The aim of this work is to explore the method of fuzzy clustering applied for classification of spatial objects or generic geospatial analysis and cluster analysis as a classification of objects by mutual similarities and organize data into groups. Clustering techniques fall into unsupervised methods, meaning that they do not use predefined class identifiers. The biggest potential of clustering is in recognizing the basic data structures, not only for classification and identification of samples, but also the reduction of models and optimization.

Nowadays, often picture of sharing data is: different organizations on different levels host its own GIS. Each of them uses software and a data model which best meet their needs with centralized storage and metadata interoperability, using appropriate tool for the job while eliminating complicated data transfers and multiple copies of the same data throughout the enterprise or department. Spatial Object Model enable using any combination of commercial or open-source GIS tools to work together with same database using triggers and storage processes. This paper demonstrates usage of IT infrastructure which is wide recognized by local governments or enterprises as platform for three-tier structure solution: spatial data server, application server and application client. Based on application server it is possible to produce different OGC Web Services for use spatial data in background application or expose via GIS portal. Any client can request the server if it accords with OGC specification. Objective of this paper is studies of very demanding integration and interoperability task from real-world: data server for storing terabytes of data, application server for creating web services which enable distribution this amount of data and simultaneously different GIS clients and WebGIS portal.

This work studies the application of the multi-objective genetic algorithm based on the Pareto approach, as a tool for the decision making support in the geospatial analysis. Pareto-based evolutionary mechanism developed as an approach to multi-objective geospatial optimisation operates with fixed parameters of genetic operators. It can be used as efficient tool for multi-objective planning both for their power and flexibility and the fact that they generate a whole set of good solutions rather than just one “optimal” solution. Within the studies it is tested and suggested an adaptive mechanism for mutation parameter based on the determinstic approach. The application of the suggested multi-objective Pareto based genetic algorithm over selected location problems demonstrates its ability of the discovery of multiple compromise solutions in a real spatial problem domain.

This paper is focused on the development of methodology for multicriterial land valorization in land use planning by application of genetic algorithm. One of the key tools for design of the decision support system based on this methodology is geographic information system which serve to quantify multicriterial data and represent resulting spatial data. The methodology and the algorithm are applied to a specific problem of spatial planning in Tuzla Canton, Bosnia and Herzegovina. The crucial points of the research are the following: possibility of multicriterial valorization of the land from the GA use perspective, how to utilize the capacity of the GA optimization techniques in the frame of decision support system and with usage of the GIS tools and how to apply the GA in the field of genotype presentation in spatial modeling.

(MSc EE Almir Karabegovic, Gauss, Geo Information Systems, Stupine B9/6, Tuzla – Bosnia and Herzegovina, almir@gauss.ba) (PhD Zikrija Avdagic, Faculty of Electrical Engineering, Department for Informatics and Computer Science, Zmaja od Bosne (Kampus), Sarajevo – Bosnia and Herzegovina, zikrija.avdagic@etf.unsa.ba) (MSc EE Mirza Ponjavic, Gauss, Geo Information Systems, Stupine B9/6, Tuzla – Bosnia and Herzegovina, mirza@gauss.ba)