URBAN 3D MODELLING METHODS: A STATE-OF-THE-ART REVIEW

As urbanisation accelerates, the urban landscape reshapes at a fast pace. Consequently, the urban built environment continuously evolves horizontally as well as vertically. However, more attention in the field of spatial analysis is given to horizontal dynamics, despite the importance of geoinformat...

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Bibliographic Details
Main Authors: Ying, Y., Koeva, M. N., Kuffer, M., Zevenbergen, J. A.
Format: Conference Proceeding
Language:English
Subjects:
Data management
Data structures
Development potential
Dimensions
Interdisciplinary research
Interdisciplinary studies
Methods
Modelling
Spatial analysis
State-of-the-art reviews
Three dimensional models
Urban areas
Urban environments
Urbanization
User requirements
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Summary:As urbanisation accelerates, the urban landscape reshapes at a fast pace. Consequently, the urban built environment continuously evolves horizontally as well as vertically. However, more attention in the field of spatial analysis is given to horizontal dynamics, despite the importance of geoinformation in the vertical dimension. 3D modelling methods have gained popularity due to their powerful capability of capturing and analysing geoinformation in the vertical dimension and visualising objects lifelike in the urban built environment. Various urban applications with diverse 3D modelling methods at different research scales and purposes have emerged. However, there is no systematic overview of these different modelling methods. Therefore, it is imperative to provide an up-to-date review of these advances. In this paper, we aim to review urban 3D modelling methods widely used in the prior 5-year period (2015–2020). Our analysis focuses on five attributes, i.e., basic characteristics, data requirements, technical requirements, users requirements and ethical considerations. The discussion presents the current status of 3D modelling methods – a wide range of applications yet with substantial development potential. This paper closes with insights for future work regarding the necessities of 3D data structure support as well as interdisciplinary research, specifically for big data management and integration.
ISSN:1682-1750
2194-9034
DOI:10.5194/isprs-archives-XLIII-B4-2020-699-2020