scholarly journals EXPLORATION OF OPEN DATA IN SOUTHEAST ASIA TO GENERATE 3D BUILDING MODELS

Author(s):  
F. Biljecki

Abstract. This article investigates the current status of generating 3D building models across 11 countries in Southeast Asia from publicly available data, primarily volunteered geoinformation (OpenStreetMap). The following countries are analysed: Brunei, Cambodia, Indonesia, Laos, Malaysia, Myanmar, Philippines, Singapore, Thailand, Timor-Leste, and Vietnam. This cross-country study includes multiple spatial levels of analysis: country, town, and micro-level (smaller neighbourhood). The main finding is that authoritative data to generate 3D building models is almost non-existent while building completeness in OpenStreetMap is highly heterogeneous, yielding location-dependent conclusions. While in general just a fraction of mapped buildings has height information and none of the administrative areas provides sufficient information to generate 3D building models, on a micro-level some areas are fully complete, providing a high potential to generate 3D building models on a precinct scale, which may be useful for certain spatial analyses. Furthermore, some areas have high building completeness, requiring only half of the work necessary for the extrusion: the collection of building height attributes. As a part of this work, a semantic 3D building model of a selected set of buildings in Singapore has been generated and released as open data (CityJSON), and the developed code was open-sourced.

Author(s):  
K. Chaidas ◽  
G. Tataris ◽  
N. Soulakellis

Abstract. In recent years 3D building modelling techniques are commonly used in various domains such as navigation, urban planning and disaster management, mostly confined to visualization purposes. The 3D building models are produced at various Levels of Detail (LOD) in the CityGML standard, that not only visualize complex urban environment but also allows queries and analysis. The aim of this paper is to present the methodology and the results of the comparison among two scenarios of LOD2 building models, which have been generated by the derivate UAS data acquired from two flight campaigns in different altitudes. The study was applied in Vrisa traditional settlement, Lesvos island, Greece, which was affected by a devastating earthquake of Mw = 6.3 on 12th June 2017. Specifically, the two scenarios were created by the results that were derived from two different flight campaigns which were: i) on 12th January 2020 with a flying altitude of 100 m and ii) on 4th February 2020 with a flying altitude of 40 m, both with a nadir camera position. The LOD2 buildings were generated in a part of Vrisa settlement consisted of 80 buildings using the footprints of the buildings, Digital Surface Models (DSMs), a Digital Elevation Model (DEM) and orthophoto maps of the area. Afterwards, a comparison was implemented between the LOD2 buildings of the two different scenarios, with their volumes and their heights. Subsequently, the heights of the LOD2 buildings were compared with the heights of the respective terrestrial laser scanner (TLS) models. Additionally, the roofs of the LOD2 buildings were evaluated through visual inspections. The results showed that the 65 of 80 LOD2 buildings were generated accurately in terms of their heights and roof types for the first scenario and 64 for the second respectively. Finally, the comparison of the results proved that the generation of post-earthquake LOD2 buildings can be achieved with the appropriate UAS data acquired at a flying altitude of 100 m and they are not affected significantly by a lower one altitude.


Author(s):  
R. Roschlaub ◽  
J. Batscheider

The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.


2021 ◽  
Author(s):  
Yipeng Yuan

Demand for three-dimensional (3D) urban models keeps growing in various civil and military applications. Topographic LiDAR systems are capable of acquiring elevation data directly over terrain features. However, the task of creating a large-scale virtual environment still remains a time-consuming and manual work. In this thesis a method for 3D building reconstruction, consisting of building roof detection, roof outline extraction and regularization, and 3D building model generation, directly from LiDAR point clouds is developed. In the proposed approach, a new algorithm called Gaussian Markov Random Field (GMRF) and Markov Chain Monte Carlo (MCMC) is used to segment point clouds for building roof detection. The modified convex hull (MCH) algorithm is used for the extraction of roof outlines followed by the regularization of the extracted outlines using the modified hierarchical regularization algorithm. Finally, 3D building models are generated in an ArcGIS environment. The results obtained demonstrate the effectiveness and satisfactory accuracy of the developed method.


2021 ◽  
Vol 13 (21) ◽  
pp. 4430
Author(s):  
Marko Bizjak ◽  
Borut Žalik ◽  
Niko Lukač

This paper aims to automatically reconstruct 3D building models on a large scale using a new approach on the basis of half-spaces, while making no assumptions about the building layout and keeping the number of input parameters to a minimum. The proposed algorithm is performed in two stages. First, the airborne LiDAR data and buildings’ outlines are preprocessed to generate buildings’ base models and the corresponding half-spaces. In the second stage, the half-spaces are analysed and used for shaping the final 3D building model using 3D Boolean operations. In experiments, the proposed algorithm was applied on a large scale, and its’ performance was inspected on a city level and on a single building level. Accurate reconstruction of buildings with various layouts were demonstrated and limitations were identified for large-scale applications. Finally, the proposed algorithm was validated on an ISPRS benchmark dataset, where a RMSE of 1.31 m and completeness of 98.9 % were obtained.


2012 ◽  
Vol 166-169 ◽  
pp. 2631-2636
Author(s):  
Sai Nan Ren ◽  
Jian Hua Mao ◽  
Ling Ye ◽  
Xue Feng Liu

3-dimensional (3D) city model is increasingly popular in urban planning and disaster management. City Geographic Markup Language (CityGML) is an open data model and XML-based format for the representation and exchange of virtual 3D city model. This paper analyzed the modeling mechanism of 3D CityGML building model in LOD4 (Level of Detail) and proposed a method representing a fire event in CityGML. Our method included three operations:1) editing of building’s hierarchy and attributes information; 2) representing of semantic information of buildings surfaces, roof height and interior furniture; 3) representing of fire event by a vivid icon. With our method, 3D building model and indoor fire event can be both represented in CityGML, which is important to analyses urban emergency events.


Author(s):  
R. Roschlaub ◽  
J. Batscheider

The federal governments of Germany endeavour to create a harmonized 3D building data set based on a common application schema (the AdV-CityGML-Profile). The Bavarian Agency for Digitisation, High-Speed Internet and Surveying has launched a statewide 3D Building Model with standardized roof shapes for all 8.1 million buildings in Bavaria. For the acquisition of the 3D Building Model LiDAR-data or data from Image Matching are used as basis in addition with the building ground plans of the official cadastral map. The data management of the 3D Building Model is carried out by a central database with the usage of a nationwide standardized CityGML-Profile of the AdV. The update of the 3D Building Model for new buildings is done by terrestrial building measurements within the maintenance process of the cadaster and from image matching. In a joint research project, the Bavarian State Agency for Surveying and Geoinformation and the TUM, Chair of Geoinformatics, transformed an AdV-CityGML-Profilebased test data set of Bavarian LoD2 building models into an INSPIRE-compliant schema. For the purpose of a transformation of such kind, the AdV provides a data specification, a test plan for 3D Building Models and a mapping table. The research project examined whether the transformation rules defined in the mapping table, were unambiguous and sufficient for implementing a transformation of LoD2 data based on the AdV-CityGML-Profile into the INSPIRE schema. The proof of concept was carried out by transforming production data of the Bavarian 3D Building Model in LoD2 into the INSPIRE BU schema. In order to assure the quality of the data to be transformed, the test specifications according to the test plan for 3D Building Models of the AdV were carried out. The AdV mapping table was checked for completeness and correctness and amendments were made accordingly.


2014 ◽  
Vol 71 (4) ◽  
Author(s):  
R. Akmaliaa ◽  
H. Setan ◽  
Z. Majid ◽  
D. Suwardhi

Nowadays, 3D city models are used by the increasing number of applications. Most applications require not only geometric information but also semantic information. As a standard and tool for 3D city model, CityGML, provides a method for storing and managing both geometric and semantic information. Moreover, it also provides the multi-scale representation of 3D building model for efficient visualization. In CityGML, building models are represented in five LODs (Level of Detail), start from LOD0, LOD1, LOD2, LOD3, and LOD4. Each level has different accuracy and detail requirement for visualization. Usually, for obtaining multi-LOD of 3D building model, several data sources are integrated. For example, LiDAR data is used for generating LOD0, LOD1, and LOD2 as close-range photogrammetry data is used for generating more detailed model in LOD3 and LOD4. However, using additional data sources is increasing cost and time consuming. Since the development of TLS (Terrestrial Laser Scanner), data collection for detailed model can be conducted in a relative short time compared to photogrammetry. Point cloud generated from TLS can be used for generating the multi-LOD of building model. This paper gives an overview about the representation of 3D building model in CityGML and also method for generating multi-LOD of building from TLS data. An experiment was conducted using TLS. Following the standard in CityGML, point clouds from TLS were processed resulting 3D model of building in different level of details. Afterward, models in different LOD were converted into XML schema to be used in CityGML. From the experiment, final result shows that TLS can be used for generating 3D models of building in LOD1, LOD2, and LOD3.


2021 ◽  
Vol 13 (6) ◽  
pp. 1107
Author(s):  
Linfu Xie ◽  
Han Hu ◽  
Qing Zhu ◽  
Xiaoming Li ◽  
Shengjun Tang ◽  
...  

Three-dimensional (3D) building models play an important role in digital cities and have numerous potential applications in environmental studies. In recent years, the photogrammetric point clouds obtained by aerial oblique images have become a major source of data for 3D building reconstruction. Aiming at reconstructing a 3D building model at Level of Detail (LoD) 2 and even LoD3 with preferred geometry accuracy and affordable computation expense, in this paper, we propose a novel method for the efficient reconstruction of building models from the photogrammetric point clouds which combines the rule-based and the hypothesis-based method using a two-stage topological recovery process. Given the point clouds of a single building, planar primitives and their corresponding boundaries are extracted and regularized to obtain abstracted building counters. In the first stage, we take advantage of the regularity and adjacency of the building counters to recover parts of the topological relationships between different primitives. Three constraints, namely pairwise constraint, triplet constraint, and nearby constraint, are utilized to form an initial reconstruction with candidate faces in ambiguous areas. In the second stage, the topologies in ambiguous areas are removed and reconstructed by solving an integer linear optimization problem based on the initial constraints while considering data fitting degree. Experiments using real datasets reveal that compared with state-of-the-art methods, the proposed method can efficiently reconstruct 3D building models in seconds with the geometry accuracy in decimeter level.


Author(s):  
D. Iwaszczuk ◽  
U. Stilla

Thermal infrared imagery of urban areas became interesting for urban climate investigations and thermal building inspections. Using a flying platform such as UAV or a helicopter for the acquisition and combining the thermal data with the 3D building models via texturing delivers a valuable groundwork for large-area building inspections. However, such thermal textures are useful for further analysis if they are geometrically correctly extracted. This can be achieved with a good coregistrations between the 3D building models and thermal images, which cannot be achieved by direct georeferencing. Hence, this paper presents methodology for alignment of 3D building models and oblique TIR image sequences taken from a flying platform. In a single image line correspondences between model edges and image line segments are found using accumulator approach and based on these correspondences an optimal camera pose is calculated to ensure the best match between the projected model and the image structures. Among the sequence the linear features are tracked based on visibility prediction. The results of the proposed methodology are presented using a TIR image sequence taken from helicopter in a densely built-up urban area. The novelty of this work is given by employing the uncertainty of the 3D building models and by innovative tracking strategy based on a priori knowledge from the 3D building model and the visibility checking.


2021 ◽  
Author(s):  
Yipeng Yuan

Demand for three-dimensional (3D) urban models keeps growing in various civil and military applications. Topographic LiDAR systems are capable of acquiring elevation data directly over terrain features. However, the task of creating a large-scale virtual environment still remains a time-consuming and manual work. In this thesis a method for 3D building reconstruction, consisting of building roof detection, roof outline extraction and regularization, and 3D building model generation, directly from LiDAR point clouds is developed. In the proposed approach, a new algorithm called Gaussian Markov Random Field (GMRF) and Markov Chain Monte Carlo (MCMC) is used to segment point clouds for building roof detection. The modified convex hull (MCH) algorithm is used for the extraction of roof outlines followed by the regularization of the extracted outlines using the modified hierarchical regularization algorithm. Finally, 3D building models are generated in an ArcGIS environment. The results obtained demonstrate the effectiveness and satisfactory accuracy of the developed method.


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