scholarly journals INFERRING ROOF SEMANTICS FOR MORE ACCURATE SOLAR POTENTIAL ASSESSMENT

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.

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

2018 ◽  
Vol XLII-4/W10 ◽  
pp. 33-40 ◽  
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

<p><strong>Abstract.</strong> 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.</p>

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

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.

scholarly journals 3D CITY MODELS FOR URBAN MINING: POINT CLOUD BASED SEMANTIC ENRICHMENT FOR SPECTRAL VARIATION IDENTIFICATION IN HYPERSPECTRAL IMAGERY

2020 ◽  
Vol V-4-2020 ◽  
pp. 223-230
Author(s):  
P. A. Ruben ◽  
R. Sileryte ◽  
G. Agugiaro
Keyword(s):  
Point Cloud ◽  
Building Materials ◽  
Hyperspectral Imagery ◽  
Region Growing ◽  
Accurate Information ◽  
Spectral Variation ◽  
Urban Mining ◽  
3D City Models ◽  
Semantic Enrichment ◽  
City Models

Abstract. Urban mining aims at reusing building materials enclosed in our cities. Therefore, it requires accurate information on the availability of these materials for each separate building. While recent publications have demonstrated that such information can be obtained using machine learning and data fusion techniques applied to hyperspectral imagery, challenges still persist. One of these is the so-called ’salt-and-pepper noise’, i.e. the oversensitivity to the presence of several materials within one pixel (e.g. chimneys, roof windows). For the specific case of identifying roof materials, this research demonstrates the potential of 3D city models to identify and filter out such unreliable pixels beforehand. As, from a geometrical point of view, most available 3D city models are too generalized for this purpose (e.g. in CityGML Level of Detail 2), semantic enrichment using a point cloud is proposed to compensate missing details. So-called deviations are mapped onto a 3D building model by comparing it with a point cloud. Seeded region growing approach based on distance and orientation features is used for the comparison. Further, the results of a validation carried out for parts of Rotterdam and resulting in KHAT values as high as 0.7 are discussed.

scholarly journals A 3D CAMPUS APPLICATION BASED ON CITY MODELS AND WEBGL

2018 ◽  
Vol XLII-5 ◽  
pp. 161-165 ◽  
Author(s):  
M. Buyukdemircioglu ◽  
S. Kocaman
Keyword(s):  
Semantic Information ◽  
Geographical Information ◽  
Data Types ◽  
3D City Models ◽  
Gis Applications ◽  
Technological Developments ◽  
Gis Environment ◽  
Virtual Platform ◽  
Application Fields ◽  
City Models

<p><strong>Abstract.</strong> 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.</p>

scholarly journals Incorporating Topological Representation in 3D City Models

2019 ◽  
Vol 8 (8) ◽  
pp. 347 ◽  
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.

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

2019 ◽  
Vol IV-4/W9 ◽  
pp. 19-26 ◽  
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.

scholarly journals Spatial ETL for 3D Building Modelling Based on Unmanned Aerial Vehicle Data in Semi-Urban Areas

2020 ◽  
Vol 12 (12) ◽  
pp. 1972 ◽  
Author(s):  
Urška Drešček ◽  
Mojca Kosmatin Fras ◽  
Jernej Tekavec ◽  
Anka Lisec
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Spatial Data ◽  
Urban Areas ◽  
Point Cloud ◽  
Process Model ◽  
Laser Scanning ◽  
3D City Models ◽  
Aerial Vehicle ◽  
Spatial Etl ◽  
City Models

This paper provides the innovative approach of using a spatial extract, transform, load (ETL) solution for 3D building modelling, based on an unmanned aerial vehicle (UAV) photogrammetric point cloud. The main objective of the paper is to present the holistic workflow for 3D building modelling, emphasising the benefits of using spatial ETL solutions for this purpose. Namely, despite the increasing demands for 3D city models and their geospatial applications, the generation of 3D city models is still challenging in the geospatial domain. Advanced geospatial technologies provide various possibilities for the mass acquisition of geospatial data that is further used for 3D city modelling, but there is a huge difference in the cost and quality of input data. While aerial photogrammetry and airborne laser scanning involve high costs, UAV photogrammetry has brought new opportunities, including for small and medium-sized companies, by providing a more flexible and low-cost source of spatial data for 3D modelling. In our data-driven approach, we use a spatial ETL solution to reconstruct a 3D building model from a dense image matching point cloud which was obtained beforehand from UAV imagery. The results are 3D building models in a semantic vector format consistent with the OGC CityGML standard, Level of Detail 2 (LOD2). The approach has been tested on selected buildings in a simple semi-urban area. We conclude that spatial ETL solutions can be efficiently used for 3D building modelling from UAV data, where the data process model developed allows the developer to easily control and manipulate each processing step.

scholarly journals Modelling Buildings in CityGML LOD1: Building Parts, Terrain Intersection Curve and Address Features

2021 ◽  
Author(s):  
Evgeny Shirinyan ◽  
Dessislava Petrova-Antonova
Keyword(s):  
Multiple Sources ◽  
Intersection Curve ◽  
3D City Models ◽  
Building Model ◽  
3D City Model ◽  
Building Models ◽  
City Model ◽  
Open Datasets ◽  
Multiple Domains ◽  
City Models

3D city models integrate heterogeneous urban data from multiple sources in a unified geospatial representation, combining both semantics and geometry. Although in the last decades, they are predominantly used for visualization, today they are used in a large range of tasks related to exploration, analysis, and management across multiple domains. The complexity of urban processes and the diversity of urban environment bring challenges to the implementation of 3D city models. To address such challenges, this paper presents the development process of a 3D city model of a single neighborhood in Sofia city based on CityGML 2.0 standard. The model represents the buildings in LOD1 with a focus on CityGML features of related to the buildings like building part, terrain intersection curve and address. Similar building models of 18 cities provided as open datasets are explored and compared in order to extract good modeling practices. As a result, workflows for generation of 3D building models in LOD1 are elaborated and improvements in the feature modeling are proposed. Two options of building model are examined: modeling of a building as a single solid and modeling of a building with separate building parts. Finally, the possibilities for visualization of the model in popular platforms such as ArcGIS Pro and Cesium Ion are explored.

scholarly journals Incorporating Topological Representation in 3D City Models

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.

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