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The aim of the conference is to present and discuss new methods, issues and challenges encountered in all parts of the complex process of gradual development and application of digital surface models. This process covers data capture, data generation, storage, model creation, validation, manipulation, utilization and visualization. Each stage requires suitable methods and involves issues that may substantially decrease the value of the model. Furthermore, the conference provides a platform to discuss the requirements, features and research approaches for 3D modeling, continuous field modeling and other geoscience applications. The conference covers the following topics: - LIDAR for elevation data - Radar interferometry for elevation data - Surface model creation - Surface model statistics - Surface model storage (including data formats, standardization, database) - Feature extraction - Analysis of surface models - Surface models for hydrology, meteorology, climatology - Surface models for signal spreading - Surface models for geology (structural, mining) - Surface models for environmental science - Surface models for visibility studies - Surface models for urban geography - Surface models for human geography - Uncertainty of surface models and digital terrain analysis - Surface model visual enhancement and rendering .

The aim of the book is to present and discuss new methods, issues and challenges involved in geoinformatics’ contribution to making transportation more intelligent, efficient and human-friendly. It covers a wide range of topics related to transportation and geoinformatics. The themes are divided into four main sections: Transport modeling, Sensor data and services, Intelligent transport systems, and Transport planning and accessibility.

This paper treats development issues of the suburban areas of Belgrade city. A considerable growth that the city had experienced has led to excessive consumption of land and also to degradation of the landscape and loss of the natural biodiversity. This is why an augmentation of the current Master Plan within the administrative extents of the city is considered to be vital for consistent planning of suburban areas development. Model used in this paper considered defining land-use suitability, relying on available thematic data, including the following sources: topography, land-cover, geology, protected areas and some synthetic maps derived from these sources in a GIS environment. For this purpose Support Vector Machines (SVM) algorithm has been implemented in a typical supervised classification learning task. Two modelling schemes have been involved (since the main problem of the study was the unavailability of the land-use suitability in the testing area): MODEL1 has been built in the extents of the training area having only two land-use suitability classes at disposal (Unsuitable and Very Unsuitable) and extrapolated to the testing area within which the same two classes were known (thus available for model performance evaluation), while MODEL2 has been trained on all four land-use suitability classes, and extrapolated to the testing area, with unknown land-use classes. The second model was then correlated with the first one in order to estimate its otherwise disputable performance. Results of MODEL1 were satisfactory, with high overall accuracy (85%). MODEL2 visually shows a good tendency, and since it has at least 85% accuracy for those coincident two classes (Unsuitable and Very Unsuitable) with MODEL1, it is justified to assume that remaining two classes match similar accuracy rates. The model could be improved by more thorough optimization of the classifier parameters, which will require much longer experimenting costs.