A 3D CAMPUS APPLICATION BASED ON CITY MODELS AND WEBGL

Abstract. In parallel with the technological developments, the conventional ways of mapping and the presentation of the geospatial data have changed significantly. 3D city models including the digital terrain models (DTMs) have become important for many application fields, such as simulation and visualization tasks for navigation, urban planning, environmental monitoring, disaster management, etc. Although currently most 3D city models are employed for visualization purposes, their application areas are increasing continuously. The presentation of these models on the web is also becoming more common than before while overcoming the performance issues with newer data types and functionalities. The biggest advantage of using web browsers is that they can be accessed everywhere without any additional software requirements. Therefore, the tools for web-based implementations of virtual globes, which allow users to navigate their data in 3D, have been available with greater numbers of functionality they offer. Online virtual web globes provide a good base for the 3D Geographical Information System (GIS) applications as well. 3D city models have also become virtual environments where different spatial queries and analysis can be performed. As a part of a 3D WebGIS, a city model enriched with semantic information provides a virtual platform for decision makers and allows realistic simulations for planning. The main aims of this study are to develop a prototype of a 3D GIS environment for Hacettepe University Beytepe campus, including 3D building geometries enriched with semantic information and a high resolution DTM; and to design a web interface using an open source virtual globe.

Download Full-text

INVESTIGATING INTEROPERABILITY CAPABILITIES BETWEEN IFC AND CITYGML LOD 4 – RETAINING SEMANTIC INFORMATION

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlii-4-w10-33-2018 ◽

2018 ◽

Vol XLII-4/W10 ◽

pp. 33-40 ◽

Cited By ~ 3

Author(s):

G. S. Floros ◽

C. Ellul ◽

E. Dimopoulou

Keyword(s):

Semantic Information ◽

Open Data ◽

3D Models ◽

Solar Panels ◽

3D City Models ◽

Information Models ◽

Building Information ◽

Consistent Manner ◽

3D Information ◽

City Models

Abstract. Applications of 3D City Models range from assessing the potential output of solar panels across a city to determining the best location for 5G mobile phone masts. While in the past these models were not readily available, the rapid increase of available data from sources such as Open Data (e.g. OpenStreetMap), National Mapping and Cadastral Agencies and increasingly Building Information Models facilitates the implementation of increasingly detailed 3D Models. However, these sources also generate integration challenges relating to heterogeneity, storage and efficient management and visualization. CityGML and IFC (Industry Foundation Classes) are two standards that serve different application domains (GIS and BIM) and are commonly used to store and share 3D information. The ability to convert data from IFC to CityGML in a consistent manner could generate 3D City Models able to represent an entire city, but that also include detailed geometric and semantic information regarding its elements. However, CityGML and IFC present major differences in their schemas, rendering interoperability a challenging task, particularly when details of a building’s internal structure are considered (Level of Detail 4 in CityGML). The aim of this paper is to investigate interoperability options between the aforementioned standards, by converting IFC models to CityGML LoD 4 Models. The CityGML Models are then semantically enriched and the proposed methodology is assessed in terms of model’s geometric validity and capability to preserve semantics.

Download Full-text

Computing and monitoring potential of public spaces by shading analysis using 3d lidar data and advanced image analysis

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsarchives-xl-7-w3-743-2015 ◽

2015 ◽

Vol XL-7/W3 ◽

pp. 743-750 ◽

Cited By ~ 2

Author(s):

A. Zwolinski ◽

M. Jarzemski

Keyword(s):

Tall Buildings ◽

Public Spaces ◽

Lidar Data ◽

Data Types ◽

3D City Models ◽

European Cities ◽

Computer Environment ◽

Definition Of ◽

3D Lidar ◽

City Models

The paper regards specific context of public spaces in “shadow” of tall buildings located in European cities. Majority of tall buildings in European cities were built in last 15 years. Tall buildings appear mainly in city centres, directly at important public spaces being viable environment for inhabitants with variety of public functions (open spaces, green areas, recreation places, shops, services etc.). All these amenities and services are under direct impact of extensive shading coming from the tall buildings. The paper focuses on analyses and representation of impact of shading from tall buildings on various public spaces in cities using 3D city models. Computer environment of 3D city models in cityGML standard uses 3D LiDAR data as one of data types for definition of 3D cities. The structure of cityGML allows analytic applications using existing computer tools, as well as developing new techniques to estimate extent of shading coming from high-risers, affecting life in public spaces. These measurable shading parameters in specific time are crucial for proper functioning, viability and attractiveness of public spaces – finally it is extremely important for location of tall buildings at main public spaces in cities. The paper explores impact of shading from tall buildings in different spatial contexts on the background of using cityGML models based on core LIDAR data to support controlled urban development in sense of viable public spaces. The article is prepared within research project 2TaLL: Application of 3D Virtual City Models in Urban Analyses of Tall Buildings, realized as a part of Polish-Norway Grants.

Download Full-text

PLASTIC SURGERY FOR 3D CITY MODELS: A PIPELINE FOR AUTOMATIC GEOMETRY REFINEMENT AND SEMANTIC ENRICHMENT

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-v-4-2021-17-2021 ◽

2021 ◽

Vol V-4-2021 ◽

pp. 17-24

Author(s):

O. Wysocki ◽

B. Schwab ◽

L. Hoegner ◽

T. H. Kolbe ◽

U. Stilla

Keyword(s):

Point Clouds ◽

3D Models ◽

Data Types ◽

Automated Driving ◽

3D City Models ◽

Semantic Enrichment ◽

Simulation Engine ◽

Global Accuracy ◽

Model Database ◽

City Models

Abstract. Nowadays, the number of connected devices providing unstructured data is rapidly rising. These devices acquire data with a temporal and spatial resolution at an unprecedented level creating an influx of geoinformation which, however, lacks semantic information. Simultaneously, structured datasets like semantic 3D city models are widely available and assure rich semantics and high global accuracy but are represented by rather coarse geometries. While the mentioned downsides curb the usability of these data types for nowadays’ applications, the fusion of both shall maximize their potential. Since testing and developing automated driving functions stands at the forefront of the challenges, we propose a pipeline fusing structured (CityGML and HD Map datasets) and unstructured datasets (MLS point clouds) to maximize their advantages in the automatic 3D road space models reconstruction domain. The pipeline is a parameterized end-to-end solution that integrates segmentation, reconstruction, and modeling tasks while ensuring geometric and semantic validity of models. Firstly, the segmentation of point clouds is supported by the transfer of semantics from a structured to an unstructured dataset. The distinction between horizontal- and vertical-like point cloud subsets enforces a further segmentation or an immediate refinement while only adequately depicted models by point clouds are allowed. Then, based on the classified and filtered point clouds the input 3D model geometries are refined. Building upon the refinement, the semantic enrichment of the 3D models is presented. The deployment of a simulation engine for automated driving research and a city model database tool underlines the versatility of possible application areas.

Download Full-text

Incorporating Topological Representation in 3D City Models

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi8080347 ◽

2019 ◽

Vol 8 (8) ◽

pp. 347 ◽

Cited By ~ 5

Author(s):

Stelios Vitalis ◽

Ken Ohori ◽

Jantien Stoter

Keyword(s):

Data Structure ◽

Data Model ◽

Semantic Information ◽

Semantic Representation ◽

Geometric Analysis ◽

Computationally Efficient ◽

Real World Data ◽

3D City Models ◽

Map Data ◽

City Models

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map’s semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of geometry, topology and semantics by incorporating the C-Map data structure into the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

Download Full-text

A REQUIREMENT ANALYSIS ON EXTENDING SEMANTIC 3D CITY MODELS FOR SUPPORTING TIME-DEPENDENT PROPERTIES

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-iv-4-w9-19-2019 ◽

2019 ◽

Vol IV-4/W9 ◽

pp. 19-26 ◽

Cited By ~ 1

Author(s):

K. Chaturvedi ◽

T. H. Kolbe

Keyword(s):

Semantic Information ◽

Smart Cities ◽

Data Models ◽

Time Dependent ◽

Systematic Analysis ◽

3D City Models ◽

Semantic Data ◽

Different Types ◽

Support Time ◽

City Models

Abstract. Semantic 3D City Models are used worldwide for different application domains ranging from Smart Cities, Simulations, Planning to History and Archeology. Well-defined data models like CityGML, IFC and INSPIRE Data Themes allow describing spatial, graphical and semantic information of physical objects. However, cities and their properties are not static and change with respect to time. Hence, it is important that such semantic data models handle different types of changes that take place in cities and their attributes over time. This paper provides a systematic analysis and recommendations for extensions of Semantic 3D City Models in order to support time-dependent properties. This paper reviews different application domains in order to identify key requirements for temporal and dynamic extensions and proposes ways to incorporate these extensions. Over the last couple of years, different extensions have been proposed for these standards to deal with temporal attributes. This paper also presents an analysis to which degree these extensions cover the requirements for dynamic city models.

Download Full-text

INFERRING ROOF SEMANTICS FOR MORE ACCURATE SOLAR POTENTIAL ASSESSMENT

ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-archives-xlvi-4-w4-2021-33-2021 ◽

2021 ◽

Vol XLVI-4/W4-2021 ◽

pp. 33-37

Author(s):

I. Apra ◽

C. Bachert ◽

C. Cáceres Tocora ◽

Ö. Tufan ◽

O. Veselý ◽

...

Keyword(s):

Point Cloud ◽

Semantic Information ◽

Renewable Energy Sources ◽

Energy Transition ◽

Urban Landscapes ◽

Solar Panels ◽

3D City Models ◽

Additional Information ◽

Open Datasets ◽

City Models

Abstract. In guiding the energy transition efforts towards renewable energy sources, 3D city models were shown to be useful tools when assessing the annual solar energy generation potential of urban landscapes. However, the simplified roof geometry included in these 3D city models and the lack of additional semantic information about the buildings’ roof often yield less accurate solar potential evaluations than desirable. In this paper we propose three different methods to infer and store additional information into 3D city models, namely on physical obstacles present on the roof and existing solar panels. Both can be used to increase the accuracy of roof solar panel retrofit potential. These methods are developed and tested on the open datasets available in the Netherlands, specifically AHN3 lidar point-cloud and PDOK aerial photography. However, we believe they can be adapted to different environments as well, based on the available datasets and their precision locally available.

Download Full-text

Services Oriented Smart City Platform Based On 3d City Model Visualization

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprsannals-ii-4-59-2014 ◽

2014 ◽

Vol II-4 ◽

pp. 59-64 ◽

Cited By ~ 8

Author(s):

F. Prandi ◽

M. Soave ◽

F. Devigili ◽

M. Andreolli ◽

R. De Amicis

Keyword(s):

Spatial Data ◽

Smart City ◽

Smart Cities ◽

Geographical Information ◽

Data Infrastructure ◽

3D City Models ◽

3D City Model ◽

Key Factor ◽

City Model ◽

City Models

The rapid technological evolution, which is characterizing all the disciplines involved within the wide concept of smart cities, is becoming a key factor to trigger true user-driven innovation. However to fully develop the Smart City concept to a wide geographical target, it is required an infrastructure that allows the integration of heterogeneous geographical information and sensor networks into a common technological ground. In this context 3D city models will play an increasingly important role in our daily lives and become an essential part of the modern city information infrastructure (Spatial Data Infrastructure). The work presented in this paper describes an innovative Services Oriented Architecture software platform aimed at providing smartcities services on top of 3D urban models. 3D city models are the basis of many applications and can became the platform for integrating city information within the Smart-Cites context. In particular the paper will investigate how the efficient visualisation of 3D city models using different levels of detail (LODs) is one of the pivotal technological challenge to support Smart-Cities applications. The goal is to provide to the final user realistic and abstract 3D representations of the urban environment and the possibility to interact with a massive amounts of semantic information contained into the geospatial 3D city model. The proposed solution, using OCG standards and a custom service to provide 3D city models, lets the users to consume the services and interact with the 3D model via Web in a more effective way.

Download Full-text

Incorporating Topological Representation in 3D City Models

10.20944/preprints201905.0024.v1 ◽

2019 ◽

Author(s):

Stelios Vitalis ◽

Ken Arroyo Ohori ◽

Jantien Stoter

Keyword(s):

Data Structure ◽

Data Model ◽

Semantic Information ◽

Semantic Representation ◽

Geometric Analysis ◽

Computationally Efficient ◽

Real World Data ◽

3D City Models ◽

Map Data ◽

City Models

3D city models are being extensively used in applications such as evacuation scenarios and energy consumption estimation. The main standard for 3D city models is the CityGML data model which can be encoded through the CityJSON data format. CityGML and CityJSON use polygonal modelling in order to represent geometries. True topological data structures have proven to be more computationally efficient for geometric analysis compared to polygonal modelling. In a previous study, we have introduced a method to topologically reconstruct CityGML models while maintaining the semantic information of the dataset, based solely on the combinatorial map (C-Map) data structure. As a result of the limitations of C-Map's semantic representation mechanism, the resulting datasets could suffer either from semantic information loss or the redundant repetition of them. In this article, we propose a solution for a more efficient representation of both geometry, topology and semantics by incorporating the C-Map data structure in the CityGML data model and implementing a CityJSON extension to encode the C-Map data. In addition, we provide an algorithm for the topological reconstruction of CityJSON datasets to append them according to this extension. Finally, we apply our methodology to three open datasets in order to validate our approach when applied to real-world data. Our results show that the proposed CityJSON extension can represent all geometric information of a city model in a lossless way, providing additional topological information for the objects of the model.

Download Full-text

INTEGRATION OF 3D POINT CLOUDS WITH SEMANTIC 3D CITY MODELS – PROVIDING SEMANTIC INFORMATION BEYOND CLASSIFICATION

ISPRS Annals of Photogrammetry Remote Sensing and Spatial Information Sciences ◽

10.5194/isprs-annals-viii-4-w2-2021-105-2021 ◽

2021 ◽

Vol VIII-4/W2-2021 ◽

pp. 105-112

Author(s):

C. Beil ◽

T. Kutzner ◽

B. Schwab ◽

B. Willenborg ◽

A. Gawronski ◽

...

Keyword(s):

Point Cloud ◽

Semantic Information ◽

Spatial Information ◽

Point Clouds ◽

Semantic Knowledge ◽

Point Cloud Data ◽

Cloud Data ◽

3D City Models ◽

3D Point Clouds ◽

City Models

Abstract. A range of different and increasingly accessible acquisition methods, the possibility for frequent data updates of large areas, and a simple data structure are some of the reasons for the popularity of three-dimensional (3D) point cloud data. While there are multiple techniques for segmenting and classifying point clouds, capabilities of common data formats such as LAS for providing semantic information are mostly limited to assigning points to a certain category (classification). However, several fields of application, such as digital urban twins used for simulations and analyses, require more detailed semantic knowledge. This can be provided by semantic 3D city models containing hierarchically structured semantic and spatial information. Although semantic models are often reconstructed from point clouds, they are usually geometrically less accurate due to generalization processes. First, point cloud data structures / formats are discussed with respect to their semantic capabilities. Then, a new approach for integrating point clouds with semantic 3D city models is presented, consequently combining respective advantages of both data types. In addition to elaborate (and established) semantic concepts for several thematic areas, the new version 3.0 of the international Open Geospatial Consortium (OGC) standard CityGML also provides a PointCloud module. In this paper a scheme is shown, how CityGML 3.0 can be used to provide semantic structures for point clouds (directly or stored in a separate LAS file). Methods and metrics to automatically assign points to corresponding Level of Detail (LoD)2 or LoD3 models are presented. Subsequently, dataset examples implementing these concepts are provided for download.

Download Full-text