Ken Arroyo Ohori

Dr. Ken Arroyo Ohori


Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 August 2022 in International Journal of Geographical Information Science
Verified
Journal Article
Open access
ALAnna Labetski
Anna Labetski
SVStelios Vitalis
Stelios Vitalis
FBFilip Biljecki
Filip Biljecki
KOKen Arroyo Ohori
Ken Arroyo Ohori
JSJantien Stoter
Jantien Stoter
Urban morphology is important in a broad range of investigations across the fields of city planning, transportation, climate, energy, and urban data science. Characterising buildings with a set of numerical metrics is fundamental to studying the urban form. Despite the rapid developments in 3D geoinformation science, and the growing 3D data availability, most studies simplify buildings to their 2D footprint, and when taking their height into account, they at most assume one height value per building, i.e. simple 3D. We take the first step in elevating building metrics into full/true 3D, uncovering the use of higher levels of detail, and taking into account the detailed shape of a building. We set the foundation of the new research line on 3D urban morphology by providing a comprehensive set of 3D metrics, implementing them in openly released software, generating an open dataset containing 2D and 3D metrics for 823,000 buildings in the Netherlands, and demonstrating a use case where clusters and architectural patterns are analysed through time. Our experiments suggest the added value of 3D metrics to complement existing counterparts, reducing ambiguity, and providing advanced insights. Furthermore, we provide a comparative analysis using different levels of detail of 3D building models.

Verified
Journal Article
Open access
PDF file
KOKen Arroyo Ohori
Ken Arroyo Ohori
Abdoulaye DiakitéAbdoulaye Diakité
Abdoulaye Diakité
TKThomas Krijnen
Thomas Krijnen
HLHugo Ledoux
Hugo Ledoux
JSJantien Stoter
Jantien Stoter
It is widely acknowledged that the integration of BIM and GIS data is a crucial step forward for future 3D city modelling, but most of the research conducted so far has covered only the high-level and semantic aspects of GIS-BIM integration. This paper presents the results of the GeoBIM project, which tackled three integration problems focussing instead on aspects involving geometry processing: (i) the automated processing of complex architectural IFC models; (ii) the integration of existing GIS subsoil data in BIM; and (iii) the georeferencing of BIM models for their use in GIS software. All the problems have been studied using real world models and existing datasets made and used by practitioners in The Netherlands. For each problem, this paper exposes in detail the issues faced, proposed solutions, and recommendations for a more successful integration.

Verified
Journal Article
Open access
PDF file
Francesca NoardoFrancesca Noardo
Francesca Noardo
LHLars Harrie
Lars Harrie
KOKen Arroyo Ohori
Ken Arroyo Ohori
FBFilip Biljecki
Filip Biljecki
CEClaire Ellul
Claire Ellul
JSJantien Stoter
Jantien Stoter
The integration of 3D city models with Building Information Models (BIM), coined as GeoBIM, facilitates improved data support to several applications, e.g., 3D map updates, building permits issuing, detailed city analysis, infrastructure design, context-based building design, to name a few. To solve the integration, several issues need to be tackled and solved, i.e., harmonization of features, interoperability, format conversions, integration of procedures. The GeoBIM benchmark 2019, funded by ISPRS and EuroSDR, evaluated the state of implementation of tools addressing some of those issues. In particular, in the part of the benchmark described in this paper, the application of georeferencing to Industry Foundation Classes (IFC) models and making consistent conversions between 3D city models and BIM are investigated, considering the OGC CityGML and buildingSMART IFC as reference standards. In the benchmark, sample datasets in the two reference standards were provided. External volunteers were asked to describe and test georeferencing procedures for IFC models and conversion tools between CityGML and IFC. From the analysis of the delivered answers and processed datasets, it was possible to notice that while there are tools and procedures available to support georeferencing and data conversion, comprehensive definition of the requirements, clear rules to perform such two tasks, as well as solid technological solutions implementing them, are still lacking in functionalities. Those specific issues can be a sensible starting point for planning the next GeoBIM integration agendas.

27 June 2019 in Journal of Spatial Science
Verified
Journal Article
Open access
Francesca NoardoFrancesca Noardo
Francesca Noardo
CEClaire Ellul
Claire Ellul
LHLars Harrie
Lars Harrie
IOI. Overland
I. Overland
MSM. Shariat
M. Shariat
JSJantien Stoter
Jantien Stoter
The integration of geoinformation with BIM (GeoBIM) is critical to underpin solutions to many city-related challenges. However, to achieve an effective integration it is necessary to consider not only data and technical options but also current practice and users’ needs. This paper describes work carried out within the EuroSDR-GeoBIM project to address this challenge. After investigating potential uses for GeoBIM and existing challenges, we address a planning permits for buildings use case, to help bridging the gap between theory and practice. The resultshighlights a high-level harmonised workflow envisaging the use of GeoBIM information for automating the planning permits process.

5 August 2015 in International Journal of Geographical Information Science
Verified
Journal Article
Closed access
RBRoeland Boeters
Roeland Boeters
KOKen Arroyo Ohori
Ken Arroyo Ohori
FBFilip Biljecki
Filip Biljecki
Sisi ZlatanovaSisi Zlatanova
Sisi Zlatanova
The international standard CityGML defines five levels of detail (LODs) for 3D city models, but only the highest of these (LOD4) supports modelling the indoor geometry of a building, which must be acquired in correspondingly high detail and therefore at a high cost. Whereas simple 3D city models of the exterior of buildings (e.g. CityGML LOD2) can be generated largely automatically, and are thus now widely available and have a great variety of applications, similarly simple models containing their indoor geometries are rare. In this paper we present two contributions: (i) the definition of a level of detail LOD2+, which extends the CityGML LOD2 specification with indoor building geometries of comparable complexity to their exterior geometries in LOD2; and more importantly (ii) a method for automatically generating such indoor geometries based on existing CityGML LOD2 exterior geometries. We validate our method by generating LOD2+ models for a subset of the Rotterdam 3D data set and visually comparing these models to their real counterparts in building blueprints and imagery from Google Street View and Bing Maps. Furthermore, we use the LOD2+ models to compute the net internal area of each dwelling and validate our results by comparing these values to the ones registered in official government data sets.

Verified
Journal Article
Open access
PDF file
KOKen Arroyo Ohori
Ken Arroyo Ohori
HLHugo Ledoux
Hugo Ledoux
FBFilip Biljecki
Filip Biljecki
JSJantien Stoter
Jantien Stoter
The various levels of detail (LODs) of a 3D city model are often stored independently, without links between the representations of the same object, causing inconsistencies, as well as update and maintenance problems. One solution to this problem is to model the LOD as an extra geometric dimension perpendicular to the three spatial ones, resulting in a true 4D model in which a single 4D object (a polychoron) represents a 3D polyhedral object (e.g., a building) at all of its LODs and a multiple-LOD 3D city model is modeled as a 4D cell complex. While such an approach has been discussed before at a conceptual level, our objective in this paper is to describe how it can be realized by appropriately linking existing 3D models of the same object at different LODs. We first present our general methodology to construct such a 4D model, which consists of three steps: (1) finding corresponding 0D–3D cells; (2) creating 1D–4D cells connecting them; and (3) constructing the 4D model. Because of the complex relationships between the objects in different LODs, the creation of the connecting cells can become difficult. We therefore describe four different alternatives to do this, and we discuss the advantages and disadvantages of each in terms of their feasibility in practice and the properties that the resulting 4D model has. We show how the different linking schemes result in objects with different characteristics in several use cases. We also show how our linking method works in practice by implementing the linking of matching cells to construct a 4D model.