The Regional Multi-Agent Simulator (RegMAS): an open-source spatially explicit model to assess the impact of agricultural policies

RegMAS (Regional Multi Agent Simulator) is an open-source spatially explicit multi-agent model framework specifically designed for long-term simulations of the effects of policies on agricultural systems. Using iterated conventional optimisation problems as agents’ behavioural rules, it allows for a bidirectional integration between geophysical and social models where spatially-distributed characteristics are taken into account in the programming problem of the optimising agents. With RegMAS it is possible to simulate the local specific response to a given policy (or scenario), where policies, together with macro and regional characteristics, are read into the program in specially formatted spreadsheets and standard GIS files. The paper presents the model logic and structure and describes its functioning by applying it to a case-study, where RegMAS results are compared with conventional agent-based modelling to demonstrate the advantages of spatial explicitness. The simulation refers to the impact of the recent “Health Check” of the CAP on farm structures, income and land use in a hilly area of a central Italian region (Marche).Agent-Based Modelling; Mathematical Programming; Explicit Spatial Analysis; Common Agricultural Policy

Agent-Based Urban Land Markets: Agent's Pricing Behavior, Land Prices and Urban Land Use Change

We present a new bilateral agent-based land market model, which moves beyond previous work by explicitly modeling behavioral drivers of land-market transactions on both the buyer and seller sides; formation of bid prices (of buyers) and ask prices (of sellers); and the relative division of the gains from trade from the market transactions. We analyze model output using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression models. We first demonstrate that our model replicates relevant theoretical results of the traditional Alonso/Von Thünen model (structural validation). We then explore how urban morphology and land rents change as the relative market power of buyers and sellers changes (i.e., we move from a 'sellers' market' to a 'buyers' market'). We demonstrate that these strategic price dynamics have differential effects on land rents, but both lead to increased urban expansion

Microeconomic Motives of Land Use Change in Coastal Zone Area: Agent Based Modelling Approach

Economic growth causes growing urbanization, extension of tourist sector, infrastructure and change of natural landscape. These processes of land use change attract even more attention if they take place in coastal zone area. In that case not only the efficient allocation and preservation of natural area, but also reduction of potential damage from flooding is important. Driven forces of land use at macro and micro levels should be taken into account. This paper presents an agent based model (ABM), which is designed to simulate land use change in coastal zone area based of human behaviour. The aim is to understand motives, types of connections and interactions between different actors and natural environment in order to get a feeling how different policy options and natural conditions might affect land use configuration. Microeconomic motives of land use decisions are in the focus of the research. Individual land use decisions are guided by economic and geomorphologic conditions, spatial planning and coastal protection policy. Each location choice is done according to a set of defined rules and land attributes. Space is represented as a grid of cells. Self-interested economic agents interact with each other trying to benefit from a certain type of land-use. We introduce the perception of risk of flooding in the model of land use as an innovative aspect of ABM simulations for water management problems. Based on decisions of spatially distributed individual economic agents operating in a policy framework, the model produces aggregated land-use patterns as an outcome. Understanding the factors that affect land use decisions will help policy makers design incentives to achieve policy objectives in coastal zone area. The proposed ABM will be applied to a study area in the province of North Holland in the Netherlands

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Agent-Based Urban Land Markets: Agent\'s Pricing Behavior, Land Prices and Urban Land Use Change

We present a new bilateral agent-based land market model, which moves beyond previous work by explicitly modeling behavioral drivers of land-market transactions on both the buyer and seller side; formation of bid prices (of buyers) and ask prices (of sellers); and the relative division of the gains from trade from the market transactions. We analyze model output using a series of macro-scale economic and landscape pattern measures, including land rent gradients estimated using simple regression models. We first demonstrate that our model replicates relevant theoretical results of the traditional Alonso/Von Th�nen model (structural validation). We then explore how urban morphology and land rents change as the relative market power of buyers and sellers changes (i.e., we move from a \'sellers\' market\' to a \'buyers\' market\'). We demonstrate that these strategic price dynamics have differential effects on land rents, but both lead to increased urban expansion.Location Choice, Urban Land Market, Agent-Based Computational Economics, Land Use, Land Rent Gradient, Spatial Simulation

Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future

Short-term Farm Level Adaptations of EU15 Agricultural Supply to Climate Change

Assessing climate change impact on agriculture is a complex task involving a wide range of economical and physical processes, leading to significant uncertainties. At European scale, climate change impacts on agricultural supply have been appraised to be of relatively less important driver by the end of century compared to other global drivers. However these diagnoses are incomplete due to a limited representation of both spatial heterogeneity in important determinants of agricultural supply (soil, management practices and producer typology) and fine scale processes such as farm scale autonomous adaptation. We propose a complementary approach based on a modeling framework including a spatially explicit representation of productivity and producer behavior with regard to heterogeneity in soil, climate, and producer socio-economic context to appraise climate change impacts including autonomous farm-scale adaptations of EU15 agricultural supply to climate change. Our results suggest that without accounting for autonomous adaptation European agricultural supply may have interesting resilience properties at an aggregated scale despite significant heterogeneity at smaller resolution. Accounting for autonomous adaptations result in significant yield gains, and may lead to (i) a significant increase in the relative profitability of crops compared to other land-covers, thus possibly increasing its agricultural land-use share over other land covers, and (ii) an increase in total European production which may have impacts on agricultural goods markets, thus highlighting the need for integrating fine scale processes such as autonomous adaptation.Environmental Economics and Policy, Farm Management,

Spatial Economic Analysis in Data-Rich Environments

Controlling for spatial effects in micro-economic studies of consumer and producer behavior necessitates a range of analytical modifications ranging from modest changes in data collection and the definition of variables to dramatic changes in the modeling of consumer and producer decision-making. This paper discusses conceptual, empirical, and data issues involved in modeling the spatial aspects of economic behavior in data rich environments. Attention is given to established and emerging agricultural economic applications of spatial data and spatial econometric methods at the micro-scale. Recent applications of individual and household data are featured, including models of land-use change at the urban-rural interface, agricultural land values, and technological change and technology adoption.Research Methods/ Statistical Methods, C21, Q10, Q12, Q15, Q56,