An Agent-Based Modelling Framework for Urban Agriculture

Ghandar, Adam; Theodoropoulos, Georgios; Zhong, Miner; Zhen, Bowen; Chen, Shijie; Gong, Yue; Ahmed, Ayyaz

doi:10.1109/wsc40007.2019.9004854

Cited by 6 publications

(5 citation statements)

References 38 publications

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“…Collaborative and participatory models are also considered for urban forest management [40], and systematic stakeholder-driven approaches are used for strategic siting through Multi-criteria Decision Analysis (MCDA) [39]. In recent years, there has been an emergence of studies focusing on modeling and visualizing decision-making processes using agent-based modeling [41], Interpretive Structural Modeling [42], robust optimization [43], and spatio-temporal modeling [44]. However, fewer studies consider the entire decision-making process of urban agriculture at the regeneration level.…”

Section: Overview Of Decision-making Methods In Urban Agriculturementioning

confidence: 99%

Integrated Decision-Making of Urban Agriculture within the Greyfield Regeneration Environments (UAGR)

Dong,

Lin

2024

Buildings

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Various urban environmental and social challenges have emerged during the rapid urban development. Urban agriculture has emerged as one of the practical solutions to address these urban issues and climate change. This study aims to establish a decision model for urban agriculture regeneration that can be applied to improve the implementation of related projects. The study first reviews existing research on Urban Agriculture within the Greyfield Regeneration Environments (UAGR) and outlines the processes involved, including project initiation, construction, and operation management. It identifies 25 factors influencing UAGR and employs the Fuzzy Delphi method (FDM) to prioritize them based on expert judgments. Subsequently, the interpretative structural model (ISM) analysis method is applied to analyze the interrelationships among the 11 most important factors. Matrix operations and MATLAB programming are utilized to establish the influence relationship model based on expert questionnaires to determine the influence between each pair of factors. This results in a hierarchically structured decision model for UAGR. Finally, the decision-making model is applied to analyze the case study in Shanghai and Hangzhou. As urban agricultural activities are proliferating in rapid urbanization, the establishment of a decision-making model for UAGR can offer practical guidance to practitioners, facilitating the development of urban agriculture and mitigating climate change.

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Section: Overview Of Decision-making Methods In Urban Agriculturementioning

confidence: 99%

Integrated Decision-Making of Urban Agriculture within the Greyfield Regeneration Environments (UAGR)

Dong,

Lin

2024

Buildings

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“…In the simulation tests included in this paper consumers initiate their shopping expeditions when stock is depleted to a threshold. Further discussion of the modelling framework is in an earlier conference paper [24].…”

Section: B Modelling Frameworkmentioning

confidence: 99%

“…The majority of applications of the digital twin concept are in manufacturing. Earlier versions of some of this work was introduced in earlier conference publications, see [4], [24] and [25], with the latter receiving the Best Paper Award in AsiaSim 2019. 2 The contributions of this article are summarized as follows:…”

Section: Introductionmentioning

confidence: 99%

A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics

et al. 2021

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There are many pressures on the global food system such as urbanization, climate change, and environmental degradation. Urban agriculture is an approach to producing food inside cities where, globally, more than half the worlds population live. It has been shown to have a range of potential benefits, for instance in reducing waste and logistics costs. Increased uptake of urban farming can even relieve pressure on the natural environment by reducing the burden of production required from farmland by creating space for it to recover from accumulated damage as a result of the use of unsustainable farming practices historically. This article describes an approach for a new type of decision support system suitable for urban farming production. We discuss differences between the requirements and the users of decision support in urban agriculture, and those of ordinary agribusiness enterprises. A case study is performed using a novel technology for urban farming: a cyber-physical implementation of aquaponics is enhanced with adaptive capabilities using a digital twin system and machine learning. Aquaponics is a farming technique that utilizes a harmonious nutrient exchange cycle for growing plants and fish together, while conserving water, and possibly without the need for soil or even sunlight. Empirical results are provided that evaluate the use of data driven decision analytics and a digital twin model to plan production from the aquaponic system during a three month trial. Another set of results evaluate a proposed modelling framework for large scale urban agriculture ecosystems. This concept forms the basis of the suggested approach for an urban farming decision support system that coordinates the activities of many independent producers to target collective goals.INDEX TERMS Decision support, urban agriculture, modelling, simulation, digital twin, Internet of Things, metaheuristics.

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“…Other authors have used ABM to study varied aspects of urban systems (e.g. Ghandar et al, 2019;Huang et al, 2014;Roy and Lees, 2020), including gentrification (Torrens and Nara, 2007), and questions in urban planning and geography (e.g. Crooks et al, 2018;Huynh et al, 2015;Johnson and Sieber 2011).…”

Section: Agent-based Modellingmentioning

confidence: 99%

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

Overwater

Yorke-Smith

2021

Environment and Planning B: Urban Analytics and City Science

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Gentrification, displacement and social exclusion are hot topics of debate in the city of Amsterdam, the Netherlands. A current phenomena is short-term rentals of private homes. In its peer-to-peer form, this phenomena has grown sharply, facilitated by services such as Airbnb. Its growth has caused controversies among communities in touristic areas of Amsterdam, since it contributes to a changed social fabric, increased housing prices and overall gentrification. In the Netherlands and elsewhere, municipal and national policy makers are interested to regulate short-term rentals. In order to provide insights into qualitative policy effects, we develop a micro-level agent-based simulation. Our spatial model simulates residential migration based on income and house pricing. The underlying economic theory is that of Smith’s rent-gap hypothesis. Our model is among the first agent-based approaches investigating this type of rental market, and the first to model a specific housing market, including social housing, in a geographically accurate way. Simulation analysis shows that the touristic rental market has caused considerable changes in housing prices and population development. We find that more lower income citizens remain in the city centre when regulation of the market is stronger, and that banning the touristic market restrains the overall increase in house prices, compared to the business-as-usual scenario. However, the feasibility of enforcement of regulation, and its libertarian consequences, must be considered.

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An Agent-Based Modelling Framework for Urban Agriculture

Cited by 6 publications

References 38 publications

Integrated Decision-Making of Urban Agriculture within the Greyfield Regeneration Environments (UAGR)

Integrated Decision-Making of Urban Agriculture within the Greyfield Regeneration Environments (UAGR)

A Decision Support System for Urban Agriculture Using Digital Twin: A Case Study With Aquaponics

Agent-based simulation of short-term peer-to-peer rentals: Evidence from the Amsterdam housing market

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