Agent-Based Simulations of Smallholder Decision-Making in Land Use Change/Cover (LUCC) Problem

2017 ◽  
pp. 97-107 ◽  
Author(s):  
Manahan Siallagan ◽  
Niken Prasasti Martono ◽  
Utomo Sarjono Putro
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Land Use Change ◽  
Agent Based ◽  
Agent Based Simulations

scholarly journals Theoretical foundations of human decision-making in agent-based land use models – A review

2017 ◽  
Vol 87 ◽  
pp. 39-48 ◽  
Author(s):  
J. Groeneveld ◽  
B. Müller ◽  
C.M. Buchmann ◽  
G. Dressler ◽  
C. Guo ◽  
...  
Keyword(s):  
Decision Making ◽  
Land Use ◽  
Agent Based ◽  
Human Decision ◽  
Land Use Models ◽  
Theoretical Foundations

An open framework for agent based modelling of agricultural land use change

2014 ◽  
Vol 61 ◽  
pp. 19-38 ◽  
Author(s):  
Dave Murray-Rust ◽  
Derek T. Robinson ◽  
Eleonore Guillem ◽  
Eleni Karali ◽  
Mark Rounsevell
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Agricultural Land ◽  
Agricultural Land Use ◽  
Agent Based ◽  
Open Framework ◽  
Agent Based Modelling

scholarly journals How model paradigms affect our representation of future land-use change

2020 ◽  
Author(s):  
Calum Brown ◽  
Ian Holman ◽  
Mark Rounsevell
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
System Development ◽  
Active Management ◽  
Integrated Modelling ◽  
Agent Based Model ◽  
Agent Based ◽  
Modelling Framework ◽  
Land Use Models ◽  
Landscape Scales

Abstract. Land use models operating at regional to global scales are almost exclusively based on the single paradigm of economic optimisation. Models based on different paradigms are known to produce very different results, but these are not always equivalent or attributable to particular assumptions. In this study, we compare two pan-European land use models that are based on the same integrated modelling framework and utilise the same climatic and socio-economic scenarios, but which adopt fundamentally different model paradigms. One of these is a constrained optimising economic-equilibrium model and the other is a stochastic agent-based model. We run both models for a range of scenario combinations and compare their projections of spatial and aggregate land use change and ecosystem service supply. We find that the agent-based model projects more multifunctional and heterogeneous landscapes in most scenarios, providing a wider range of ecosystem services at landscape scales, as agents make individual, time-dependent decisions that reflect economic and non-economic motivations. This tendency also results in food shortages under certain scenario conditions. The optimisation model, in contrast, maintains food supply through intensification of agricultural production in the most profitable areas, sometimes at the expense of active management in large, contiguous parts of Europe. We relate the principal differences observed to underlying model assumptions, and hypothesise that optimisation may be appropriate in scenarios that allow for coherent political and economic control of land systems, but not in scenarios where economic and other scenario conditions prevent the normal functioning of price signals and responses. In these circumstances, agent-based modelling allows explicit consideration of behavioural processes, but in doing so provides a highly flexible account of land system development that is harder to link to underlying assumptions. We suggest that structured comparisons of parallel, transparent but paradigmatically distinct models are an important method for better understanding the potential scope and uncertainties of future land use change.

Theory, Data, and Methods

2019 ◽  
pp. 156-202
Author(s):  
Eda Ustaoglu ◽  
Arif Çagdaş Aydinoglu
Keyword(s):  
Machine Learning ◽  
Land Use ◽  
Information System ◽  
Land Use Change ◽  
Model Development ◽  
Agent Based ◽  
Change Models ◽  
Multi Scale ◽  
Land Use Dynamics ◽  
Scale Characteristics

Land-use change models are tools to support analyses, assessments, and policy decisions concerning the causes and consequences of land-use dynamics, by providing a framework for the analysis of land-use change processes and making projections for the future land-use/cover patterns. There is a variety of modelling approaches that were developed from different disciplinary backgrounds. Following the reviews in the literature, this chapter focuses on various modelling tools and practices that range from pattern-based methods such as machine learning and GIS (Geographic Information System)-based approaches, to process-based methods such as structural economic or agent-based models. For each of these methods, an overview is given for the advances that have been progressed by geographers, natural and economy scientists in developing these models of spatial land-use change. It is noted that further progress is needed in terms of model development, and integration of models operating at various scales that better address the multi-scale characteristics of the land-use system.

Collective decision making, leadership, and collective intelligence: Tests with agent-based simulations and a Field study

2016 ◽  
Vol 27 (2) ◽  
pp. 218-241 ◽  
Author(s):  
Kristie A. McHugh ◽  
Francis J. Yammarino ◽  
Shelley D. Dionne ◽  
Andra Serban ◽  
Hiroki Sayama ◽  
...  
Keyword(s):  
Decision Making ◽  
Field Study ◽  
Collective Intelligence ◽  
Collective Decision ◽  
Intelligence Tests ◽  
Collective Decision Making ◽  
Agent Based ◽  
Agent Based Simulations

A Spatio-Temporal Storage Method for Land-Use Change

2014 ◽  
Vol 687-691 ◽  
pp. 3078-3082
Author(s):  
Ning Pan ◽  
Ke Wang ◽  
Jing Jing Tan
Keyword(s):  
Data Mining ◽  
Decision Making ◽  
Land Use ◽  
Land Use Change ◽  
Land Use Planning ◽  
Historical Data ◽  
Land Use Changes ◽  
Storage Method ◽  
Temporal Aspect ◽  
Spatio Temporal

Frequent land-use changes might produce a large amount of historical data which are valuable for data mining and decision-making. Based on the traditional Whole-state-recording Mode, the Special-state-recording Mode was proposed, focusing on the temporal aspect. This mode could optimize the land use database and reduce redundant change record. It could also improve data rollback and historical backtracking functions. The mode was successfully applied to land use planning in Zhejiang Province.

An agent-based approach to explore the effect of voluntary mechanisms on land use change: A case in rural Queensland, Australia

2010 ◽  
Vol 91 (12) ◽  
pp. 2615-2625 ◽  
Author(s):  
Diego Valbuena ◽  
Arnold K. Bregt ◽  
Clive McAlpine ◽  
Peter H. Verburg ◽  
Leonie Seabrook
Keyword(s):  
Land Use ◽  
Land Use Change ◽  
Agent Based
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