A simulation-based design framework to iteratively analyze and shape urban landscapes using point cloud modeling

Urech, Philipp R.W.; Mughal, Muhammad Omer; Bartesaghi-Koc, Carlos

doi:10.1016/j.compenvurbsys.2021.101731

Cited by 16 publications

(8 citation statements)

References 60 publications

(64 reference statements)

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Section: Results and Analysismentioning

confidence: 99%

“…The adoption of CIM has evolved the discourse of urban design by providing a platform for better collaborations (Alashi and Koramaz, 2019; Cousins, 2017); supporting decision-making in urban landscaping design (Urech et al. , 2022; Kong et al.…”

Section: Results and Analysismentioning

confidence: 99%

“…3.2.9 Urban landscaping design. The adoption of CIM has evolved the discourse of urban design by providing a platform for better collaborations (Alashi and Koramaz, 2019;Cousins, 2017); supporting decision-making in urban landscaping design (Urech et al, 2022;Kong et al, 2022); analysing future design scenarios based on real-time data (Urech et al, 2020) and facilitating the design of safe, cost-effective and ecologically friendly environments (Yeo and Yee, 2016;Kim et al, 2016;Stojanovski et al, 2020). For instance, CIM facilitates the dynamic design of urban environments.…”

Section: City Informationmentioning

confidence: 99%

“…The use of digital tools and 3D models for urban designing has been around for decades; however, the majority of the objects such as buildings, vegetation, open spaces, streets, urban topographies, or water features presented in conventional 3D models are static, hence limiting applications for dynamic analytical purposes. Urech et al (2022) attempted to address this limitation by proposing a framework that enables City Information Modelling developing multiple design scenarios and dynamically evaluating the effectiveness of developed scenarios on urban landscapes. The framework first establishes a thorough geometric documentation of urban areas using laser-scanned point cloud modelling techniques and then converts the geometric data from point cloud models into voxels and meshes to allow for further dynamic analyses.…”

Section: City Informationmentioning

confidence: 99%

See 3 more Smart Citations

The uptake of City Information Modelling (CIM): a comprehensive review of current implementations, challenges and future outlook

Omrany

GhaffarianHoseini

Ghaffarianhoseini

et al. 2022

SASBE

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PurposeThis paper critically analysed 195 articles with the objectives of providing a clear understanding of the current City Information Modelling (CIM) implementations, identifying the main challenges hampering the uptake of CIM and providing recommendations for the future development of CIM.Design/methodology/approachThis paper adopts the PRISMA method in order to perform the systematic literature review.FindingsThe results identified nine domains of CIM implementation including (1) natural disaster management, (2) urban building energy modelling, (3) urban facility management, (4) urban infrastructure management, (5) land administration systems, (6) improvement of urban microclimates, (7) development of digital twin and smart cities, (8) improvement of social engagement and (9) urban landscaping design. 10; Further, eight challenges were identified that hinder the widespread employment of CIM including (1) reluctance towards CIM application, (2) data quality, (3) computing resources and storage inefficiency, (4) data integration between BIM and GIS and interoperability, (5) establishing a standardised workflow for CIM implementation, (6) synergy between all parties involved, (7) cybersecurity and intellectual property and (8) data management.Originality/valueThis is the first paper of its kind that provides a holistic understanding of the current implementation of CIM. The outcomes will benefit multiple target groups. First, urban planners and designers will be supplied with a status-quo understanding of CIM implementations. Second, this research introduces possibilities of CIM deployment for the governance of cities; hence the outcomes can be useful for policymakers. Lastly, the scientific community can use the findings of this study as a reference point to gain a comprehensive understanding of the field and contribute to the future development of CIM.

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Section: Results and Analysismentioning

confidence: 99%

Section: Results and Analysismentioning

confidence: 99%

Section: City Informationmentioning

confidence: 99%

Section: City Informationmentioning

confidence: 99%

See 2 more Smart Citations

The uptake of City Information Modelling (CIM): a comprehensive review of current implementations, challenges and future outlook

Omrany

GhaffarianHoseini

Ghaffarianhoseini

et al. 2022

SASBE

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“…For example, the use of 3D point cloud models opens a dialogue between landscape designers and planners (Urech et al, 2020). The potential of such digital models to assess the performance of urban design in relation with bundles of ecosystem services that contribute to resilience and sustainability is state of the art research (Alavipanah et al, 2017;Urech et al, 2022). While visual simulation of flowing ecosystem services (like water for example) using point cloud models is achievable (Vollmer, Costa, et al, 2015), visualizing other services like carbon storage remain a challenge.…”

Section: Informed Design Through the Science-design Loopmentioning

confidence: 99%

Science-design loop for the design of resilient urban landscapes

Salliou

Arborino²,

Nassauer

et al. 2023

SESMO

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Urban landscapes face significant challenges, as they must transform towards sustainability while remaining resilient. Urban landscape transformation is a complex task for landscape designers. They must not only create new solutions for landscapes but also ensure that their proposals are capable to deliver and maintain key ecosystems services over time and especially after shocks. In practice, designers must increase their dialogue with scientists and engineers to include expertise on ecosystems functions and services. Through science-design feedback loops, designers can be challenged by scientists’ models and simulations and thus create informed designs. Lastly, stakeholders also catalyse key steps of such a process, in particular by providing local expertise as well as co-constructing and validating the informed designs. In this paper, we introduce a roadmap, centred on an intensive interdisciplinary dialogue – a science-design loop. We illustrate the relevance of this roadmap with the analysis of five case studies about flood management and blue-green infrastructures. We analyse them according to the main steps of our roadmap and with the support of key interviews with experienced practitioners. First, this analysis provides an overview of best practices and challenges in the current urban landscape design world. But above all, we show the relevance of the proposed roadmap to muster science and design in a balanced manner in urban transformations.

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Optimal Design of Garden Landscape Space Environment Based on Interactive Genetic Algorithm

Chen

Wen

2023

Lecture Notes in Mechanical Engineering

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A simulation-based design framework to iteratively analyze and shape urban landscapes using point cloud modeling

Cited by 16 publications

References 60 publications

The uptake of City Information Modelling (CIM): a comprehensive review of current implementations, challenges and future outlook

The uptake of City Information Modelling (CIM): a comprehensive review of current implementations, challenges and future outlook

Science-design loop for the design of resilient urban landscapes

Optimal Design of Garden Landscape Space Environment Based on Interactive Genetic Algorithm

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