Modeling and Simulation of Urban Growth in the Use of Industry 4.0

Industrial growth is the positive increase of various opportunities and factors in a region within the framework of certain planning over time. Along with the developing technologies, Remote Sensing (RS), Geographic Information Systems (GIS), and simulation models are used to see the results of industrial growth effects and to create predictions. The findings obtained are guiding in terms of planning, investment studies, and management. In this context, the data obtained by using RS and GIS are input data for different simulation models, while simulation models provide predictions for the future with information in the past and present time period. Various hybrid simulation techniques are used in the computer-aided industrial simulation, consisting of Monte-Carlo, Petri-Networks, reality and traffic simulation, and their combination. In this context, the basic components and properties of an industrially strong and healthy simulation will be emphasized. In this study, by considering the integration of RS and GIS with simulation models in modeling industrial systems, the Von Thünen Model, Concentric Zoning Theory, Central Field Theory, Sector Theory, Artificial Neural Networks, Markov Chains, Cellular Automaton, Logistic Regression, and SLEUTH model have been examined.