Multi-level agent-based modeling - A literature survey

During last decade, multi-level agent-based modeling has received significant and dramatically increasing interest. In this article we present a comprehensive and structured review of literature on the subject. We present the main theoretical contributions and application domains of this concept, with an emphasis on social, flow, biological and biomedical models.Comment: v2. Ref 102 added. v3-4 Many refs and text added v5-6 bibliographic statistics updated. v7 Change of the name of the paper to reflect what it became, many refs and text added, bibliographic statistics update

An Open-Source Microscopic Traffic Simulator

We present the interactive Java-based open-source traffic simulator available at www.traffic-simulation.de. In contrast to most closed-source commercial simulators, the focus is on investigating fundamental issues of traffic dynamics rather than simulating specific road networks. This includes testing theories for the spatiotemporal evolution of traffic jams, comparing and testing different microscopic traffic models, modeling the effects of driving styles and traffic rules on the efficiency and stability of traffic flow, and investigating novel ITS technologies such as adaptive cruise control, inter-vehicle and vehicle-infrastructure communication

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

Modeling Linkages Between Climate Policy and Land Use: An Overview

Agriculture and forestry play an important role in emitting and storing greenhouse gases. For an efficient and cost-effective climate policy it is therefore important to explicitly include land use, land use change, and forestry (LULUCF) in economy-climate models. This paper gives an overview and assessment of existing approaches to include land use, land-use change, and forestry into climate-economy models or to link economy-climate models to land-use models.Climate Change, Climate Policy, Modeling, Land Use

Hybrid Modeling: New Answers to Old Challenges

After nearly two decades of debate and fundamental disagreement, topdown and bottom-up energy-economy modelers, sometimes referred to as modeling ‘tribes', began to engage in productive dialogue in the mid-1990s (IPCC 2001). From this methodological conversation have emerged modeling approaches that offer a hybrid of the two perspectives. Yet, while individual publications over the past decade have described efforts at hybrid modeling, there has not as yet been a systematic assessment of their prospects and challenges. To this end, several research teams that explore hybrid modeling held a workshop in Paris on April 20–21, 2005 to share and compare the strategies and techniques that each has applied to the development of hybrid modeling. This special issue provides the results of the workshop and of follow-up efforts between different researchers to exchange ideas.climat ; modeling

A coupled terrestrial and aquatic biogeophysical model of the Upper Merrimack River watershed, New Hampshire, to inform ecosystem services evaluation and management under climate and land-cover change

Accurate quantification of ecosystem services (ES) at regional scales is increasingly important for making informed decisions in the face of environmental change. We linked terrestrial and aquatic ecosystem process models to simulate the spatial and temporal distribution of hydrological and water quality characteristics related to ecosystem services. The linked model integrates two existing models (a forest ecosystem model and a river network model) to establish consistent responses to changing drivers across climate, terrestrial, and aquatic domains. The linked model is spatially distributed, accounts for terrestrial–aquatic and upstream–downstream linkages, and operates on a daily time-step, all characteristics needed to understand regional responses. The model was applied to the diverse landscapes of the Upper Merrimack River watershed, New Hampshire, USA. Potential changes in future environmental functions were evaluated using statistically downscaled global climate model simulations (both a high and low emission scenario) coupled with scenarios of changing land cover (centralized vs. dispersed land development) for the time period of 1980–2099. Projections of climate, land cover, and water quality were translated into a suite of environmental indicators that represent conditions relevant to important ecosystem services and were designed to be readily understood by the public. Model projections show that climate will have a greater influence on future aquatic ecosystem services (flooding, drinking water, fish habitat, and nitrogen export) than plausible changes in land cover. Minimal changes in aquatic environmental indicators are predicted through 2050, after which the high emissions scenarios show intensifying impacts. The spatially distributed modeling approach indicates that heavily populated portions of the watershed will show the strongest responses. Management of land cover could attenuate some of the changes associated with climate change and should be considered in future planning for the region

Utilizing a cellular automaton model to explore the influence of coastal flood adaptation strategies on Helsinki's urbanization patterns

A cellular automaton model (SLEUTH-3r) is utilized to explore the impacts of coastal flood risk management strategies on the urbanization parameters of Helsinki's metropolitan area, at a 50-m spatial resolution by 2040. The current urbanization trend is characterized by the consolidation of existing built-up land and loss of inter- spersed green spaces, whereas the most intense growth is forecast inside the coastal flood risk areas. This base- line is compared to strategies that test various responses of the planning system to real estate market forces and the spatial distribution of flood risks. A set of scenarios translates property price effects of flood risk information into various attraction-repulsion areas in and adjacent to the floodplain, while a second set explores varying de- grees of restricting new growth in the flood risk zones without reference to the housing market. The simulations indicate that growth under all scenarios is distributed in a more fragmented manner relative to the baseline, which can be interpreted favorably regarding house prices and increased access to ecosystem ser- vices, although the indirect effects should also be considered. Demand for coastal flood-safe properties does not appear to automatically translate to refocusing of development toward those areas, unless planning interven- tions encourage this redistribution. The character of the planning system with respect to market drivers and the spatial distribution of risks and amenities is thus important. A mixture of market-based measures and moderate zoning interventions may be preferable for flood risk management and provide the necessary precision for adap- tation strategies.Peer reviewe

Urban land expansion model based on SLEUTH, a case study in Dongguan city, China

The SLEUTH urban model is developed with sets of predefined growing rules involving Spontaneous Growth, New Spreading Center Growth, Edge Growth, Road Influenced Growth and Self-modification. They are applied continuously to lead the urban simulation to a specific morphology. A SLEUTH land use model was set up to simulate urban growth trajectory of Dongguan city from 1997 to 2009. The accuracy of localized parameters was evaluated to illuminate the growth pattern of Dongguan. Two different scenarios were set to predict the urban development from 2022 to 2030. Edge Growth is the dominant force of Dongguan's urbanization: regions adjacent to growth centers are more likely to be urbanized than remote area in general. Rapid urban expansion takes up large amount of other land types, around 2030, urbanization will reach the critical state in spatial. Unlike excessive growth rate in scenario 1, the urbanization speed is obviously more reasonable and sustainable in scenario 2, which confirms SLEUTH urban model is a good assistant of urban planning to avoid willful expansion with a scenario forecast. To protect ecological environment and promoting sustainable development of the region, relevant decision makers should take effective strategies to control urban sprawl. By the set of forecast scenarios, SLEUTH can certainly predict future urban development as an auxiliary to urban planners and government.Dongguan is under rapid urbanization in these decades. SLEUTH is an urban land use model named after the six input layers (Slope, Land use, Excluded, Urban, Transportation and Hill shade), and it is applied for simulating how surrounding land use changes due to urban expansion. A SLEUTH model was coupled with multi-source GIS (Geographic Information Systems) and RS (Remote Sensing) data to simulate urban growth trajectory of Dongguan city from 1997 to 2009. The accuracy of localized parameters was evaluated to illuminate the growth pattern of Dongguan. Based on the hypothesis that the urbanization process is as fast as before, a historical scenario from 2010 to 2050 was built up to choose the suitable study periods. In order to prove SLEUTH is able to offer reasonable outcomes for urban plan, two different scenarios were set to predict the urban development from 2022 to 2030, which shows SLEUTH is able to offer reasonable outcomes to government policy makers. Finally, the dynamic mechanism of urban growth combined with local characteristics was discussed. Some suggestions were also proposed for future urban planning and policy making in this study