Feedback loops and types of adaptation in the modelling of land-use decisions in an agent-based simulation

2012 ◽  
Vol 27-28 ◽  
pp. 83-96 ◽  
Author(s):  
Quang Bao Le ◽  
Roman Seidl ◽  
Roland W. Scholz
Keyword(s):  
Land Use ◽  
Feedback Loops ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Use Decisions

scholarly journals MULTI-AGENT BASED SIMULATION OF OPTIMAL URBAN LAND USE ALLOCATION IN THE MIDDLE REACHES OF THE YANGTZE RIVER, CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 1089-1092 ◽  
Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Resource ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Use Allocation ◽  
Land Use Optimization ◽  
Multi Agent ◽  
Optimization Allocation

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

scholarly journals MULTI-AGENT BASED SIMULATION OF OPTIMAL URBAN LAND USE ALLOCATION IN THE MIDDLE REACHES OF THE YANGTZE RIVER, CHINA

2016 ◽  
Vol XLI-B8 ◽  
pp. 1089-1092
Author(s):  
Y. Zeng ◽  
W. Huang ◽  
W. Jin ◽  
S. Li
Keyword(s):  
Land Use ◽  
Urban Land ◽  
Urban Land Use ◽  
Land Resource ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Use Allocation ◽  
Land Use Optimization ◽  
Multi Agent ◽  
Optimization Allocation

The optimization of land-use allocation is one of important approaches to achieve regional sustainable development. This study selects Chang-Zhu-Tan agglomeration as study area and proposed a new land use optimization allocation model. Using multi-agent based simulation model, the future urban land use optimization allocation was simulated in 2020 and 2030 under three different scenarios. This kind of quantitative information about urban land use optimization allocation and urban expansions in future would be of great interest to urban planning, water and land resource management, and climate change research.

scholarly journals Impacts of land-use management on ecosystem services and biodiversity: an agent-based modelling approach

PeerJ ◽  
2016 ◽  
Vol 4 ◽  
pp. e2814 ◽  
Author(s):  
Thomas J. Habib ◽  
Scott Heckbert ◽  
Jeffrey J. Wilson ◽  
Andrew J. K. Vandenbroeck ◽  
Jerome Cranston ◽  
...  
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Ecosystem Services ◽  
Timber Harvest ◽  
Successful Implementation ◽  
Management Decisions ◽  
Agent Based ◽  
Agent Based Modelling ◽  
Land Use Decisions ◽  
Modelling System

The science of ecosystem service (ES) mapping has become increasingly sophisticated over the past 20 years, and examples of successfully integrating ES into management decisions at national and sub-national scales have begun to emerge. However, increasing model sophistication and accuracy—and therefore complexity—may trade-off with ease of use and applicability to real-world decision-making contexts, so it is vital to incorporate the lessons learned from implementation efforts into new model development. Using successful implementation efforts for guidance, we developed an integrated ES modelling system to quantify several ecosystem services: forest timber production and carbon storage, water purification, pollination, and biodiversity. The system is designed to facilitate uptake of ES information into land-use decisions through three principal considerations: (1) using relatively straightforward models that can be readily deployed and interpreted without specialized expertise; (2) using an agent-based modelling framework to enable the incorporation of human decision-making directly within the model; and (3) integration among all ES models to simultaneously demonstrate the effects of a single land-use decision on multiple ES. We present an implementation of the model for a major watershed in Alberta, Canada, and highlight the system’s capabilities to assess a suite of ES under future management decisions, including forestry activities under two alternative timber harvest strategies, and through a scenario modelling analysis exploring different intensities of hypothetical agricultural expansion. By using a modular approach, the modelling system can be readily expanded to evaluate additional ecosystem services or management questions of interest in order to guide land-use decisions to achieve socioeconomic and environmental objectives.

scholarly journals Land-use change arising from rural land exchange: an agent-based simulation model

2014 ◽  
Vol 30 (2) ◽  
pp. 273-286 ◽  
Author(s):  
Martha M. Bakker ◽  
Shah Jamal Alam ◽  
Jerry van Dijk ◽  
Mark D. A. Rounsevell
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Simulation Model ◽  
Rural Land ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Land Exchange

scholarly journals Improving Representation of Decision Rules in LUCC-ABM: An Example with an Elicitation of Farmers’ Decision Making for Landscape Restoration in Central Malawi

2020 ◽  
Vol 12 (13) ◽  
pp. 5380 ◽  
Author(s):  
Ida Nadia S. Djenontin ◽  
Leo C. Zulu ◽  
Arika Ligmann-Zielinska
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Decision Rules ◽  
Well Being ◽  
Agricultural Landscapes ◽  
Agent Based ◽  
Social Actors ◽  
Land Use Decisions ◽  
Decision Making Processes ◽  
Restoration Practices

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.

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