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Special Issue "Modelling and Simulation of Human-Environment Interactions"

A special issue of Sustainability (ISSN 2071-1050).

Deadline for manuscript submissions: closed (31 May 2021).

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editors

Dr. Philippe J. Giabbanelli
E-Mail Website
Guest Editor
Department of Computer Science & Software Engineering, Miami University, Oxford, OH 45056, USA
Interests: agent-based modeling; cellular automata; fuzzy cognitive maps; social simulations; system dynamics
Prof. Dr. Arika Ligmann-Zielinska
E-Mail Website
Guest Editor
Department of Geography, Environment, and Spatial Sciences, Michigan State University, Geography Building, 673 Auditorium Rd, East Lansing, MI 48824, USA
Interests: (spatial) agent-based modeling; sensitivity analysis; model development; spatial analysis; complex urban systems
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to announce the development of a Special Issue on “Modelling and Simulation of Human-Environment Interactions”. Computational models provide intelligent environmental decision support systems to understand how human decisions are shaped by, and contribute to changes in, the environment. The complexity of these systems is reflected by the abundance of open questions in modelling and simulation:

  • At the design stage, we need to identify the right set of methods (e.g., should we use Agent-Based Modeling, Fuzzy Cognitive Maps, or Hybrid Models?), deal with issues in the data (e.g., uncertainty, linking datasets, utilizing narratives on top surveys and questionnaires), and efficiently work with the community (e.g., how can we transparently engage stakeholders in participatory modeling?).
  • At the implementation stage, we need to create models that can perform simulations efficiently (e.g., to scale to a large population or geographical area), integrate with other systems, or support a high level of interactivity with decision-makers.
  • When results are generated, we need to account for uncertainty, analyze their output, and validate them depending on the social and environmental context of use.

We solicit papers for this Special Issue that broadly deal with such challenges by addressing open questions, providing novel case studies, or encourage interesting and challenging debates. Papers can be reviews, syntheses, viewpoints, meta-analyses, or original research. Theoretical and applied contributions may include, but are not limited to, the following areas:

  • Simulation models and techniques (e.g., Agent-Based Model, Cellular Automata, Fuzzy Cognitive Maps, System Dynamics) for human-environment interactions.
  • Using Artificial Intelligence techniques and systems to model human-environment interactions (e.g., case-based reasoning systems, machine learning, data mining).
  • Software or implementations covering issues of scalability, usability, or integration.
  • Methodologies for parts of the modelling process (e.g., design, analysis).
  • Engagement of participants (i.e. participatory modelling) in building or using models.

Dr. Philippe J. Giabbanelli
Dr. Arika Ligmann-Zielinska
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2000 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • agent-based model
  • artificial societies
  • decision support systems
  • fuzzy cognitive maps
  • environmental software
  • human-natural interactions
  • integrated assessment
  • model development
  • participatory modeling
  • social simulation

Published Papers (8 papers)

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Editorial

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Editorial
Editorial for the Special Issue on Modelling and Simulation of Human-Environment Interactions
Sustainability 2021, 13(23), 13405; https://doi.org/10.3390/su132313405 - 03 Dec 2021
Viewed by 245
Abstract
At the core of the Anthropocene lies human influence on the environment [...] Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)

Research

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Article
A Usability Study of Classical Mechanics Education Based on Hybrid Modeling: Implications for Sustainability in Learning
Sustainability 2021, 13(20), 11225; https://doi.org/10.3390/su132011225 - 12 Oct 2021
Viewed by 382
Abstract
A usability study evaluated the ease with which users interacted with an author-designed modeling and simulation program called STEPP (Scaffolded Training Environment for Physics Programming). STEPP is a series of educational modules for introductory algebra-based physics classes that allow students to model the [...] Read more.
A usability study evaluated the ease with which users interacted with an author-designed modeling and simulation program called STEPP (Scaffolded Training Environment for Physics Programming). STEPP is a series of educational modules for introductory algebra-based physics classes that allow students to model the motion of an object using Finite State Machines (FSMs). STEPP was designed to teach students to decompose physical systems into a few key variables such as time, position, and velocity and then encourages them to use these variables to define states (such as running a marathon) and transitions between these states (such as crossing the finish line). We report the results of a usability study on high school physics teachers that was part of a summer training institute. To examine this, 8 high school physics teachers (6 women, 2 men) were taught how to use our simulation software. Data from qualitative and quantitative measures revealed that our tool generally exceeded teacher’s expectations across questions assessing: (1) User Experience, (2) STEM-C Relevance, and (3) Classroom Applicability. Implications of this research for STEM education and the use of modeling and simulation to enhance sustainability in learning will be discussed. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Article
An Integrated Information System of Climate-Water-Migrations-Conflicts Nexus in the Congo Basin
Sustainability 2021, 13(16), 9323; https://doi.org/10.3390/su13169323 - 19 Aug 2021
Cited by 1 | Viewed by 642
Abstract
We present an integrated information system needed to address the climate-water-migration-conflict nexus in the Congo Basin. It is based on a rigorous and multidisciplinary methodological approach that consists of designing appropriate tools for field surveys and data collection campaigns, data analysis, creating a [...] Read more.
We present an integrated information system needed to address the climate-water-migration-conflict nexus in the Congo Basin. It is based on a rigorous and multidisciplinary methodological approach that consists of designing appropriate tools for field surveys and data collection campaigns, data analysis, creating a statistical database and creating a web interface with the aim to make this information system publicly available for users and stakeholders. The information system developed is a structured and organized set of quantitative and qualitative data on the climate-water-migration-conflict nexus and gender, consisting of primary data collected during field surveys. It contains 250 aggregated variables or 575 disaggregated variables, all grouped into 15 thematic areas, including identification; socio-demographic characteristics; access to resources; perception of climate change; perception of migration; financial inclusion (savings, access to credit and circulation of money); domination and control on water resources, land ownership and property rights, conflict resolution and community resilience; water uses; vulnerability to climate change; housing, household assets and household expenditure; food security; health, hygiene and sanitation; environmental risk management; women’s economic autonomy; and water transfer from the Congo Basin to Lake Chad. The information system can be used to model and understand the interface of human-environment interactions, and develop scenarios necessary to address the challenges of climate change and resilient development, while supporting key policy areas and strategies to foster effective stakeholder participation to ensure management and governance of climate and natural resources in the Congo Basin. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Article
Improving Model Predictions—Integration of Real-Time Sensor Data into a Running Simulation of an Agent-Based Model
Sustainability 2021, 13(13), 7000; https://doi.org/10.3390/su13137000 - 22 Jun 2021
Cited by 1 | Viewed by 770
Abstract
The current trend towards living in big cities contributes to an increased demand for efficient and sustainable space and resource allocation in urban environments. This leads to enormous pressure for resource minimization in city planning. One pillar of efficient city management is a [...] Read more.
The current trend towards living in big cities contributes to an increased demand for efficient and sustainable space and resource allocation in urban environments. This leads to enormous pressure for resource minimization in city planning. One pillar of efficient city management is a smart intermodal traffic system. Planning and organizing the various kinds of modes of transport in a complex and dynamically adaptive system such as a city is inherently challenging. By deliberately simplifying reality, models can help decision-makers shape the traffic systems of tomorrow. Meanwhile, Smart City initiatives are investing in sensors to observe and manage many kinds of urban resources, making up a part of the Internet of Things (IoT) that produces massive amounts of data relevant for urban planning and monitoring. We use these new data sources of smart cities by integrating real-time data of IoT sensors in an ongoing simulation. In this sense, the model is a digital twin of its real-world counterpart, being augmented with real-world data. To our knowledge, this is a novel instance of real-time correction during simulation of an agent-based model. The process of creating a valid mapping between model components and real-world objects posed several challenges and offered valuable insights, particularly when studying the interaction between humans and their environment. As a proof-of-concept for our implementation, we designed a showcase with bike rental stations in Hamburg-Harburg, a southern district of Hamburg, Germany. Our objective was to investigate the concept of real-time data correction in agent-based modeling, which we consider to hold great potential for improving the predictive capabilities of models. In particular, we hope that the chosen proof-of-concept informs the ongoing politically supported trends in mobility—away from individual and private transport and towards—in Hamburg. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Article
Simulating Urban Shrinkage in Detroit via Agent-Based Modeling
Sustainability 2021, 13(4), 2283; https://doi.org/10.3390/su13042283 - 20 Feb 2021
Cited by 1 | Viewed by 1160
Abstract
While the world’s total urban population continues to grow, not all cities are witnessing such growth—some are actually shrinking. This shrinkage has caused several problems to emerge, including population loss, economic depression, vacant properties and the contraction of housing markets. Such issues challenge [...] Read more.
While the world’s total urban population continues to grow, not all cities are witnessing such growth—some are actually shrinking. This shrinkage has caused several problems to emerge, including population loss, economic depression, vacant properties and the contraction of housing markets. Such issues challenge efforts to make cities sustainable. While there is a growing body of work on studying shrinking cities, few explore such a phenomenon from the bottom-up using dynamic computational models. To fill this gap, this paper presents a spatially explicit agent-based model stylized on the Detroit Tri-County area, an area witnessing shrinkage. Specifically, the model demonstrates how the buying and selling of houses can lead to urban shrinkage through a bottom-up approach. The results of the model indicate that, along with the lower level housing transactions being captured, the aggregated level market conditions relating to urban shrinkage are also denoted (i.e., the contraction of housing markets). As such, the paper demonstrates the potential of simulation for exploring urban shrinkage and potentially offers a means to test policies to achieve urban sustainability. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Article
Human Simulation and Sustainability: Ontological, Epistemological, and Ethical Reflections
Sustainability 2020, 12(23), 10039; https://doi.org/10.3390/su122310039 - 01 Dec 2020
Cited by 3 | Viewed by 806
Abstract
This article begins with a brief outline of recent advances in the application of computer modeling to sustainability research, identifying important gaps in coverage and associated limits in methodological capability, particularly in regard to taking account of the tangled human factors that are [...] Read more.
This article begins with a brief outline of recent advances in the application of computer modeling to sustainability research, identifying important gaps in coverage and associated limits in methodological capability, particularly in regard to taking account of the tangled human factors that are often impediments to a sustainable future. It then describes some of the ways in which a new transdisciplinary approach within “human simulation” can contribute to the further development of sustainability modeling, more effectively addressing such human factors through its emphasis on stakeholder, policy professional, and subject matter expert participation, and its focus on constructing more realistic cognitive architectures and artificial societies. Finally, the article offers philosophical reflections on some of the ontological, epistemological, and ethical issues raised at the intersection of sustainability research and social simulation, considered in light of the importance of human factors, including values and worldviews, in the modeling process. Based on this philosophical analysis, we encourage more explicit conversations about the value of naturalism and secularism in finding and facilitating effective and ethical strategies for sustainable development. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Article
Improving Representation of Decision Rules in LUCC-ABM: An Example with an Elicitation of Farmers’ Decision Making for Landscape Restoration in Central Malawi
Sustainability 2020, 12(13), 5380; https://doi.org/10.3390/su12135380 - 03 Jul 2020
Cited by 8 | Viewed by 1081
Abstract
Restoring interlocking forest-agricultural landscapes—forest-agricscapes—to sustainably supply ecosystem services for socio-ecological well-being is one of Malawi’s priorities. Engaging local farmers is crucial in implementing restoration schemes. While farmers’ land-use decisions shape land-use/cover and changes (LUCC) and ecological conditions, why and how they [...] Read more.
Restoring interlocking forest-agricultural landscapes—forest-agricscapes—to sustainably supply ecosystem services for socio-ecological well-being is one of Malawi’s priorities. Engaging local farmers is crucial in implementing restoration schemes. While farmers’ land-use decisions shape land-use/cover and changes (LUCC) and ecological conditions, why and how they decide to embrace restoration activities is poorly understood and neglected in forest-agricscape restoration. We analyze the nature of farmers’ restoration decisions, both individually and collectively, in Central Malawi using a mixed-method analysis. We characterize, qualitatively and quantitatively, the underlying contextual rationales, motives, benefits, and incentives. Identified decision-making rules reflect diverse and nuanced goal frames of relative importance that are featured in various combinations. We categorize the decision-making rules as: problem-solving oriented, resource/material-constrained, benefits-oriented, incentive-based, peers/leaders-influenced, knowledge/skill-dependent, altruistic-oriented, rules/norms-constrained, economic capacity-dependent, awareness-dependent, and risk averse-oriented. We link them with the corresponding vegetation- and non-vegetation-based restoration practices to depict the overall decision-making processes. Findings advance the representation of farmers’ decision rules and behavioral responses in computational agent-based modeling (ABM), through the decomposition of empirical data. The approach used can inform other modeling works attempting to better capture social actors’ decision rules. Such LUCC-ABMs are valuable for exploring spatially explicit outcomes of restoration investments by modeling such decision-making processes and policy scenarios. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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Review

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Review
Quantitative Modeling of Human Responses to Changes in Water Resources Availability: A Review of Methods and Theories
Sustainability 2021, 13(15), 8675; https://doi.org/10.3390/su13158675 - 03 Aug 2021
Cited by 1 | Viewed by 985
Abstract
In rural areas in developing countries where livelihoods directly depend on agriculture, shortage of water can have severe socio-economic and humanitarian consequences and has been suggested to result in conflict and migration. Understanding such responses is important for the development of effective water [...] Read more.
In rural areas in developing countries where livelihoods directly depend on agriculture, shortage of water can have severe socio-economic and humanitarian consequences and has been suggested to result in conflict and migration. Understanding such responses is important for the development of effective water management policies and other interventions. However, despite the availability of extensive knowledge on water-related human behavior, water resources planning studies do not always look beyond direct impacts. Therefore, this paper assesses literature on water-related human responses, the quantification and conceptualization methods and theories used, the scale at which models are applied, and the extent to which findings are used to make policy recommendations. We found system dynamics approaches mostly applied for policy evaluations, but often with a limited integration of human behavior beyond water use; agent-based models seem to be suited for policy analysis, but only limitedly applied for that purpose; and statistical studies to present the widest range of human responses and explanatory factors, but without making the behavioral mechanisms explicit. In fact, only a limited number of studies was based on behavioral theories. Based on these findings we recommend eight steps to facilitate quantification of human responses for water resources planning purposes. Full article
(This article belongs to the Special Issue Modelling and Simulation of Human-Environment Interactions)
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