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Multi-Agent-Based Urban Vegetation Design
Urban vegetation is an essential element of the urban city pedestrian walkway. Despite city forest regulations and urban planning best practices, vegetation planning lacks clear comprehension and compatibility with other urban elements surrounding it. Urban planners and academic researchers currentl...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246495/ https://www.ncbi.nlm.nih.gov/pubmed/32354149 http://dx.doi.org/10.3390/ijerph17093075 |
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author | Ali, Ahmed Khairadeen Song, Hayub Lee, One Jae Kim, Eun Seok Mohammed Ali, Haneen Hashim |
author_facet | Ali, Ahmed Khairadeen Song, Hayub Lee, One Jae Kim, Eun Seok Mohammed Ali, Haneen Hashim |
author_sort | Ali, Ahmed Khairadeen |
collection | PubMed |
description | Urban vegetation is an essential element of the urban city pedestrian walkway. Despite city forest regulations and urban planning best practices, vegetation planning lacks clear comprehension and compatibility with other urban elements surrounding it. Urban planners and academic researchers currently devote vital attention to include most of the urban elements and their impact on the occupants and the environment in the planning stage of urban development. With the advancement in computational design, they have developed various algorithms to generate design alternatives and measure their impact on the environment that meets occupants’ needs and perceptions of their city. In particular, multi-agent-based simulations show great promise in developing rule compliance with urban vegetation design tools. This paper proposed an automatic urban vegetation city rule compliance approach for pedestrian pathway vegetation, leveraging multi-agent system and algorithmic modeling tools. This approach comprises three modules: rule compliance (T-Rule), street vegetation design tool (T-Design), and multi-agent alternative generation (T-Agent). Notably, the scope of the paper is limited to trees, shrubbery, and seating area configurations in the urban pathway context. To validate the developed design tool, a case study was tested, and the vegetation design tool generated the expected results successfully. A questionnaire was conducted to give feedback on the use of the developed tool for enhancing positive experience of the developed tool. It is anticipated that the proposed tool has the potential to aid urban planners in decision-making and develop more practical vegetation planting plans compared with the conventional Two-Dimensional (2D) plans, and give the city occupants the chance to take part in shaping their city by merely selecting from predefined parameters in a user interface to generate their neighborhood pathway vegetation plans. Moreover, this approach can be extended to be embedded in an interactive map where city occupants can shape their neighborhood greenery and give feedback to urban planners for decision-making. |
format | Online Article Text |
id | pubmed-7246495 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72464952020-06-11 Multi-Agent-Based Urban Vegetation Design Ali, Ahmed Khairadeen Song, Hayub Lee, One Jae Kim, Eun Seok Mohammed Ali, Haneen Hashim Int J Environ Res Public Health Article Urban vegetation is an essential element of the urban city pedestrian walkway. Despite city forest regulations and urban planning best practices, vegetation planning lacks clear comprehension and compatibility with other urban elements surrounding it. Urban planners and academic researchers currently devote vital attention to include most of the urban elements and their impact on the occupants and the environment in the planning stage of urban development. With the advancement in computational design, they have developed various algorithms to generate design alternatives and measure their impact on the environment that meets occupants’ needs and perceptions of their city. In particular, multi-agent-based simulations show great promise in developing rule compliance with urban vegetation design tools. This paper proposed an automatic urban vegetation city rule compliance approach for pedestrian pathway vegetation, leveraging multi-agent system and algorithmic modeling tools. This approach comprises three modules: rule compliance (T-Rule), street vegetation design tool (T-Design), and multi-agent alternative generation (T-Agent). Notably, the scope of the paper is limited to trees, shrubbery, and seating area configurations in the urban pathway context. To validate the developed design tool, a case study was tested, and the vegetation design tool generated the expected results successfully. A questionnaire was conducted to give feedback on the use of the developed tool for enhancing positive experience of the developed tool. It is anticipated that the proposed tool has the potential to aid urban planners in decision-making and develop more practical vegetation planting plans compared with the conventional Two-Dimensional (2D) plans, and give the city occupants the chance to take part in shaping their city by merely selecting from predefined parameters in a user interface to generate their neighborhood pathway vegetation plans. Moreover, this approach can be extended to be embedded in an interactive map where city occupants can shape their neighborhood greenery and give feedback to urban planners for decision-making. MDPI 2020-04-28 2020-05 /pmc/articles/PMC7246495/ /pubmed/32354149 http://dx.doi.org/10.3390/ijerph17093075 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ali, Ahmed Khairadeen Song, Hayub Lee, One Jae Kim, Eun Seok Mohammed Ali, Haneen Hashim Multi-Agent-Based Urban Vegetation Design |
title | Multi-Agent-Based Urban Vegetation Design |
title_full | Multi-Agent-Based Urban Vegetation Design |
title_fullStr | Multi-Agent-Based Urban Vegetation Design |
title_full_unstemmed | Multi-Agent-Based Urban Vegetation Design |
title_short | Multi-Agent-Based Urban Vegetation Design |
title_sort | multi-agent-based urban vegetation design |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246495/ https://www.ncbi.nlm.nih.gov/pubmed/32354149 http://dx.doi.org/10.3390/ijerph17093075 |
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