Multi Agent System For Simulation Of Land Use And Land Cover Change

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 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.

This book presents recent estimates on the rate of change of major land classes. Aggregated globally, multiple impacts of local land changes are shown to significantly affect central aspects of Earth System functioning. The book offers innovative developments and applications in the fields of modeling and scenario construction. Conclusions are also drawn about the most pressing implications for the design of appropriate intervention policies.

The quality of ecosystems is affected by the actions of different stakeholders who use them in a variety of ways. In order to understand this complex relationship between humans and nature, it is vital to understand the complexity of the interacting agents. The authors in this book attempt to do this by applying multi-agent systems to the problems of ecosystem management. The multi-agent approach to ecosystem management is a relatively new and rapidly developing field which takes a formal computational approach towards the interaction of humans with their environment. The authors highlight some of the promising new methodologies which are emerging in the field from disciplines such as computer science and computational social science. They move on to address a number of important topics including diffusion processes, common-pool resources, land use change and the participatory use of models, in an attempt to solve contemporary management issues. They clearly demonstrate the potential utility of multi-agent systems in the context of theoretical problems and practical case studies.

This book constitutes the thoroughly refereed and revised selected papers from the 22nd International Workshop on Multi-Agent-Based Simulation, MABS 2022, which took place virtually during May 8–9, 2022. The conference was originally planned to take place in Auckland, New Zealand, but had to change to an online format due to the COVID-19 pandemic. The 11 papers included in these proceedings were carefully reviewed and selected from 17 submissions. They focus on finding efficient solutions to model complex social systems, in areas such as economics, management, organisational and social sciences in general.

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.