Agent-Based Modeling in Coupled Human and Natural Systems (CHANS): Lessons from a Comparative Analysis

An, Li; Zvoleff, Alex; Liu, Jianguo; Axinn, William G.

doi:10.1080/00045608.2014.910085

Cited by 76 publications

(42 citation statements)

References 83 publications

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“…Other closely related subjects, for example land use models are comprehensively reviewed by [24,25]. From a techniques perspective, we are strictly focusing on ABM.…”

Section: Introductionmentioning

confidence: 99%

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

Heppenstall

Malleson

Crooks

2016

Systems

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Cities are complex systems, comprising of many interacting parts. How we simulate and understand causality in urban systems is continually evolving. Over the last decade the agent-based modeling (ABM) paradigm has provided a new lens for understanding the effects of interactions of individuals and how through such interactions macro structures emerge, both in the social and physical environment of cities. However, such a paradigm has been hindered due to computational power and a lack of large fine scale datasets. Within the last few years we have witnessed a massive increase in computational processing power and storage, combined with the onset of Big Data. Today geographers find themselves in a data rich era. We now have access to a variety of data sources (e.g., social media, mobile phone data, etc.) that tells us how, and when, individuals are using urban spaces. These data raise several questions: can we effectively use them to understand and model cities as complex entities? How well have ABM approaches lent themselves to simulating the dynamics of urban processes? What has been, or will be, the influence of Big Data on increasing our ability to understand and simulate cities? What is the appropriate level of spatial analysis and time frame to model urban phenomena? Within this paper we discuss these questions using several examples of ABM applied to urban geography to begin a dialogue about the utility of ABM for urban modeling. The arguments that the paper raises are applicable across the wider research environment where researchers are considering using this approach.

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“…Other closely related subjects, for example land use models are comprehensively reviewed by [24,25]. From a techniques perspective, we are strictly focusing on ABM.…”

Section: Introductionmentioning

confidence: 99%

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

Heppenstall

Malleson

Crooks

2016

Systems

View full text Add to dashboard Cite

show abstract

“…ABMs, as reviewed earlier, are also applicable to spatial panel data analysis (Table 2), even though the modeler is more interested in using an ABM to predict or explain the observed spatial patterns (e.g., habitat or land use and cover at discrete times) rather than in time paths or movement patterns of individual agents. We skip ABM in this section for brevity, though, while pointing out some literature about using ABMs in this manner (Parker et al 2003;An et al 2005;Brown et al 2005;Brown et al 2008;An et al 2014).…”

Section: Process-based Simulationsmentioning

confidence: 98%

Space–Time Analysis: Concepts, Quantitative Methods, and Future Directions

Tsou

Crook

et al. 2015

Annals of the Association of American Geographers

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“…When the "Sediment-chg-order bar" is set at "off", the thickness of all segments decreases simultaneously at a rate determined by rules 1-3 until it becomes zero (this option is primarily for the purpose of testing the model). To test the ABM, we compared the predicted segment elevations at discrete time steps with the March 2014 survey following the model verification and validation procedures in An et al (2005An et al ( , 2014. The simple test results show that the A C C E P T E D M A N U S C R I P T…”

Section: Accepted Manuscriptmentioning

confidence: 99%

“…This study also demonstrates how one integrative tool, the agent-based model, provides a framework to simulate geomorphological change. Although ABMs are already common in studies of socialecological systems (e.g., An et al, 2014;Brown et al, 2007), geomorphologists have only begun to explore their use. Challenges remain to gather sufficient data for both the physical and human systems -especially in quantifying human decision-making and behavior --to fully inform application of these models to adequately capture the dynamics of human-landscape systems.…”

Section: Accepted Manuscriptmentioning

confidence: 99%

Investigating feedbacks in human–landscape systems: Lessons following a wildfire in Colorado, USA

Chin

Florsheim

et al. 2016

Geomorphology

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Agent-Based Modeling in Coupled Human and Natural Systems (CHANS): Lessons from a Comparative Analysis

Cited by 76 publications

References 83 publications

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

“Space, the Final Frontier”: How Good are Agent-Based Models at Simulating Individuals and Space in Cities?

Space–Time Analysis: Concepts, Quantitative Methods, and Future Directions

Investigating feedbacks in human–landscape systems: Lessons following a wildfire in Colorado, USA

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