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.

The utility network cadastre in Serbia is the main register of utility lines and the rights to them. The Law on State Survey and Cadastre states the necessity for implementing a unified information system of both a real estate and utility network cadastre, but this has not been achieved in practice. The reasons for such a unified information system are to ensure easier maintenance of the rights of both the utilities and properties located above or below them, to ensure more efficient procedures for obtaining the consent for placement, repair, or removal of the utility line, to prevent procedures being executed based on outdated data, to build an information system as the law prescribes, and to facilitate the business processes in the Serbian geodetic authority, since it is responsible for both registers. Therefore, an already-developed LADM (Land Administration Domain Model)-based country profile for Serbia should be extended to include information from the utility network cadastre. An analysis of Serbian legislation showed the necessity of extending the class set of the utility network cadastre by further specialization of the LADM LA_LegalSpaceUtilityNetwork class. Furthermore, such a system will support the maintenance of utility network data. In practice, when there is a change made on utility lines by the right holders, it is necessary to implement the change in the register. In many situations, this is not done, and the actual state does not correspond to the one in the register. Usually, modern technologies, such as ground penetrating radar (GPR) and LIDAR, are used for data acquisition in order to provide an update of the utility network data. Since these technologies produce 3D data, we analyzed how to link that data to the traditional 2D spatial paradigm.

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.

Precision viticulture systems are essential for enhancing traditional intensive viticulture, achieving high-quality results, and minimizing costs. This study explores the integration of Unmanned Aerial Vehicles (UAVs) and artificial intelligence in precision viticulture, focusing on vine detection and vineyard zoning. Vine detection employs the YOLO (You Only Look Once) deep learning algorithm, achieving a remarkable 90% accuracy by analysing UAV imagery with various spectral ranges from various phenological stages. Vineyard zoning, achieved through the application of the K-means algorithm, incorporates geospatial data such as the Normalized Difference Vegetation Index (NDVI) and the assessment of nitrogen, phosphorus, and potassium content in leaf blades and petioles. This approach enables efficient resource management tailored to each zone’s specific needs. The research aims to develop a decision-support model for precision viticulture. The proposed model demonstrates a high vine detection accuracy and defines management zones with variable weighting factors assigned to each variable while preserving location information, revealing significant differences in variables. The model’s advantages lie in its rapid results and minimal data requirements, offering profound insights into the benefits of UAV application for precise vineyard management. This approach has the potential to expedite decision making, allowing for adaptive strategies based on the unique conditions of each zone.

Based on a newly adopted “Rulebook on the records of identified changes on buildings in Serbia” (2020) that regulates the content, establishment, maintenance and use of records on identified changes on buildings, it is expected that the geodetic-cadastral information system will be extended with these records. The records contain data on determined changes of buildings in relation to the reference epoch of aerial or satellite imagery, namely data on buildings: (1) that are not registered in the real estate cadastre; (2) which are registered in the real estate cadastre, and have been changed in terms of the dimensions in relation to the data registered in the real estate cadastre; (3) which are registered in the real estate cadastre, but are removed on the ground. For this purpose, the LADM-based cadastral data model for Serbia is extended to include records on identified changes on buildings. In the year 2020, Republic Geodetic Authority commenced a new satellite acquisition for the purpose of restoration of official buildings registry, as part of a World Bank project for improving land administration in Serbia. Using this satellite imagery and existing cadastral data, we propose a method based on comparison of object-based and pixel-based image analysis approaches to automatically detect newly built, changed or demolished buildings and import these data into extended cadastral records. Our results, using only VHR images containing only RGB and NIR bands, showed object identification accuracy ranging from 84% to 88%, with kappa statistic from 89% to 96%. The accuracy of obtained results is satisfactory for the purpose of developing a register of changes on buildings to keep cadastral records up to date and to support activities related to legalization of illegal buildings, etc.

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.