Semantically Enriched High Resolution Lod 3 Building Model Generation

Gruen, Armin; Schubiger, Simon; Qin, Rongjun; Schrotter, Gerhard; Xiong, Boli; Ling, Xiao; Xiao, Chen; Yao, Shuyu; Nuesch, F.

doi:10.5194/isprs-archives-xlii-4-w15-11-2019

Cited by 13 publications

(10 citation statements)

References 19 publications

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“…Using different raw data from the latest technologies and methods (such as laser scanning, photogrammetry) and parametric modelling, geometrically correct façades can be generated and the accuracy or deviation of the models from reality can be determined. The process and the detailed contents of the research packages can be found under Gruen et al (2019).…”

Section: More Detailed Modelsmentioning

confidence: 99%

The Digital Twin of the City of Zurich for Urban Planning

Schrotter¹,

Hürzeler²

2020

PFG

231

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Population growth will confront the City of Zurich with a variety of challenges in the coming years, as the increase in the number of inhabitants and jobs will lead to densification and competing land uses. The tasks for the city administration have become more complex, whereas tools and methods are often based on traditional, static approaches while involving a limited number of citizens and stakeholders in relevant decisions. The digital transformation of more and more pieces of the planning and decision-making process will make both increasingly more illustrative, easier to understand and more comprehensible. An important data basis for these processes is the digital twin of the City of Zurich. 3D spatial data and their models transform themes of the city, such as buildings, bridges, vegetation, etc., to the digital world, are being updated when required, and create advantages in digital space. These benefits need to be highlighted and published. An important step in public awareness is the release of 3D spatial data under Open Government Data. This allows the development of applications, the promotion of understanding, and the simplification of the creation of different collaborative platforms. By visualization and analysis of digital prototypes and the demonstration of interactions with the built environment, scenarios can be digitally developed and discussed in decision-making bodies. Questions about the urban climate can be simulated with the help of the digital twin and results can be linked to the existing 3D spatial data. Thus, the 3D spatial data set, the models and their descriptions through metadata become the reference and must be updated according to the requirements. Depending on requirements and questions, further 3D spatial data must be added. The description of the 3D spatial data and their models or the lifecycle management of the digital twin must be carried out with great care. Only in this way, decision processes can be supported in a comprehensible way. Keywords Digital twin • Digital transformation in urban planning • Densification • Urban climate • Architectural competition • Participation Zusammenfassung Das Bevölkerungswachstum stellt die Stadt Zürich in den kommenden Jahren vor vielfältige Herausforderungen, denn die Zunahme von Einwohnerinnen und Einwohnern sowie von Arbeitsplätzen führt unter anderem zu einer Verdichtung und konkurrierenden Nutzungen. Die Aufgaben für die Stadtverwaltung sind komplexer geworden, wohingegen die Werkzeuge und Methoden oft auf traditionellen, statischen Ansätzen beruhen und eine begrenzte Anzahl von Bürgern und Interessengruppen in relevante Entscheidungen einbeziehen. Durch Digitalisierung von Schritten in der Planung wird der planerische Prozess inklusive der Entscheidungsfindung ins Digitale transformiert und damit immer anschaulicher, verständlicher und nachvollziehbarer. Eine wichtige Datengrundlage für diese Prozesse ist der Digitale Zwilling der Stadt Zürich. Er bildet durch 3D Geodaten und deren Modelle Themen der Stadt, wie Gebäude, Brücken, V...

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Section: More Detailed Modelsmentioning

confidence: 99%

The Digital Twin of the City of Zurich for Urban Planning

Schrotter¹,

Hürzeler²

2020

PFG

231

View full text Add to dashboard Cite

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“…There is a significant body of literature focused on trying to automate building model reconstruction to make it low-cost, faster, accurate and easy to update. Nevertheless, many of the approaches proposed to solve the challenge of automatic generation of detailed models require a great deal of pre-and post-processing, therefore restricting their utilisation as standalone solutions [9].…”

Section: Introductionmentioning

confidence: 99%

Detailed Three-Dimensional Building Façade Reconstruction: A Review on Applications, Data and Technologies

et al. 2022

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Urban environments are regions of complex and diverse architecture. Their reconstruction and representation as three-dimensional city models have attracted the attention of many researchers and industry specialists, as they increasingly recognise the potential for new applications requiring detailed building models. Nevertheless, despite being investigated for a few decades, the comprehensive reconstruction of buildings remains a challenging task. While there is a considerable body of literature on this topic, including several systematic reviews summarising ways of acquiring and reconstructing coarse building structures, there is a paucity of in-depth research on the detection and reconstruction of façade openings (i.e., windows and doors). In this review, we provide an overview of emerging applications, data acquisition and processing techniques for building façade reconstruction, emphasising building opening detection. The use of traditional technologies from terrestrial and aerial platforms, along with emerging approaches, such as mobile phones and volunteered geography information, is discussed. The current status of approaches for opening detection is then examined in detail, separated into methods for three-dimensional and two-dimensional data. Based on the review, it is clear that a key limitation associated with façade reconstruction is process automation and the need for user intervention. Another limitation is the incompleteness of the data due to occlusion, which can be reduced by data fusion. In addition, the lack of available diverse benchmark datasets and further investigation into deep-learning methods for façade openings extraction present crucial opportunities for future research.

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“…LiDAR technology has proven its usefulness in multiple fields, such as architecture, heritage and environment, among others (Refs. [6][7][8][9][10]), thanks to its great capacity to acquire massive data with geometric and radiometric information simultaneously. However, this productivity in the acquisition contrasts with the difficulty of its processing, since it requires extensive technical knowledge and a high computational cost.…”

Section: Introductionmentioning

confidence: 99%

Automatic Generation of Urban Road 3D Models for Pedestrian Studies from LiDAR Data

et al. 2022

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The point clouds acquired with a mobile LiDAR scanner (MLS) have high density and accuracy, which allows one to identify different elements of the road in them, as can be found in many scientific references, especially in the last decade. This study presents a methodology to characterize the urban space available for walking, by segmenting point clouds from data acquired with MLS and automatically generating impedance surfaces to be used in pedestrian accessibility studies. Common problems in the automatic segmentation of the LiDAR point cloud were corrected, achieving a very accurate segmentation of the points belonging to the ground. In addition, problems caused by occlusions caused mainly by parked vehicles and that prevent the availability of LiDAR points in spaces normally intended for pedestrian circulation, such as sidewalks, were solved in the proposed methodology. The innovation of this method lies, therefore, in the high definition of the generated 3D model of the pedestrian space to model pedestrian mobility, which allowed us to apply it in the search for shorter and safer pedestrian paths between the homes and schools of students in urban areas within the Big-Geomove project. Both the developed algorithms and the LiDAR data used are freely licensed for their use in further research.

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Semantically Enriched High Resolution Lod 3 Building Model Generation

Cited by 13 publications

References 19 publications

The Digital Twin of the City of Zurich for Urban Planning

The Digital Twin of the City of Zurich for Urban Planning

Detailed Three-Dimensional Building Façade Reconstruction: A Review on Applications, Data and Technologies

Automatic Generation of Urban Road 3D Models for Pedestrian Studies from LiDAR Data

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