since to date, no known algorithm is capable of detecting spatio-semantic changes in CityGML documents, a frequent approach is to replace the older models completely with the newer ones, which not only costs computational resources, but also loses track of collaborative and chronological changes. Thus, this research proposes an approach capable of comparing two arbitrarily large-sized CityGML documents on both semantic and geometric level. Detected deviations are then attached to their respective sources and can easily be retrieved on demand. As a result, updating a 3D city model using this approach is much more efficient as only real changes are committed. To achieve this, the research employs a graph database as the main data structure for storing and processing CityGML datasets in three major steps: mapping, matching and updating. The mapping process transforms input CityGML documents into respective graph representations. The matching process compares these graphs and attaches edit operations on the fly. Found changes can then be executed using the Web Feature Service (WFS), the standard interface for updating geographical features across the web.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

Nguyen¹,

Yao²,

Kolbe³

2017

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

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“…Nevertheless, the CityGML standard currently does not provide us with a way to store this kind of information, because only the current state values are included (Morel and Gesquière 2014). An alternative is to extend CityGML to allow for versions of the entire model, or of some specific city elements, to represent different planning alternatives (Chaturvedi et al 2015). There is also a modeling approach and an implementation for supporting the management of versions and history within CityGML (Chaturvedi et al 2015).…”

Section: Related Workmentioning

confidence: 99%

“…An alternative is to extend CityGML to allow for versions of the entire model, or of some specific city elements, to represent different planning alternatives (Chaturvedi et al 2015). There is also a modeling approach and an implementation for supporting the management of versions and history within CityGML (Chaturvedi et al 2015). Another related problem is to keep the changes under control as the models evolve.…”

Section: Related Workmentioning

confidence: 99%

A continuous deployment-based approach for the collaborative creation, maintenance, testing and deployment of CityGML models

Prieto

Izkara

Béjar

2017

International Journal of Geographical Information Science

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Georeferenced 3D models are an increasingly common choice to store and display urban data in many application areas. CityGML is an open and standardized data model, and exchange format that provides common semantics for 3D city entities and their relations and one of the most common options for this kind of information. Currently, creating and maintaining CityGML models is costly and difficult. This is in part because both the creation of the geometries and the semantic annotation can be complex processes that require at least some manual work. In fact, many publicly available CityGML models have errors. This paper proposes a method to facilitate the regular maintenance of correct city models in CityGML. This method is based on the continuous deployment strategy and tools used in software development, but adapted to the problem of creating, maintaining and deploying CityGML models, even when several people are working on them at the same time. The method requires designing and implementing CityGML deployment pipelines. These pipelines are automatic implementations of the process of building, testing and deploying CityGML models. These pipelines must be run by the maintainers of the models when they make changes that are intended to be shared with others. The pipelines execute increasingly complex automatic tests in order to detect errors as soon as possible, and can even automate the deployment step, where the CityGML models are made available to their end users. In order to demonstrate the feasibility of this method, and as an example of its application, a CityGML deployment pipeline has been developed for an example scenario where three actors maintain the same city model. This scenario is representative of the kind of problems that this method intends to solve, and it is based on real work in progress. The main benefits of this method are the automation of model testing, every change to the model is tested in a repeatable way; the automation of the model deployment, every change to the model can reach its end users as fast as possible; the systematic approach to integrating changes made by different people working together on the models, including the possibility of keeping parallel versions with a common core; an automatic record of every change made to the models (who did what and when) and the possibility of undoing some of those changes at any time. ARTICLE HISTORY

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“…Furthermore, a unified model removes the need to duplicate the data (base model and visualisation model). With datasets covering larger and larger areas, exceeding the city scale, as well as existing in multiple temporal versions (Chaturvedi et al, 2015a), storage may well become an issue in the future.…”

Section: Introductionmentioning

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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Managing Versions and History Within Semantic 3D City Models for the Next Generation of CityGML

Cited by 47 publications

References 8 publications

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

Spatio-Semantic Comparison of Large 3d City Models in Citygml Using a Graph Database

A continuous deployment-based approach for the collaborative creation, maintenance, testing and deployment of CityGML models

Data Structure for Progressive Visualisation and Edition Of Vectorial Geospatial Data

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