The objectives and methodology of the MAMUD research project are presented in this paper. MAMUD is an acronym for Measuring and Modeling Urban Dynamics: Impact on Quality of Live and Hydrology. The research will be conducted over a four year period (2007-2011). The major goal is to investigate how earth observation can contribute to a better monitoring, modeling and understanding of urban dynam...

This work focuses on adapting artificial intelligence techniques for urban growth modeling using multitemporal imagery. Fuzzy set theory and cellular automata are used for this purpose. Fuzzy set theory preserves the spatial continuity of the growth process through allowing a test pixel to be partially developed unlike the binary crisp system (developed/undeveloped). The development level ident...

Hernán A. Makse, José S. Andrade, Jr., Michael Batty, Shlomo Havlin, and H. Eugene Stanley Center for Polymer Studies and Department of Physics, Boston University, Boston, Massachusetts 02215 Departamento de Fı́sica, Universidade Federal do Ceará, 60451-970 Fortaleza, Ceará, Brazil Centre for Advanced Spatial Analysis, University College London, 1-19 Torrington Place, London WC1E 6BT, United Kin...

Urban growth models have been used for decades to forecast urban development in metropolitan areas. Since the 1990s cellular automata, with simple computational rules and an explicitly spatial architecture, have been heavily utilized in this endeavor. One such cellularautomata-based model, SLEUTH, has been successfully applied around the world to better understand and forecast not only urban gr...

The modeling of a city’s evolution is one of the most exciting fields in urban studies research. The interest of such a model lies more in the past than the future: understanding how a city was made rather as opposed to how it might evolve. Such a model can necessitate expertise from numerous fields. From urban network analysis to spatial organisation and social patterning, modeling is a matter...

Urban growth modelling cellular automata has blossomed due to the advancement in geographic information systems (GIS), remote sensing and computer technology. Among such urban growth models, our urban growth model (UGM), was modified from SLEUTH (Slope Land-use Transport Hill-shade) model. UGM has been integrated in the XULU modeling frame-work (eXtendable Unified Land Use Modelling Platform). ...

The interactions between urban development and ecological processes are extraordinarily complex. Urban development evolves over time and space as the outcome of microscopic interactions of individual choices and actions taken by multiple agents. These decisions affect ecosystem structures and functions through the conversion of land, fragmentation of natural habitat use, disruption of hydrologi...

This paper describes an on-going work on the development and implementation of cellular automata based urban growth modeling using multitemporal satellite imagery. The algorithm is designed to simulate the historical growth as a function of local neighbourhood structure of the input data. Transition rules in the algorithm drive the urban growth over time. Calibration is introduced in the cellul...

Modern urban regions are highly complex entities. Despite the difficulty of modeling every relevant aspect of an urban region, researchers have produced a rich variety of models dealing with interrelated processes of urban change. The most popular types of models have been those dealing with the relationship between transportation network growth and changes in land use and the location of econo...