A data structure for scientific models of historical cities

Vaienti, Beatrice; Guhennec, Paul; Lenardo, Isabella di

doi:10.1145/3557919.3565813

Cited by 4 publications

(6 citation statements)

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“…This adaptation allows for the inclusion of all the required fields essential for the procedural generation of 3D models. This extension builds upon our initial proposal [25], incorporating improvements and additional features to support the refined level of modeling proposed in this contribution. The extension ensures compatibility between the scripts and the parameterization.…”

Section: Parameters Employed For the Procedural Modelingmentioning

confidence: 99%

“…Furthermore, we included fields to track the provenance of the parameters, ensuring transparency and traceability. To achieve this, we developed our own CityJSON extension, referred to as Historical CityJSON [25]. This extension underwent further refinement to align the attributes with the needs of the previously described LOD 2.1 level of modeling, which offers a higher level of detail in the representation of city elements.…”

Section: Introductionmentioning

confidence: 99%

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Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

et al. 2023

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The generation of 3D models depicting cities in the past holds great potential for documentation and educational purposes. However, it is often hindered by incomplete historical data and the specialized expertise required. To address these challenges, we propose a framework for historical city reconstruction. By integrating procedural modeling techniques and machine learning models within a Geographic Information System (GIS) framework, our pipeline allows for effective management of spatial data and the generation of detailed 3D models. We developed an open-source Python module that fills gaps in 2D GIS datasets and directly generates 3D models up to LOD 2.1 from GIS files. The use of the CityJSON format ensures interoperability and accommodates the specific needs of historical models. A practical case study using footprints of the Old City of Jerusalem between 1840 and 1940 demonstrates the creation, completion, and 3D representation of the dataset, highlighting the versatility and effectiveness of our approach. This research contributes to the accessibility and accuracy of historical city models, providing tools for the generation of informative 3D models. By incorporating machine learning models and maintaining the dynamic nature of the models, we ensure the possibility of supporting ongoing updates and refinement based on newly acquired data. Our procedural modeling methodology offers a streamlined and open-source solution for historical city reconstruction, eliminating the need for additional software and increasing the usability and practicality of the process.

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Section: Parameters Employed For the Procedural Modelingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

et al. 2023

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“…Aly; Tarek, 2016) até simulações energéticas (Calcerano et al, 2023) e reconstruções históricas (Vaienti et al, 2023).…”

Section: Possibilidadesunclassified

“…A metodologia HBIM permite simular virtualmente diferentes cenários de intervenção, oferecendo a oportunidade de testar e avaliar os impactos de diversas propostas de restauração antes da implementação real, por meio de modelos digitais 3D que integram informações geométricas com dados históricos, estruturais e materiais, proporcionando uma abordagem mais holística (Vaienti et al, 2023).…”

Section: Possibilidadesunclassified

Gestão do escopo em projetos de intervenção do patrimônio arquitetônico: integração das boas práticas do PMBOK com o manual de elaboração de projetos de preservação do patrimônio cultural e o contexto HBIM

Rimkus,

Cuperschmid

2023

Cad. Pedagógico

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A preservação do patrimônio arquitetônico, crucial para salvaguardar a herança cultural e histórica, enfrenta desafios únicos devido aos sistemas construtivos antigos, materiais diversos e patologias construtivas variadas. A adaptação a novos usos e conformidade com normas específicas aumentam a complexidade dessa tarefa. Apesar da importância, a gestão de projetos do patrimônio arquitetônico carece de aprofundamento. A gestão eficaz do escopo atua como guia essencial para alinhar partes interessadas, estabelece limites e orienta a equipe na realização de objetivos, sendo fundamental para o êxito na definição e gerenciamento de projetos. Este artigo visa fornecer subsídios aos gestores de Projetos de Intervenção no Patrimônio Arquitetônico, procurando integrar a metodologia Heritage Building Information Modeling (HBIM) com o processo de gerenciamento do escopo delineado pelo Project Management Body of Knowledge (PMBOK) e com as diretrizes do Manual de Elaboração de Projetos de Preservação do Patrimônio Cultural. Essa integração resultou em recomendações para boas práticas de gerenciamento do escopo em projetos de intervenções no patrimônio arquitetônico. Por fim, são destacadas as potencialidades, limitações e perspectivas futuras de HBIM nesse contexto.

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“…Vaienti et al. (2022) propose a CityJSON extension to model the temporal changes of the cities in 3D for historical studies.…”

Section: Introductionmentioning

confidence: 99%

Implementation of 3D spatial planning through the integration of the standards

Guler

2023

Transactions in GIS

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To plan future land use, zoning plans (i.e., spatial plans) are prepared to get the most out of land for both the public and the government. These plans manifest which facilities can be built and where they can be built on land based on defined requirements such as building height and road length. The Land Administration Domain Model (LADM) is well‐known and widely used standard for describing Rights, Restrictions, and Responsibilities (RRRs) with respect to land and buildings. The next version of the standard will contain the Spatial Plan Information (SPI) part to enable better land‐use planning. Three‐dimensional (3D) land‐use planning has gained attention to delineate detailed requirements inclusively and allow different spatial analysis that provides a basis for decisions in the planning. Data standards pertaining to 3D geoinformation are vital to put into practice 3D spatial planning. To this extent, CityJSON is proposed for the effortless and efficient use of 3D city models. This article thus first aims to extend the CityJSON schema based on the proposed SPI part of the LADM such that it allows modeling, storing, visualizing, and utilizing the features and attributes required for the implementation of 3D spatial planning. Then, the usability of the proposed extension schema is demonstrated by the real‐world use cases that benefit from the exemplary CityJSON files that are created based on approved zoning plans in the country. The results of this study show that there is an important opportunity coming from the integration of international standards that enables semantic information along with their spatial counterparts within 3D spatial planning.

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A data structure for scientific models of historical cities

Cited by 4 publications

References 6 publications

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Machine-Learning-Enhanced Procedural Modeling for 4D Historical Cities Reconstruction

Gestão do escopo em projetos de intervenção do patrimônio arquitetônico: integração das boas práticas do PMBOK com o manual de elaboração de projetos de preservação do patrimônio cultural e o contexto HBIM

Implementation of 3D spatial planning through the integration of the standards

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