The Smart Cities data and applications need to replicate, as faithfully as possible, the state of the city and to simulate possible alternative futures. In order to do this, the modelling of the city should cover all aspects of the city that are relevant to the problems that require smart solutions. In this context, 2D and 3D spatial data play a key role, in particular 3D city models. One of the methods for collecting data that can be used for developing such 3D city models is Light Detection and Ranging (LiDAR), a technology that has provided opportunities to generate large-scale 3D city models at relatively low cost. The collected data is further processed to obtain fully developed photorealistic virtual 3D city models. The goal of this research is to develop virtual 3D city model based on airborne LiDAR surveying and to analyze its applicability toward Smart Cities applications. It this paper, we present workflow that goes from data collection by LiDAR, through extract, transform, load (ETL) transformations and data processing to developing 3D virtual city model and finally discuss its future potential usage scenarios in various fields of application such as modern ICT-based urban planning and 3D cadaster. The results are presented on the case study of campus area of the University of Novi Sad.

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Rosemary (Rosmarinus officinalis L.) is a plant worldwide cultivated mainly for essential oils, extracts, and as a spice. Up-to-date results showed diversity in composition of the essential oils, which may influence their quality, biological activity, and thermal properties. Therefore, the aim of this study was to investigate the chemical composition, antimicrobial activity, and thermal properties of the rosemary essential oils originating from Serbia and Russia. Additionally, oils were added to the sunflower oils in order to investigate possible antioxidant activity during the frying. Investigation of the chemical profile marked α-pinene, eucalyptol, and camphor as the most abundant compounds in both oils. However, overall composition influenced in such manner that Russian oil showed significantly higher antimicrobial activity, while Serbian oil proved to be better antioxidant agent in case of frying of sunflower oil. This would significantly influence possible application of the oils, which could be used as an antioxidant agent for extension of the food shelf life, or antimicrobial agent for protection against different microbial strains.

Change detection is a process of detecting differences with the objects or phenomena which are observed in the different time intervals. In this study different methods of analyzing satellite images are presented, with the aim to identify changes in land cover in a certain period of time (1985 -2013). The area observed in this study is the region of mountain Zlatibor (Serbia) with its surroundings. The methods represented in this study are vegetation indices differencing, Supervised classification and Object based classification. These methods gave different results in term of land cover area, and it is generally concluded that supervised classification gave the most accurate results with the images of medium spatial resolution. The results of this study can be used for urban and environmental planning. All information lead to conclusion that the surface under the forests is reduced for about 4% (or about 1000 ha) while the built up area has doubled (grown about 600 ha) during the examined period. The results also highlights the importance of change detection techniques in land cover for the areas that are developing rapidly, such as Zlatibor study area.

Abstract.3D models of urban areas have found use in modern world such as navigation, cartography, urban planning visualization, construction, tourism and even in new applications of mobile navigations. With the advancement of technology there are much better solutions for mapping earth's surface and spatial objects. 3D city model enables exploration, analysis, management tasks and presentation of a city. Urban areas consist of terrain surfaces, buildings, vegetation and other parts of city infrastructure such as city furniture. Nowadays there are a lot of different methods for collecting, processing and publishing 3D models of area of interest. LIDAR technology is one of the most effective methods for collecting data due the large amount data that can be obtained with high density and geometrical accuracy. CityGML is open standard data model for storing alphanumeric and geometry attributes of city. There are 5 levels of display (LoD0, LoD1, LoD2, LoD3, LoD4). In this study, main aim is to represent part of urban area of Novi Sad using LIDAR technology, for data collecting, and different methods for extraction of information's using CityGML as a standard for 3D representation. By using series of programs, it is possible to process collected data, transform it to CityGML and store it in spatial database. Final product is CityGML 3D model which can display textures and colours in order to give a better insight of the cities. This paper shows results of the first three levels of display. They consist of digital terrain model and buildings with differentiated rooftops and differentiated boundary surfaces. Complete model gives us a realistic view of 3D objects. IntroductionWith the advancement of today's technology there is need to improve current methods in order to enable fast and efficientmanagement and distribution of geospatial information, andgreater availability of spatial data. Currently majority of topics in area of geoinformatics is dealing with 3D cadastre and how to represent 3D objects. 2D maps are outdated and do not provide sufficient information that is now more than necessary. 3D cities are becoming more and more important in different areas of the modern world.There are several data models for the creation of 3D city models including GML, KML, X3D, CityGML, VRML, STL etc. The CityGML defines five levels of details for multi-scale modelling: LOD0 -Regional model contains 2.5D Digital Terrain Model, LOD1 -Building block model without roof structures, LOD2 -Building model including roof structures, LOD3 -Building model including detailed architecture, LOD4 -Building model including interior model. Figure 1 contains LOD representations.