Exploring normative scenarios of land use development decisions with an agent-based simulation laboratory

2010 ◽  
Vol 34 (5) ◽  
pp. 409-423 ◽  
Author(s):  
Arika Ligmann-Zielinska ◽  
Piotr Jankowski
Keyword(s):  
Land Use ◽  
Agent Based Simulation ◽  
Agent Based ◽  
Simulation Laboratory ◽  
Land Use Development

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 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 Simulation of Land-Use Development, Using a Risk-Regarding Agent-Based Model

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
F. Hosseinali ◽  
A. A. Alesheikh ◽  
F. Nourian
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Information Systems ◽  
Geographic Information Systems ◽  
Spatial Data ◽  
Agent Based Model ◽  
Or Education ◽  
Agent Based ◽  
New Methods ◽  
Land Use Development

The aim of this paper is to study the spatial consequences of applying different Attitude Utility Functions (AUFs), which reflect peoples’ simplified psychological frames, to investment plans in land-use decision making. For this purpose, we considered and implemented an agent-based model with new methods for searching landscapes, for selecting parcels to develop, and for allowing competitions among agents. Besides this, GIS (Geographic Information Systems) as a versatile and powerful medium of analyzing and representing spatial data is used. Our model is implemented on an artificial landscape in which land is being developed by agents. The agents are assumed to be mobile developers that are equipped with several land-related objectives. In this paper, agents mimic various risk-bearing attitudes and sometimes compete for developing the same parcel. The results reveal that patterns of land-use development are different in the two cases of regarding and disregarding AUFs. Therefore, it is considered here that using the attitudes of people towards risk helps the model to better simulate the decision making of land-use developers. The different attitudes toward risk used in this study can be attributed to different categories of developers based on sets of characteristics such as income, age, or education.

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