Agent Based Modelling And Landscape Change

This book is a printed edition of the Special Issue "Agent-Based Modelling and Landscape Change" that was published in Land

The use of agent-based models (ABMs) and modelling for understanding landscape change and dynamics continues to grow. One reason for the popularity of ABMs is that they provide a framework to represent multiple, discrete, multi-faceted, heterogeneous actors (human or otherwise) and their relationships and interactions between one another and their environment, through time and across space. This collection showcases innovative uses of ABMs for investigating and explaining landscape change and dynamics and to explore and identify how researchers in different disciplines can learn from one another to further innovate. The diverse range of processes and landscapes that ABMs are currently used to examine is clearly demonstrated, including: land-use decision making in agricultural landscapes; soil erosion in semi-arid environments; forest change in mountainous landscapes; trade in 1st Century BC southern France; social adaptations of herders in northern Mongolia; and malaria epidemiology in Kenya. A range of agent-based representation is used from the implied presence of agents, through comparing heterogeneous vs. aggregated representation of human activity, to alternative means of parameterizing individual agent behaviour. The collection will be of interest to all interested in innovative agent-based modelling for understanding landscape change, its causes and consequences for sustainability in the Anthropocene

People are constantly changing the land surface through construction, agriculture, energy production, and other activities. Changes both in how land is used by people (land use) and in the vegetation, rock, buildings, and other physical material that cover the Earth's surface (land cover) can be described and future land change can be projected using land-change models (LCMs). LCMs are a key means for understanding how humans are reshaping the Earth's surface in the past and present, for forecasting future landscape conditions, and for developing policies to manage our use of resources and the environment at scales ranging from an individual parcel of land in a city to vast expanses of forests around the world. Advancing Land Change Modeling: Opportunities and Research Requirements describes various LCM approaches, suggests guidance for their appropriate application, and makes recommendations to improve the integration of observation strategies into the models. This report provides a summary and evaluation of several modeling approaches, and their theoretical and empirical underpinnings, relative to complex land-change dynamics and processes, and identifies several opportunities for further advancing the science, data, and cyberinfrastructure involved in the LCM enterprise. Because of the numerous models available, the report focuses on describing the categories of approaches used along with selected examples, rather than providing a review of specific models. Additionally, because all modeling approaches have relative strengths and weaknesses, the report compares these relative to different purposes. Advancing Land Change Modeling's recommendations for assessment of future data and research needs will enable model outputs to better assist the science, policy, and decisionsupport communities.

This unique book brings together a comprehensive set of papers on the background, theory, technical issues and applications of agent-based modelling (ABM) within geographical systems. This collection of papers is an invaluable reference point for the experienced agent-based modeller as well those new to the area. Specific geographical issues such as handling scale and space are dealt with as well as practical advice from leading experts about designing and creating ABMs, handling complexity, visualising and validating model outputs. With contributions from many of the world’s leading research institutions, the latest applied research (micro and macro applications) from around the globe exemplify what can be achieved in geographical context. This book is relevant to researchers, postgraduate and advanced undergraduate students, and professionals in the areas of quantitative geography, spatial analysis, spatial modelling, social simulation modelling and geographical information sciences.

Tobacco consumption continues to be the leading cause of preventable disease and death in the United States. The Food and Drug Administration (FDA) regulates the manufacture, distribution, and marketing of tobacco products - specifically cigarettes, cigarette tobacco, roll-your-own tobacco, and smokeless tobacco - to protect public health and reduce tobacco use in the United States. Given the strong social component inherent to tobacco use onset, cessation, and relapse, and given the heterogeneity of those social interactions, agent-based models have the potential to be an essential tool in assessing the effects of policies to control tobacco. Assessing the Use of Agent-Based Models for Tobacco Regulation describes the complex tobacco environment; discusses the usefulness of agent-based models to inform tobacco policy and regulation; presents an evaluation framework for policy-relevant agent-based models; examines the role and type of data needed to develop agent-based models for tobacco regulation; provides an assessment of the agent-based model developed for FDA; and offers strategies for using agent-based models to inform decision making in the future.

Geosimulation is hailed as ‘the next big thing’ in geographic modelling for urban studies. This book presents readers with an overview of this new and innovative field by introducing the spatial modelling environment and describing the latest research and development using cellular automata and multi-agent systems. Extensive case studies and working code is available from an associated website which demonstrate the technicalities of geosimulation, and provide readers with the tools to carry out their own modelling and testing. The first book to treat urban geosimulation explicitly, integrating socio-economic and environmental modelling approaches Provides the reader with a sound theoretical base in the science of geosimulation as well as applied material on the construction of geosimulation models Cross-references to an author-maintained associated website with downloadable working code for readers to apply the models presented in the book Visit the Author's Website for further information on Geosimulation, Geographic Automata Systems and Geographic Automata Software http://www.geosimulationbook.com

This is the era of Big Data and computational social science. It is an era that requires tools which can do more than visualise data but also model the complex relation between data and human action, and interaction. Agent-Based Models (ABM) - computational models which simulate human action and interaction – do just that. This textbook explains how to design and build ABM and how to link the models to Geographical Information Systems. It guides you from the basics through to constructing more complex models which work with data and human behaviour in a spatial context. All of the fundamental concepts are explained and related to practical examples to facilitate learning (with models developed in NetLogo with all code examples available on the accompanying website). You will be able to use these models to develop your own applications and link, where appropriate, to Geographical Information Systems. All of the key ideas and methods are explained in detail: geographical modelling; an introduction to ABM; the fundamentals of Geographical Information Science; why ABM and GIS; using QGIS; designing and building an ABM; calibration and validation; modelling human behavior. An applied primer, that provides fundamental knowledge and practical skills, it will provide you with the skills to build and run your own models, and to begin your own research projects.

The thesis is an original and novel contribution to land use/land cover change analysis using methods of geosimulation and agent-based modeling. The author implements several traditional methodologies of land use change by means of remote sensing and GIS techniques. An Agent-Based Model was developed in order to simulate land use change in the Tehran metropolitan area, comparing the outcomes of each particular methodology. All methods are compared, and advantages and disadvantages discussed.

The 21st century has seen the beginnings of a great restoration effort towards the world’s forests, accompanied by the emergence of an increasing literature on reforestation, regeneration and regrowth of forest cover. Yet to date, there is no volume which synthesises current knowledge on the extent, trends, patterns and drivers of reforestation. This edited volume draws together research from leading researchers to explore reforestation and forest regrowth across the world, from multiple dimensions – including ecosystem services, protected areas, social institutions, economic transitions, remediation of environmental problems, conservation and land abandonment – and at different scales. Detailing the methods and analyses used from across a wide range of disciplines, and incorporating research from North, South and Central America, Africa, Asia and Europe, this groundbreaking book provides a global overview of current trends, explores their underlying causes and proposes future forest trajectories. The first of its kind, the book will provide an invaluable reference for researchers and students involved in interdisciplinary research and working on issues relevant to the biophysical, geographic, socioeconomic and institutional processes associated with reforestation.