Simulation of urban system evolution in a synergetic modelling framework. The case of Attica, Greece

Spatial analysis and evolution simulation of such complex and dynamic systems as modern urban areas could greatly benefit from the synergy of methods and techniques that constitute the core of the fields of Information Technology and Artificial Intelligence. Additionally, if during the decision making process, a consistent methodology is applied and assisted by a user-friendly interface, premium and pragmatic solution strategies can be tested and evaluated. In such a framework, this paper presents both a prototype Decision Support System and a consorting spatio-temporal methodology, for modelling urban growth. Its main focus is on the analysis of current trends, the detection of the factors that mostly affect the evolution process and the examination of user-defined hypotheses regarding future states of the problem environment. According to the approach, a neural network model is formulated for a specific time intervals and each different group of spatial units, mainly based to the degree of their contiguity and spatial interaction. At this stage, fuzzy logic provides a precise image of spatial entities, further exploited in a twofold way. First, for the analysis and interpretation of up-to-date urban evolution and second, for the formulation of a robust spatial simulation model. It should be stressed, however, that the neural network model is not solely used to define future urban images, but also to evaluate the degree of influence that each variable as a significant of problem parameter, contributes to the final result. Thus, the formulation and the analysis of alternative planning scenarios are assisted. Both the proposed methodological framework and the prototype Decision Support System are utilized during the study of Attica, Greece?s principal prefecture and the definition of a twenty-year forecast. The variables considered and projected refer to population data derived from the 1961-1991 censuses and building uses aggregated in ten different categories. The final results are visualised through thematic maps in a GIS environment. Finally, the performance of the methodology is evaluated as well as directions for further improvements and enhancements are outlined. Keywords: Computational geography, Spatial modelling, Neural network models, Fuzzy logic.

Modeling urban evolution by identifying spatiotemporal patterns and applying methods of artificial intelligence.Case study: Athens, Greece.

While during the past decades, urban areas experience constant slow population growth, the spatial patterns they form, by means of their limits and borders, are rapidly changing in a complex way. Furthermore, urban areas continue to expand to the expense of "rural” intensifying urban sprawl. The main aim of this paper is the definition of the evolution of urban areas and more specifically, the specification of an urban model, which deals simultaneously with the modification of population and building use patterns. Classical theories define city geographic border, with the Aristotelian division of 0 or 1 and are called fiat geographic boundaries. But the edge of a city and the urbanization "degree" is something not easily distinguishable. Actually, the line that city ends and rural starts is vague. In this respect a synthetic spatio - temporal methodology is described which, through the adaptation of different computational methods aims to assist planners and decision makers to gain an insight in urban - rural transition. Fuzzy Logic and Neural Networks are recruited to provide a precise image of spatial entities, further exploited in a twofold way. First for analysis and interpretation of up - to - date urban evolution and second, for the formulation of a robust spatial simulation model, the theoretical background of which is that the spatial contiguity between members of the same or different groups is one of the key factors in their evolution. The paper finally presents the results of the model application in the prefecture of Attica in Greece, unveiling the role of the Athens Metropolitan Area to its current and future evolution, by illustrating maps of urban growth dynamics.urban growth; urban dynamics; neural networks; fuzzy logic; Greece; Athens

Refugee Mobilities and Institutional Changes: Local Housing Policies and Segregation Processes in Greek Cities

Many studies have explored the dynamics of immigrant and refugee settlement at the local level, highlighting that it is actually a two-way process: On the one hand, the local socio-political context specifies the conditions for refugee inclusion, and on the other, migrant mobility leads to the transformation of localities in various ways. In Greek cities, the social practices of local actors have played an important role in the implementation of the immigration policy, where refugees were perceived as a threat to personal and community security. Yet, new forms of social mobilisation and solidarity by individual citizens and community initiatives have worked to alter these attitudes, mitigating tensions and obstacles in refugee acceptance. The article draws on the Greek experience to explore the role and importance of the local socio-political texture in refugee inclusion, shedding light on how it gave rise to various local initiatives that inform refugee allocation as well as urban transformation and institutional change. In methodological terms, the article considers three neighbouring Greek cities as case studies to identify the different institutional and policy responses to refugee accommodation, giving rise to different paths and forms of social inclusion. The study reveals the complexity and context of the social-spatial diversity that refugees face but also the transformation dynamics of local states and civil society.The paper draws on the Greek experience to explore the role and importance of social infrastructure in refugee integration, shedding light on how these qualities, materialized in local initiatives for refugee integration to influence urban transformation and institutional change. In methodological terms, the paper employs three small and medium-size Greek cities as case studies to identify the different institutional and policy responses to refugee accommodation followed, giving rise to different paths and forms of social inclusion and urban transformation. The study reveals the complexity and the contextuality of the social spatial diversity that refugees face but also the transformation of local states and civil society

Primary care clinic location decision-making and spatial accessibility for the region of Thessaly

The prospect for establishing a General Clinic at the Thessaly Region was examined. The new facility aimes to provide full medical care by qualified scientists (permanent personnel, shareholders or associates), by experienced, trained and skilled nursing personnel, fully organised with sophisticated technological equipment, in a hospitable and pleasant environment, with easy and fast access. The main aim of this study is the determination of the optimum location for the construction of the proposed medical centre for providing high level services in the Thessaly region, by implementing quantitative methods of Spatial Analysis of GIS technology. Spatial Analysis focuses on evaluating existing and proposed models of spatial organization, while GIS, provide the necessary informational tools for the elaboration and management of the relevant information and all in all in the support of the relevant decision making process

Geographic information analysis and health infrastructure

Enterprises seek for development and growth  so  as  to increase  their  sales  and  profits. In  order  to  come  to  a  decision  on  how  this development  is  going  to  be  achieved  they  face an  endless  line  of  possible  strategies,  one  of which is location. Location of the business affects its development and viability, concerning the cost, its efficiency and its use.  Regarding the location  of  the  centers  of  providing  medical services  despite  the  new  technologies  (like telemedicine  ‐ which  facilitates  the reaction  to a distant  event),  their  location  continue  to  be  a distinctive  advantage  since  immediate  access and  service  is  the  objective  target.  Significant factors are  the  nature  of  the  situations a  facility has to face as well as the displacement time both in  cases  of diagnosis and in cases of remedies, which is important and in various cases decisive.  Additionally to the best location, the best possible cooperation with specialized doctors and nursery personnel from the wider region is required. In this framework, Spatial Analysis and Geographical Information Systems are recruited to demonstrate how all the above issues can be answered under the complex environment  a location‐allocation  decision  must  be  taken,  by the  authorities  for  the  location‐allocation  of health infrastructure

Primary care clinic location decision-making and spatial accessibility for the region of Thessaly

The prospect for establishing a General Clinic at the Thessaly Region was examined. The new facility aimes to provide full medical care by qualified scientists (permanent personnel, shareholders or associates), by experienced, trained and skilled nursing personnel, fully organised with sophisticated technological equipment, in a hospitable and pleasant environment, with easy and fast access. The main aim of this study is the determination of the optimum location for the construction of the proposed medical centre for providing high level services in the Thessaly region, by implementing quantitative methods of Spatial Analysis of GIS technology. Spatial Analysis focuses on evaluating existing and proposed models of spatial organization, while GIS, provide the necessary informational tools for the elaboration and management of the relevant information and all in all in the support of the relevant decision making process

Modeling urban evolution by identifying spatiotemporal patterns and applying methods of artificial intelligence.Case study: Athens, Greece.

While during the past decades, urban areas experience constant slow population growth, the spatial patterns they form, by means of their limits and borders, are rapidly changing in a complex way. Furthermore, urban areas continue to expand to the expense of "rural” intensifying urban sprawl. The main aim of this paper is the definition of the evolution of urban areas and more specifically, the specification of an urban model, which deals simultaneously with the modification of population and building use patterns. Classical theories define city geographic border, with the Aristotelian division of 0 or 1 and are called fiat geographic boundaries. But the edge of a city and the urbanization "degree" is something not easily distinguishable. Actually, the line that city ends and rural starts is vague. In this respect a synthetic spatio - temporal methodology is described which, through the adaptation of different computational methods aims to assist planners and decision makers to gain an insight in urban - rural transition. Fuzzy Logic and Neural Networks are recruited to provide a precise image of spatial entities, further exploited in a twofold way. First for analysis and interpretation of up - to - date urban evolution and second, for the formulation of a robust spatial simulation model, the theoretical background of which is that the spatial contiguity between members of the same or different groups is one of the key factors in their evolution. The paper finally presents the results of the model application in the prefecture of Attica in Greece, unveiling the role of the Athens Metropolitan Area to its current and future evolution, by illustrating maps of urban growth dynamics

Simulation of urban system evolution in a synergetic modelling framework. The case of Attica, Greece

Spatial analysis and evolution simulation of such complex and dynamic systems as modern urban areas could greatly benefit from the synergy of methods and techniques that constitute the core of the fields of Information Technology and Artificial Intelligence. Additionally, if during the decision making process, a consistent methodology is applied and assisted by a user-friendly interface, premium and pragmatic solution strategies can be tested and evaluated. In such a framework, this paper presents both a prototype Decision Support System and a consorting spatio-temporal methodology, for modelling urban growth. Its main focus is on the analysis of current trends, the detection of the factors that mostly affect the evolution process and the examination of user-defined hypotheses regarding future states of the problem environment. According to the approach, a neural network model is formulated for a specific time intervals and each different group of spatial units, mainly based to the degree of their contiguity and spatial interaction. At this stage, fuzzy logic provides a precise image of spatial entities, further exploited in a twofold way. First, for the analysis and interpretation of up-to-date urban evolution and second, for the formulation of a robust spatial simulation model. It should be stressed, however, that the neural network model is not solely used to define future urban images, but also to evaluate the degree of influence that each variable as a significant of problem parameter, contributes to the final result. Thus, the formulation and the analysis of alternative planning scenarios are assisted. Both the proposed methodological framework and the prototype Decision Support System are utilized during the study of Attica, Greece's principal prefecture and the definition of a twenty-year forecast. The variables considered and projected refer to population data derived from the 1961-1991 censuses and building uses aggregated in ten different categories. The final results are visualised through thematic maps in a GIS environment. Finally, the performance of the methodology is evaluated as well as directions for further improvements and enhancements are outlined. Keywords: Computational geography, Spatial modelling, Neural network models, Fuzzy logic