TY  - JOUR
AU  - Stančić, Nikola
AU  - Kovačević, Jovan
AU  - Cvijetinović, Željko
AU  - Brodić, Nenad
AU  - Mihajlović, Dragan
PY  - 2023
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/3039
AB  - Transport management is one of the most important logistical tasks, and the designing the optimal transport routes plays a major role in that process. Vehicle routing is primarily of interest to companies that organize the transportation of goods to end users, with the aim of minimizing the total cost of the routes. Being a well-known NP-hard problem, the theoretical background of the vehicle routing problem has been researched for many years and it has been the basis for the development of a large number of commercial software. However, affordable software solutions are lacking. Difficult access to high quality and reliable spatial data related to the road network is also a limitation. This paper discusses the possibilities of applying open-source software for solving the VRP. Open spatial data from a collaborative project of the virtual community was used as the basis for modeling the road network graph. The experiment was carried out on data on vehicles and customers of a certain retail chain and refers to the territory of Serbia.
PB  - IPSI, Dalmatinska 55, 11000 Belgrade, Serbia
T2  - IPSI Transactions on Advanced Research
T1  - Solving the Vehicle Routing Problem In the Open-Source Software ‘ODL Studio’
EP  - 12
IS  - 1
SP  - 5
VL  - 19
UR  - https://hdl.handle.net/21.15107/rcub_grafar_3039
ER  - 

@article{
author = "Stančić, Nikola and Kovačević, Jovan and Cvijetinović, Željko and Brodić, Nenad and Mihajlović, Dragan",
year = "2023",
abstract = "Transport management is one of the most important logistical tasks, and the designing the optimal transport routes plays a major role in that process. Vehicle routing is primarily of interest to companies that organize the transportation of goods to end users, with the aim of minimizing the total cost of the routes. Being a well-known NP-hard problem, the theoretical background of the vehicle routing problem has been researched for many years and it has been the basis for the development of a large number of commercial software. However, affordable software solutions are lacking. Difficult access to high quality and reliable spatial data related to the road network is also a limitation. This paper discusses the possibilities of applying open-source software for solving the VRP. Open spatial data from a collaborative project of the virtual community was used as the basis for modeling the road network graph. The experiment was carried out on data on vehicles and customers of a certain retail chain and refers to the territory of Serbia.",
publisher = "IPSI, Dalmatinska 55, 11000 Belgrade, Serbia",
journal = "IPSI Transactions on Advanced Research",
title = "Solving the Vehicle Routing Problem In the Open-Source Software ‘ODL Studio’",
pages = "12-5",
number = "1",
volume = "19",
url = "https://hdl.handle.net/21.15107/rcub_grafar_3039"
}

Stančić, N., Kovačević, J., Cvijetinović, Ž., Brodić, N.,& Mihajlović, D.. (2023). Solving the Vehicle Routing Problem In the Open-Source Software ‘ODL Studio’. in IPSI Transactions on Advanced Research
IPSI, Dalmatinska 55, 11000 Belgrade, Serbia., 19(1), 5-12.
https://hdl.handle.net/21.15107/rcub_grafar_3039

Stančić N, Kovačević J, Cvijetinović Ž, Brodić N, Mihajlović D. Solving the Vehicle Routing Problem In the Open-Source Software ‘ODL Studio’. in IPSI Transactions on Advanced Research. 2023;19(1):5-12.
https://hdl.handle.net/21.15107/rcub_grafar_3039 .

Stančić, Nikola, Kovačević, Jovan, Cvijetinović, Željko, Brodić, Nenad, Mihajlović, Dragan, "Solving the Vehicle Routing Problem In the Open-Source Software ‘ODL Studio’" in IPSI Transactions on Advanced Research, 19, no. 1 (2023):5-12,
https://hdl.handle.net/21.15107/rcub_grafar_3039 .

TY  - JOUR
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
AU  - Cvijetinović, Željko
AU  - Brodić, Nenad
AU  - Mihajlović, Dragan
PY  - 2023
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2987
AB  - Airborne Laser Scanning (ALS) is one of the most popular and cost-effective approaches for collecting Digital Elevation Model (DEM) data. This especially applies to large areas, forested areas, areas with dense vegetation and urban environments. The ALS results in a vast amount of data in the form of point clouds. Successful use of such data requires applying semi-automatic and automatic approaches to classify points according to which objects or phenomena it represents. LAStools software package represents a set of highly efficient tools for processing ALS data. Through this study, the functionality of the LAStools software package for DEM generation has
been analyzed. The proposed procedure for generating DEM products from ALS point cloud with LAStools has been determined and presented. The study also focuses on the important parameters of each tool in the proposed DEM procedure, with a special focus on advantages and disadvantages, possibilities and limitations.
PB  - IPSI, Dalmatinska 55, 11000 Belgrade, Serbia
T2  - IPSI Transactions on Advanced Research
T1  - Airborne Laser Scanning to Digital Elevation Model – LAStools approach
EP  - 17
IS  - 1
SP  - 13
VL  - 19
UR  - https://hdl.handle.net/21.15107/rcub_grafar_2987
ER  - 

@article{
author = "Kovačević, Jovan and Stančić, Nikola and Cvijetinović, Željko and Brodić, Nenad and Mihajlović, Dragan",
year = "2023",
abstract = "Airborne Laser Scanning (ALS) is one of the most popular and cost-effective approaches for collecting Digital Elevation Model (DEM) data. This especially applies to large areas, forested areas, areas with dense vegetation and urban environments. The ALS results in a vast amount of data in the form of point clouds. Successful use of such data requires applying semi-automatic and automatic approaches to classify points according to which objects or phenomena it represents. LAStools software package represents a set of highly efficient tools for processing ALS data. Through this study, the functionality of the LAStools software package for DEM generation has
been analyzed. The proposed procedure for generating DEM products from ALS point cloud with LAStools has been determined and presented. The study also focuses on the important parameters of each tool in the proposed DEM procedure, with a special focus on advantages and disadvantages, possibilities and limitations.",
publisher = "IPSI, Dalmatinska 55, 11000 Belgrade, Serbia",
journal = "IPSI Transactions on Advanced Research",
title = "Airborne Laser Scanning to Digital Elevation Model – LAStools approach",
pages = "17-13",
number = "1",
volume = "19",
url = "https://hdl.handle.net/21.15107/rcub_grafar_2987"
}

Kovačević, J., Stančić, N., Cvijetinović, Ž., Brodić, N.,& Mihajlović, D.. (2023). Airborne Laser Scanning to Digital Elevation Model – LAStools approach. in IPSI Transactions on Advanced Research
IPSI, Dalmatinska 55, 11000 Belgrade, Serbia., 19(1), 13-17.
https://hdl.handle.net/21.15107/rcub_grafar_2987

Kovačević J, Stančić N, Cvijetinović Ž, Brodić N, Mihajlović D. Airborne Laser Scanning to Digital Elevation Model – LAStools approach. in IPSI Transactions on Advanced Research. 2023;19(1):13-17.
https://hdl.handle.net/21.15107/rcub_grafar_2987 .

Kovačević, Jovan, Stančić, Nikola, Cvijetinović, Željko, Brodić, Nenad, Mihajlović, Dragan, "Airborne Laser Scanning to Digital Elevation Model – LAStools approach" in IPSI Transactions on Advanced Research, 19, no. 1 (2023):13-17,
https://hdl.handle.net/21.15107/rcub_grafar_2987 .

TY  - CONF
AU  - Lakušić, Dmitar
AU  - Kuzmanović, Nevena
AU  - Kovačević, Jovan
PY  - 2022
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2690
AB  - The generalized habitat map of Serbia is one of the products of the project carried out for the needs of the Institute for Nature Protection of Serbia by the Faculty of Biology University of Belgrade in cooperation with the geomatics company MapSoft d.o.o. The map was created using an adapted methodology for extracting different habitat types from remote sensing data. To interpret the basic habitat types, the following input datasets were used: Sentinel-2 satellite data, EU-DEM terrain elevation data, Basic land cover map, Copernicus pan-European high resolution layers, Open Street Map data, pedological and geological map of Serbia, and numerous training data. The map was created by integrating the rasters of each habitat type into a single raster, separating additional habitat subtypes by crossing them with additional sources (geologic and pedological map, basic land cover map, etc.). The final results are presented in the form of a spatial raster, with 32 cartographic classes defined based on the typology of habitats according to the Rulebook on Habitats of Serbia. In addition, manual vectorization of several other habitat types (springs - 37,284 objects, caves - 499 objects, waterfalls - 109 objects) was performed, and these results are provided in the form of vector point entities.
C3  - 14th Symposium on the Flora of Southeastern Serbia and Neighboring Regions
T1  - Generalized habitat map of Serbia
UR  - https://hdl.handle.net/21.15107/rcub_grafar_2690
ER  - 

@conference{
author = "Lakušić, Dmitar and Kuzmanović, Nevena and Kovačević, Jovan",
year = "2022",
abstract = "The generalized habitat map of Serbia is one of the products of the project carried out for the needs of the Institute for Nature Protection of Serbia by the Faculty of Biology University of Belgrade in cooperation with the geomatics company MapSoft d.o.o. The map was created using an adapted methodology for extracting different habitat types from remote sensing data. To interpret the basic habitat types, the following input datasets were used: Sentinel-2 satellite data, EU-DEM terrain elevation data, Basic land cover map, Copernicus pan-European high resolution layers, Open Street Map data, pedological and geological map of Serbia, and numerous training data. The map was created by integrating the rasters of each habitat type into a single raster, separating additional habitat subtypes by crossing them with additional sources (geologic and pedological map, basic land cover map, etc.). The final results are presented in the form of a spatial raster, with 32 cartographic classes defined based on the typology of habitats according to the Rulebook on Habitats of Serbia. In addition, manual vectorization of several other habitat types (springs - 37,284 objects, caves - 499 objects, waterfalls - 109 objects) was performed, and these results are provided in the form of vector point entities.",
journal = "14th Symposium on the Flora of Southeastern Serbia and Neighboring Regions",
title = "Generalized habitat map of Serbia",
url = "https://hdl.handle.net/21.15107/rcub_grafar_2690"
}

Lakušić, D., Kuzmanović, N.,& Kovačević, J.. (2022). Generalized habitat map of Serbia. in 14th Symposium on the Flora of Southeastern Serbia and Neighboring Regions.
https://hdl.handle.net/21.15107/rcub_grafar_2690

Lakušić D, Kuzmanović N, Kovačević J. Generalized habitat map of Serbia. in 14th Symposium on the Flora of Southeastern Serbia and Neighboring Regions. 2022;.
https://hdl.handle.net/21.15107/rcub_grafar_2690 .

Lakušić, Dmitar, Kuzmanović, Nevena, Kovačević, Jovan, "Generalized habitat map of Serbia" in 14th Symposium on the Flora of Southeastern Serbia and Neighboring Regions (2022),
https://hdl.handle.net/21.15107/rcub_grafar_2690 .

TY  - JOUR
AU  - Brodić, Nenad
AU  - Cvijetinović, Željko
AU  - Milenković, Milutin
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
AU  - Mitrović, Momir
AU  - Mihajlović, Dragan
PY  - 2022
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2775
AB  - Numerous semi- and fully-automatic algorithms have been developed for individual tree detection from airborne laser-scanning data, but different rates of falsely detected treetops also accompany their results. In this paper, we proposed an approach that includes a machine learning based refinement step to reduce the number of falsely detected treetops. The approach involves the local maxima filtering and segmentation of the canopy height model to extract different segment level features used for the classification of treetop candidates. The study was conducted in a mixed temperate forest, predominantly deciduous, with a complex topography and an area size of 0.6 km × 4 km. The classification model’s training was performed by five machine learning approaches: Random Forest (RF), Extreme Gradient Boosting, Artificial Neural Network, the Support Vector
Machine, and Logistic Regression. The final classification model with optimal hyperparameters was adopted based on the best-performing classifier (RF). The overall accuracy (OA) and kappa coefficient (κ) obtained from the ten-fold cross validation for the training data were 90.4% and 0.808, respectively. The prediction of the test data resulted in an OA = 89.0% and a κ = 0.757. This indicates that the proposed method could be an adequate solution for the reduction of falsely detected treetops before tree crown segmentation, especially in deciduous forests.
PB  - MDPI
T2  - Remote Sensing, 2022, 14(21), 5345
T1  - Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest
VL  - 14
DO  - 10.3390/rs14215345
ER  - 

@article{
author = "Brodić, Nenad and Cvijetinović, Željko and Milenković, Milutin and Kovačević, Jovan and Stančić, Nikola and Mitrović, Momir and Mihajlović, Dragan",
year = "2022",
abstract = "Numerous semi- and fully-automatic algorithms have been developed for individual tree detection from airborne laser-scanning data, but different rates of falsely detected treetops also accompany their results. In this paper, we proposed an approach that includes a machine learning based refinement step to reduce the number of falsely detected treetops. The approach involves the local maxima filtering and segmentation of the canopy height model to extract different segment level features used for the classification of treetop candidates. The study was conducted in a mixed temperate forest, predominantly deciduous, with a complex topography and an area size of 0.6 km × 4 km. The classification model’s training was performed by five machine learning approaches: Random Forest (RF), Extreme Gradient Boosting, Artificial Neural Network, the Support Vector
Machine, and Logistic Regression. The final classification model with optimal hyperparameters was adopted based on the best-performing classifier (RF). The overall accuracy (OA) and kappa coefficient (κ) obtained from the ten-fold cross validation for the training data were 90.4% and 0.808, respectively. The prediction of the test data resulted in an OA = 89.0% and a κ = 0.757. This indicates that the proposed method could be an adequate solution for the reduction of falsely detected treetops before tree crown segmentation, especially in deciduous forests.",
publisher = "MDPI",
journal = "Remote Sensing, 2022, 14(21), 5345",
title = "Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest",
volume = "14",
doi = "10.3390/rs14215345"
}

Brodić, N., Cvijetinović, Ž., Milenković, M., Kovačević, J., Stančić, N., Mitrović, M.,& Mihajlović, D.. (2022). Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest. in Remote Sensing, 2022, 14(21), 5345
MDPI., 14.
https://doi.org/10.3390/rs14215345

Brodić N, Cvijetinović Ž, Milenković M, Kovačević J, Stančić N, Mitrović M, Mihajlović D. Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest. in Remote Sensing, 2022, 14(21), 5345. 2022;14.
doi:10.3390/rs14215345 .

Brodić, Nenad, Cvijetinović, Željko, Milenković, Milutin, Kovačević, Jovan, Stančić, Nikola, Mitrović, Momir, Mihajlović, Dragan, "Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest" in Remote Sensing, 2022, 14(21), 5345, 14 (2022),
https://doi.org/10.3390/rs14215345 . .

TY  - THES
AU  - Kovačević, Jovan
PY  - 2022
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2696
AB  - Potrebe za kvalitetnim podacima kvantitativnih i kvalitativnih karakteristika šuma se povećavaju kako je pritisak na ovaj prirodni resurs sve veći. Podaci satelitskog osmatranja Zemlje su se pokazali kao pogodna alternativa terenskim metodama za prikupljanje informacija o šumama. Osnovni ciljevi istraživanja u okviru ove disertacije su analiza, razvoj i unapređenje metodologije za kartiranje tipova šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje. Predložena metodologija se u osnovi oslanja na izdvajanje tematskih informacija iz satelitskih snimaka primenom nadziranih neparametarskih metoda klasifikacije, posebno tehnika mašinskog učenja. Istraživanje obuhvata utvrđivanje primenljivosti različitih tehnika mašinskog učenja (stabla odlučivanja, slučajne šume i gradijentnog pojačavanja) za kartiranje tipova šumske vegetacije, analizu različitih reprezentacija podataka radi naglašavanja prostornih i vremenskih aspekata u klasifikacionom modelu, kao i primenu tehnika za kreiranje optimalnog balansiranog skupa podataka i izbora atributa od značaja za kvalitetno kartiranje šumske vegetacije. Razvoj i testiranje predložene metodologije je izvršeno identifikacijom osam tipova šumske vegetacije na području Republike Srbije. Korišćeni su podaci satelitske misije Sentinel-2 iz 2019. godine u kombinaciji sa dodatnim izvorima podataka. Rezultati sprovedenih eksperimenata se podudaraju sa rezultatima sličnih istraživanja zasnovanih na optičkim satelitskim opažanjima visoke prostorne rezolucije. Na osnovu sprovedenih eksperimenata je zaključeno da je predložena metodologija primenljiva za kartiranje tipova šumske vegetacije u Srbiji. Iako je testiranje izvršeno na teritoriji Srbije, metodologija ima značajan potencijal da se primeni i na drugim područjima uz prilagođavanje klasifikacione šeme i dopune podataka za treniranje modela. Takođe, može se smatrati da je predložena metodologija opšteg tipa, tj. ona može biti relativno jednostavno prilagođena i drugim klasifikacionim problemima. Dodatna istraživanja su predviđena u budućnosti kako bi se ispitale prethodne pretpostavke.
AB  - The necessity for quality data on quantitative and qualitative characteristics of forests is increasing as the pressure on this natural resource rises. Satellite Earth observation data has proven to be a suitable alternative to field methods when it comes to collecting information about forests. The main goals of the research within this dissertation are the analysis, development and improvement of the methodology for mapping forest vegetation types using satellite Earth observation data. The proposed methodology relies on the extraction of thematic information from satellite imagery using supervised non-parametric classification methods, especially machine learning techniques. The research includes determining the applicability of different machine learning techniques (decision tree, random forest and gradient boosting) for mapping forest vegetation types, analysis of different data representations for emphasizing spatial and temporal aspects in the classification model, and applying techniques to create optimal balanced datasets and to determine optimal features for quality mapping of forest vegetation. The development and testing of the proposed methodology were performed by identifying eight forest vegetation types in the Republic of Serbia. Sentinel-2 satellite imagery from the 2019 was used in combination with additional data sources. The results of the conducted experiments match the results of similar studies which were based on high-resolution optical satellite imagery. In accordance with the conducted experiments, it can be concluded that the proposed methodology is applicable for mapping forest vegetation types in Serbia. While the testing was performed on the territory of Serbia, the methodology has significant potential to be applied in other regions as well, with the adjustment of the classification scheme and the additional data for model training. Also, the proposed methodology can be considered to be of a generic type, since it can be relatively easily adapted to other classification problems. Additional research is planned in the future to test these assumptions.
T1  - Kartiranje šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje korišćenjem tehnika mašinskog učenja
T1  - Mapping Forest Vegetation from Satellite Earth Observation Data Using Machine Learning Techniques
UR  - https://hdl.handle.net/21.15107/rcub_grafar_2696
ER  - 

@phdthesis{
author = "Kovačević, Jovan",
year = "2022",
abstract = "Potrebe za kvalitetnim podacima kvantitativnih i kvalitativnih karakteristika šuma se povećavaju kako je pritisak na ovaj prirodni resurs sve veći. Podaci satelitskog osmatranja Zemlje su se pokazali kao pogodna alternativa terenskim metodama za prikupljanje informacija o šumama. Osnovni ciljevi istraživanja u okviru ove disertacije su analiza, razvoj i unapređenje metodologije za kartiranje tipova šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje. Predložena metodologija se u osnovi oslanja na izdvajanje tematskih informacija iz satelitskih snimaka primenom nadziranih neparametarskih metoda klasifikacije, posebno tehnika mašinskog učenja. Istraživanje obuhvata utvrđivanje primenljivosti različitih tehnika mašinskog učenja (stabla odlučivanja, slučajne šume i gradijentnog pojačavanja) za kartiranje tipova šumske vegetacije, analizu različitih reprezentacija podataka radi naglašavanja prostornih i vremenskih aspekata u klasifikacionom modelu, kao i primenu tehnika za kreiranje optimalnog balansiranog skupa podataka i izbora atributa od značaja za kvalitetno kartiranje šumske vegetacije. Razvoj i testiranje predložene metodologije je izvršeno identifikacijom osam tipova šumske vegetacije na području Republike Srbije. Korišćeni su podaci satelitske misije Sentinel-2 iz 2019. godine u kombinaciji sa dodatnim izvorima podataka. Rezultati sprovedenih eksperimenata se podudaraju sa rezultatima sličnih istraživanja zasnovanih na optičkim satelitskim opažanjima visoke prostorne rezolucije. Na osnovu sprovedenih eksperimenata je zaključeno da je predložena metodologija primenljiva za kartiranje tipova šumske vegetacije u Srbiji. Iako je testiranje izvršeno na teritoriji Srbije, metodologija ima značajan potencijal da se primeni i na drugim područjima uz prilagođavanje klasifikacione šeme i dopune podataka za treniranje modela. Takođe, može se smatrati da je predložena metodologija opšteg tipa, tj. ona može biti relativno jednostavno prilagođena i drugim klasifikacionim problemima. Dodatna istraživanja su predviđena u budućnosti kako bi se ispitale prethodne pretpostavke., The necessity for quality data on quantitative and qualitative characteristics of forests is increasing as the pressure on this natural resource rises. Satellite Earth observation data has proven to be a suitable alternative to field methods when it comes to collecting information about forests. The main goals of the research within this dissertation are the analysis, development and improvement of the methodology for mapping forest vegetation types using satellite Earth observation data. The proposed methodology relies on the extraction of thematic information from satellite imagery using supervised non-parametric classification methods, especially machine learning techniques. The research includes determining the applicability of different machine learning techniques (decision tree, random forest and gradient boosting) for mapping forest vegetation types, analysis of different data representations for emphasizing spatial and temporal aspects in the classification model, and applying techniques to create optimal balanced datasets and to determine optimal features for quality mapping of forest vegetation. The development and testing of the proposed methodology were performed by identifying eight forest vegetation types in the Republic of Serbia. Sentinel-2 satellite imagery from the 2019 was used in combination with additional data sources. The results of the conducted experiments match the results of similar studies which were based on high-resolution optical satellite imagery. In accordance with the conducted experiments, it can be concluded that the proposed methodology is applicable for mapping forest vegetation types in Serbia. While the testing was performed on the territory of Serbia, the methodology has significant potential to be applied in other regions as well, with the adjustment of the classification scheme and the additional data for model training. Also, the proposed methodology can be considered to be of a generic type, since it can be relatively easily adapted to other classification problems. Additional research is planned in the future to test these assumptions.",
title = "Kartiranje šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje korišćenjem tehnika mašinskog učenja, Mapping Forest Vegetation from Satellite Earth Observation Data Using Machine Learning Techniques",
url = "https://hdl.handle.net/21.15107/rcub_grafar_2696"
}

Kovačević, J.. (2022). Kartiranje šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje korišćenjem tehnika mašinskog učenja. .
https://hdl.handle.net/21.15107/rcub_grafar_2696

Kovačević J. Kartiranje šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje korišćenjem tehnika mašinskog učenja. 2022;.
https://hdl.handle.net/21.15107/rcub_grafar_2696 .

Kovačević, Jovan, "Kartiranje šumske vegetacije na osnovu podataka satelitskog osmatranja Zemlje korišćenjem tehnika mašinskog učenja" (2022),
https://hdl.handle.net/21.15107/rcub_grafar_2696 .

TY  - JOUR
AU  - Polovina, Siniša
AU  - Radić, Boris
AU  - Ristić, Ratko
AU  - Kovačević, Jovan
AU  - Milčanović, Vukašin
AU  - Živanović, Nikola
PY  - 2021
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2357
AB  - Soil erosion is a global problem that negatively affects the quality of the environment, the availability of natural resources, as well as the safety of inhabitants. Soil erosion threatens the functioning of urban areas, which was the reason for choosing the territory of the Master Plan of Belgrade (Serbia) as the research area. The calculation of soil erosion loss was analyzed using the G2 erosion model. The model belongs to a group of empirical models and is based on the synthesis of the equation from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM). The estimation of soil degradation was analyzed in two time periods (2001 and 2019), which represent the time boundaries of the management of the Master Plan of Belgrade. The novel approach used in this research is based on using the land cover inventory as a dynamic indicator of the urbanization process. Land cover was identified using remote sensing, machine learning techniques, and the random forest algorithm applied to multispectral satellite images of the Landsat mission in combination with spectral indices. Climatic parameters were analyzed on the basis of data from meteorological stations (first scenario, i.e., 2001), as well as on simulations of changes based on climate scenario RCP8.5 (representative concentration pathways) concerning the current condition of the land cover (second scenario). A comparative analysis of the two time periods identified a slight reduction in total soil loss. For the first period, the average soil loss value is 4.11 t·ha−1·y−1. The analysis of the second period revealed an average value of 3.63 t·ha−1·y−1. However, the increase in non-porous surfaces has led to a change in the focus of soil degradation. Increased average soil loss as one of the catalysts of torrential flood frequencies registered on natural and semi-natural areas were 43.29% and 16.14%, respectively. These results are a significant contribution to the study of soil erosion in urban conditions under the impact of climate change.
PB  - MDPI
T2  - Applied Sciences
T1  - Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach
IS  - 9
SP  - 4154
VL  - 11
DO  - https://doi.org/10.3390/app11094154
ER  - 

@article{
author = "Polovina, Siniša and Radić, Boris and Ristić, Ratko and Kovačević, Jovan and Milčanović, Vukašin and Živanović, Nikola",
year = "2021",
abstract = "Soil erosion is a global problem that negatively affects the quality of the environment, the availability of natural resources, as well as the safety of inhabitants. Soil erosion threatens the functioning of urban areas, which was the reason for choosing the territory of the Master Plan of Belgrade (Serbia) as the research area. The calculation of soil erosion loss was analyzed using the G2 erosion model. The model belongs to a group of empirical models and is based on the synthesis of the equation from the Revised Universal Soil Loss Equation (RUSLE) and the Erosion Potential Method (EPM). The estimation of soil degradation was analyzed in two time periods (2001 and 2019), which represent the time boundaries of the management of the Master Plan of Belgrade. The novel approach used in this research is based on using the land cover inventory as a dynamic indicator of the urbanization process. Land cover was identified using remote sensing, machine learning techniques, and the random forest algorithm applied to multispectral satellite images of the Landsat mission in combination with spectral indices. Climatic parameters were analyzed on the basis of data from meteorological stations (first scenario, i.e., 2001), as well as on simulations of changes based on climate scenario RCP8.5 (representative concentration pathways) concerning the current condition of the land cover (second scenario). A comparative analysis of the two time periods identified a slight reduction in total soil loss. For the first period, the average soil loss value is 4.11 t·ha−1·y−1. The analysis of the second period revealed an average value of 3.63 t·ha−1·y−1. However, the increase in non-porous surfaces has led to a change in the focus of soil degradation. Increased average soil loss as one of the catalysts of torrential flood frequencies registered on natural and semi-natural areas were 43.29% and 16.14%, respectively. These results are a significant contribution to the study of soil erosion in urban conditions under the impact of climate change.",
publisher = "MDPI",
journal = "Applied Sciences",
title = "Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach",
number = "9",
pages = "4154",
volume = "11",
doi = "https://doi.org/10.3390/app11094154"
}

Polovina, S., Radić, B., Ristić, R., Kovačević, J., Milčanović, V.,& Živanović, N.. (2021). Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach. in Applied Sciences
MDPI., 11(9), 4154.
https://doi.org/https://doi.org/10.3390/app11094154

Polovina S, Radić B, Ristić R, Kovačević J, Milčanović V, Živanović N. Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach. in Applied Sciences. 2021;11(9):4154.
doi:https://doi.org/10.3390/app11094154 .

Polovina, Siniša, Radić, Boris, Ristić, Ratko, Kovačević, Jovan, Milčanović, Vukašin, Živanović, Nikola, "Soil Erosion Assessment and Prediction in Urban Landscapes: A New G2 Model Approach" in Applied Sciences, 11, no. 9 (2021):4154,
https://doi.org/https://doi.org/10.3390/app11094154 . .

TY  - JOUR
AU  - Kovačević, Jovan
AU  - Cvijetinović, Željko
AU  - Lakušić, Dmitar
AU  - Kuzmanović, Nevena
AU  - Šinžar-Sekulić, Jasmina
AU  - Mitrović, Momir
AU  - Stančić, Nikola
AU  - Brodić, Nenad
AU  - Mihajlović, Dragan
PY  - 2020
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/2057
AB  - The inventory of woody vegetation is of great importance for good forest management. Advancements of remote sensing techniques have provided excellent tools for such purposes, reducing the required amount of time and labor, yet with high accuracy and the information richness. Sentinel-2 is one of the relatively new satellite missions, whose 13 spectral bands and short revisit time proved to be very useful when it comes to forest monitoring. In this study, the novel spatio-temporal classification framework for mapping woody vegetation from Sentinel-2 multitemporal data has been proposed. The used framework is based on the probability random forest classification, where temporal information is explicitly defined in the model. Because of this, several predictions are made for each pixel of the study area, which allow for specific spatio-temporal aggregation to be performed. The proposed methodology has been successfully applied for mapping eight potential forest and shrubby vegetation types over the study area of Serbia. Several spatio-temporal aggregation approaches have been tested, divided into two main groups: pixel-based and neighborhood-based. The validation metrics show that determining the most common vegetation type classes in the neighborhood of 5 × 5 pixels provides the best results. The overall accuracy and kappa coefficient obtained from five-fold cross validation of the results are 82.97% and 0.75, respectively. The corresponding producer’s accuracies range from 36.74% to 97.99% and user’s accuracies range from 46.31% to 98.43%. The proposed methodology proved to be applicable for mapping woody vegetation in Serbia and shows a potential to be implemented in other areas as well. Further testing is necessary to confirm such assumptions.
PB  - MDPI
T2  - Remote Sensing
T1  - Spatio-Temporal Classification Framework for Mapping Woody Vegetation from Multi-Temporal Sentinel-2 Imagery
IS  - 17
SP  - 2845
VL  - 12
DO  - https://doi.org/10.3390/rs12172845
ER  - 

@article{
author = "Kovačević, Jovan and Cvijetinović, Željko and Lakušić, Dmitar and Kuzmanović, Nevena and Šinžar-Sekulić, Jasmina and Mitrović, Momir and Stančić, Nikola and Brodić, Nenad and Mihajlović, Dragan",
year = "2020",
abstract = "The inventory of woody vegetation is of great importance for good forest management. Advancements of remote sensing techniques have provided excellent tools for such purposes, reducing the required amount of time and labor, yet with high accuracy and the information richness. Sentinel-2 is one of the relatively new satellite missions, whose 13 spectral bands and short revisit time proved to be very useful when it comes to forest monitoring. In this study, the novel spatio-temporal classification framework for mapping woody vegetation from Sentinel-2 multitemporal data has been proposed. The used framework is based on the probability random forest classification, where temporal information is explicitly defined in the model. Because of this, several predictions are made for each pixel of the study area, which allow for specific spatio-temporal aggregation to be performed. The proposed methodology has been successfully applied for mapping eight potential forest and shrubby vegetation types over the study area of Serbia. Several spatio-temporal aggregation approaches have been tested, divided into two main groups: pixel-based and neighborhood-based. The validation metrics show that determining the most common vegetation type classes in the neighborhood of 5 × 5 pixels provides the best results. The overall accuracy and kappa coefficient obtained from five-fold cross validation of the results are 82.97% and 0.75, respectively. The corresponding producer’s accuracies range from 36.74% to 97.99% and user’s accuracies range from 46.31% to 98.43%. The proposed methodology proved to be applicable for mapping woody vegetation in Serbia and shows a potential to be implemented in other areas as well. Further testing is necessary to confirm such assumptions.",
publisher = "MDPI",
journal = "Remote Sensing",
title = "Spatio-Temporal Classification Framework for Mapping Woody Vegetation from Multi-Temporal Sentinel-2 Imagery",
number = "17",
pages = "2845",
volume = "12",
doi = "https://doi.org/10.3390/rs12172845"
}

Kovačević, J., Cvijetinović, Ž., Lakušić, D., Kuzmanović, N., Šinžar-Sekulić, J., Mitrović, M., Stančić, N., Brodić, N.,& Mihajlović, D.. (2020). Spatio-Temporal Classification Framework for Mapping Woody Vegetation from Multi-Temporal Sentinel-2 Imagery. in Remote Sensing
MDPI., 12(17), 2845.
https://doi.org/https://doi.org/10.3390/rs12172845

Kovačević J, Cvijetinović Ž, Lakušić D, Kuzmanović N, Šinžar-Sekulić J, Mitrović M, Stančić N, Brodić N, Mihajlović D. Spatio-Temporal Classification Framework for Mapping Woody Vegetation from Multi-Temporal Sentinel-2 Imagery. in Remote Sensing. 2020;12(17):2845.
doi:https://doi.org/10.3390/rs12172845 .

Kovačević, Jovan, Cvijetinović, Željko, Lakušić, Dmitar, Kuzmanović, Nevena, Šinžar-Sekulić, Jasmina, Mitrović, Momir, Stančić, Nikola, Brodić, Nenad, Mihajlović, Dragan, "Spatio-Temporal Classification Framework for Mapping Woody Vegetation from Multi-Temporal Sentinel-2 Imagery" in Remote Sensing, 12, no. 17 (2020):2845,
https://doi.org/https://doi.org/10.3390/rs12172845 . .

TY  - JOUR
AU  - Kovačević, Jovan
AU  - Cvijetinović, Željko
AU  - Stančić, Nikola
AU  - Brodić, Nenad
AU  - Mihajlović, Dragan
PY  - 2020
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1908
AB  - ESA CCI SM products have provided remotely-sensed surface soil moisture (SSM) content with the best spatial and temporal coverage thus far, although its output spatial resolution of 25 km is too coarse for many regional and local applications. The downscaling methodology presented in this paper improves ESA CCI SM spatial resolution to 1 km using two-step approach. The first step is used as a data engineering tool and its output is used as an input for the Random forest model in the second step. In addition to improvements in terms of spatial resolution, the approach also considers the problem of data gaps. The filling of these gaps is the initial step of the procedure, which in the end produces a continuous product in both temporal and spatial domains. The methodology uses combined active and passive ESA CCI SM products in addition to in situ soil moisture observations and the set of auxiliary downscaling predictors. The research tested several variants of Random forest models to determine the best combination of ESA CCI SM products. The conclusion is that synergic use of all ESA CCI SM products together with the auxiliary datasets in the downscaling procedure provides better results than using just one type of ESA CCI SM product alone. The methodology was applied for obtaining SSM maps for the area of California, USA during 2016. The accuracy of tested models was validated using five-fold cross-validation against in situ data and the best variation of model achieved RMSE, R2 and MAE of 0.0518 m3/m3, 0.7312 and 0.0374 m3/m3, respectively. The methodology proved to be useful for generating high-resolution SSM products, although additional improvements are necessary.
PB  - MDPI
T2  - Remote Sensing
T1  - New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture
IS  - 20
SP  - 1119
VL  - 12
DO  - 10.3390/rs12071119
ER  - 

@article{
author = "Kovačević, Jovan and Cvijetinović, Željko and Stančić, Nikola and Brodić, Nenad and Mihajlović, Dragan",
year = "2020",
abstract = "ESA CCI SM products have provided remotely-sensed surface soil moisture (SSM) content with the best spatial and temporal coverage thus far, although its output spatial resolution of 25 km is too coarse for many regional and local applications. The downscaling methodology presented in this paper improves ESA CCI SM spatial resolution to 1 km using two-step approach. The first step is used as a data engineering tool and its output is used as an input for the Random forest model in the second step. In addition to improvements in terms of spatial resolution, the approach also considers the problem of data gaps. The filling of these gaps is the initial step of the procedure, which in the end produces a continuous product in both temporal and spatial domains. The methodology uses combined active and passive ESA CCI SM products in addition to in situ soil moisture observations and the set of auxiliary downscaling predictors. The research tested several variants of Random forest models to determine the best combination of ESA CCI SM products. The conclusion is that synergic use of all ESA CCI SM products together with the auxiliary datasets in the downscaling procedure provides better results than using just one type of ESA CCI SM product alone. The methodology was applied for obtaining SSM maps for the area of California, USA during 2016. The accuracy of tested models was validated using five-fold cross-validation against in situ data and the best variation of model achieved RMSE, R2 and MAE of 0.0518 m3/m3, 0.7312 and 0.0374 m3/m3, respectively. The methodology proved to be useful for generating high-resolution SSM products, although additional improvements are necessary.",
publisher = "MDPI",
journal = "Remote Sensing",
title = "New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture",
number = "20",
pages = "1119",
volume = "12",
doi = "10.3390/rs12071119"
}

Kovačević, J., Cvijetinović, Ž., Stančić, N., Brodić, N.,& Mihajlović, D.. (2020). New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture. in Remote Sensing
MDPI., 12(20), 1119.
https://doi.org/10.3390/rs12071119

Kovačević J, Cvijetinović Ž, Stančić N, Brodić N, Mihajlović D. New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture. in Remote Sensing. 2020;12(20):1119.
doi:10.3390/rs12071119 .

Kovačević, Jovan, Cvijetinović, Željko, Stančić, Nikola, Brodić, Nenad, Mihajlović, Dragan, "New Downscaling Approach Using ESA CCI SM Products for Obtaining High Resolution Surface Soil Moisture" in Remote Sensing, 12, no. 20 (2020):1119,
https://doi.org/10.3390/rs12071119 . .

TY  - CONF
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
AU  - Cvijetinović, Željko
AU  - Mihajlović, Dragan
AU  - Brodić, Nenad
PY  - 2019
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1921
AB  - One of the dimensions describing accessibility to health services is its spatial component. This paper presents the methodology of using GIS technologies for the analysis of existing locations of health institutions in Serbia. The methodology includes determining the coordinates of hospitals using the geotagging, on the basis of which isochrons are created with 10 minutes time interval. For that purpose, the road network and functionalities provided by HERE Maps and its APIs are used. This service is selected since it offers high quality and complete data related to the network of roads in the territory of interest. Taking demographic data into account, the goal is to examine the impact that the distribution of institutions has on the population, first of all as the percentage of the population living at a certain distance from the nearest institution. The obtained results can be significant for future development, as critical spots with poor accessibility can be identified. These locations are suitable for the construction of new health care facilities.
AB  - Jedna od dimenzija koje opisuju pristupačnost zdravstvenim uslugama jeste prostorna komponenta. U ovom radu je predstavljena metodologija korišćenja GIS tehnologija za potrebe analize postojećih lokacija zdravstvenih ustanova u Srbiji. Metodologija obuhvata određivanje koordinata bolnica u postupku geotagovanja, na osnovu kojih se kreiraju izohrone s vremenskim intervalom od 10 minuta. Tom prilikom se koriste putna mreža i funkcionalnosti koje pruža HERE Maps u okviru svojih API-ja. Ovaj servis je odabran zato što nudi kvalitetne i kompletne podatke koji se odnose na mrežu saobraćajnica teritorije od interesa. Uzimajući u obzir demografske podatke, cilj je sagledavanje uticaja rasporeda ovih ustanova na stanovništvo, najpre u pogledu procenta stanovništva koji živi na određenoj udaljenosti od najbliže ustanove. Dobijeni rezultati mogu biti značajni za budući razvoj, s obzirom na to da se mogu utvrditi kritična mesta na kojima je pristupačnost loša. Upravo te lokacije jesu pogodne za izgradnju novih zdravstvenih ustanova.
PB  - University of East Sarajevo, Faculty of Transport and Traffic Engineering Doboj
C3  - VII International Symposium NEW HORIZONS 2019 of Transport and Communications
T1  - Spatial Accessibility Analysis of Health Care Facilities in Serbia
T1  - Analiza prostorne pristupačnosti zdravstvenim ustanovama u Srbiji
EP  - 534
SP  - 527
VL  - 7
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1921
ER  - 

@conference{
author = "Kovačević, Jovan and Stančić, Nikola and Cvijetinović, Željko and Mihajlović, Dragan and Brodić, Nenad",
year = "2019",
abstract = "One of the dimensions describing accessibility to health services is its spatial component. This paper presents the methodology of using GIS technologies for the analysis of existing locations of health institutions in Serbia. The methodology includes determining the coordinates of hospitals using the geotagging, on the basis of which isochrons are created with 10 minutes time interval. For that purpose, the road network and functionalities provided by HERE Maps and its APIs are used. This service is selected since it offers high quality and complete data related to the network of roads in the territory of interest. Taking demographic data into account, the goal is to examine the impact that the distribution of institutions has on the population, first of all as the percentage of the population living at a certain distance from the nearest institution. The obtained results can be significant for future development, as critical spots with poor accessibility can be identified. These locations are suitable for the construction of new health care facilities., Jedna od dimenzija koje opisuju pristupačnost zdravstvenim uslugama jeste prostorna komponenta. U ovom radu je predstavljena metodologija korišćenja GIS tehnologija za potrebe analize postojećih lokacija zdravstvenih ustanova u Srbiji. Metodologija obuhvata određivanje koordinata bolnica u postupku geotagovanja, na osnovu kojih se kreiraju izohrone s vremenskim intervalom od 10 minuta. Tom prilikom se koriste putna mreža i funkcionalnosti koje pruža HERE Maps u okviru svojih API-ja. Ovaj servis je odabran zato što nudi kvalitetne i kompletne podatke koji se odnose na mrežu saobraćajnica teritorije od interesa. Uzimajući u obzir demografske podatke, cilj je sagledavanje uticaja rasporeda ovih ustanova na stanovništvo, najpre u pogledu procenta stanovništva koji živi na određenoj udaljenosti od najbliže ustanove. Dobijeni rezultati mogu biti značajni za budući razvoj, s obzirom na to da se mogu utvrditi kritična mesta na kojima je pristupačnost loša. Upravo te lokacije jesu pogodne za izgradnju novih zdravstvenih ustanova.",
publisher = "University of East Sarajevo, Faculty of Transport and Traffic Engineering Doboj",
journal = "VII International Symposium NEW HORIZONS 2019 of Transport and Communications",
title = "Spatial Accessibility Analysis of Health Care Facilities in Serbia, Analiza prostorne pristupačnosti zdravstvenim ustanovama u Srbiji",
pages = "534-527",
volume = "7",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1921"
}

Kovačević, J., Stančić, N., Cvijetinović, Ž., Mihajlović, D.,& Brodić, N.. (2019). Spatial Accessibility Analysis of Health Care Facilities in Serbia. in VII International Symposium NEW HORIZONS 2019 of Transport and Communications
University of East Sarajevo, Faculty of Transport and Traffic Engineering Doboj., 7, 527-534.
https://hdl.handle.net/21.15107/rcub_grafar_1921

Kovačević J, Stančić N, Cvijetinović Ž, Mihajlović D, Brodić N. Spatial Accessibility Analysis of Health Care Facilities in Serbia. in VII International Symposium NEW HORIZONS 2019 of Transport and Communications. 2019;7:527-534.
https://hdl.handle.net/21.15107/rcub_grafar_1921 .

Kovačević, Jovan, Stančić, Nikola, Cvijetinović, Željko, Mihajlović, Dragan, Brodić, Nenad, "Spatial Accessibility Analysis of Health Care Facilities in Serbia" in VII International Symposium NEW HORIZONS 2019 of Transport and Communications, 7 (2019):527-534,
https://hdl.handle.net/21.15107/rcub_grafar_1921 .

TY  - CONF
AU  - Brodić, Nenad
AU  - Milić, Stevan
AU  - Mitrović, Momir
AU  - Cvijetinović, Željko
AU  - Mihajlović, Dragan
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
PY  - 2019
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1966
AB  - The methodology for modeling the distribution of certain air pollutant for the city of Belgrade in winter 2015 is presented in the paper. Land Use Regression (LUR) was used for modeling and visualization of spatial distribution of air pollution concentration in the city. NO2 concentrations were sampled at 46 locations, and predictive variables were calculated based on the road category, traffic intensity, demographic data, altitude, household furnaces and land use. These variables were calculated using buffers of different sizes. Linear regressions between NO2 and predictive spatial variables were calculated. Afterwards, the most significant predictors were used for multivariate regression model. Quality of the final model was checked using measurement available at certain locations. The RMSE of 9.8 μg/m³ and the coefficient of determination (R2) of 0.6 were obtained. These results indicate that traffic has the largest impact on air pollution concentration especially near the major roads. Prediction should help in deciding which air protection measures are to be taken in order to preserve and improve the city environment. The lack of data that are collected by using quite a few sensor stations is still rather limiting for the successful monitoring of air pollution in the city of Belgrade.
PB  - University of Belgrade - Faculty of Civil Engineering
C3  - 4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019
T1  - Monitoring Air Pollution Using GIS: Case Study for the City of Belgrade
EP  - 25
SP  - 18
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1966
ER  - 

@conference{
author = "Brodić, Nenad and Milić, Stevan and Mitrović, Momir and Cvijetinović, Željko and Mihajlović, Dragan and Kovačević, Jovan and Stančić, Nikola",
year = "2019",
abstract = "The methodology for modeling the distribution of certain air pollutant for the city of Belgrade in winter 2015 is presented in the paper. Land Use Regression (LUR) was used for modeling and visualization of spatial distribution of air pollution concentration in the city. NO2 concentrations were sampled at 46 locations, and predictive variables were calculated based on the road category, traffic intensity, demographic data, altitude, household furnaces and land use. These variables were calculated using buffers of different sizes. Linear regressions between NO2 and predictive spatial variables were calculated. Afterwards, the most significant predictors were used for multivariate regression model. Quality of the final model was checked using measurement available at certain locations. The RMSE of 9.8 μg/m³ and the coefficient of determination (R2) of 0.6 were obtained. These results indicate that traffic has the largest impact on air pollution concentration especially near the major roads. Prediction should help in deciding which air protection measures are to be taken in order to preserve and improve the city environment. The lack of data that are collected by using quite a few sensor stations is still rather limiting for the successful monitoring of air pollution in the city of Belgrade.",
publisher = "University of Belgrade - Faculty of Civil Engineering",
journal = "4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019",
title = "Monitoring Air Pollution Using GIS: Case Study for the City of Belgrade",
pages = "25-18",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1966"
}

Brodić, N., Milić, S., Mitrović, M., Cvijetinović, Ž., Mihajlović, D., Kovačević, J.,& Stančić, N.. (2019). Monitoring Air Pollution Using GIS: Case Study for the City of Belgrade. in 4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019
University of Belgrade - Faculty of Civil Engineering., 18-25.
https://hdl.handle.net/21.15107/rcub_grafar_1966

Brodić N, Milić S, Mitrović M, Cvijetinović Ž, Mihajlović D, Kovačević J, Stančić N. Monitoring Air Pollution Using GIS: Case Study for the City of Belgrade. in 4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019. 2019;:18-25.
https://hdl.handle.net/21.15107/rcub_grafar_1966 .

Brodić, Nenad, Milić, Stevan, Mitrović, Momir, Cvijetinović, Željko, Mihajlović, Dragan, Kovačević, Jovan, Stančić, Nikola, "Monitoring Air Pollution Using GIS: Case Study for the City of Belgrade" in 4th BAB International Conference Decoding Balkan: Architecture, Urbanism, Planning, Belgrade, 2019 (2019):18-25,
https://hdl.handle.net/21.15107/rcub_grafar_1966 .

TY  - CONF
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
PY  - 2019
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1850
AB  - Breast cancer screening involves recognizing so far unrecognized disease using a screening test, in particular case using the mammographic examination method. The high price of a single mammogram and the relatively large population of the women who need to be examined make screening challenging, especially for less developed countries such as the Republic of Serbia. Within this paper an analysis of available equipment for breast cancer screening – mammography in the Republic of Serbia was performed. As a result, series of choropleth maps were made, from which potentially problematic areas in the Republic of Serbia can be determined. All processing is done using the "R" programming language, and all used data are available for free download and use.
AB  - Скрининг рака дојке подразумева препознавање до тог тренутка непрепознате болести коришћењем скрининг теста, методом мaмогрaфског прегледа. Висока цена појединачног мамографа, а релативно велика популација жена коју треба прегледати, чине организовани скрининг изазовом, посебно за слабије развијене државе попут Републике Србије. У оквиру овог рада извршена је анализа расположиве опреме за скрининг рака дојке – мамографа у Републици Србији. Као резултат, направљена је серија хороплет карата на којима се одговарајућом скалом боја могу уочити потенцијално проблематичне области у Републици Србији. Сва обрада је извршена коришћењем „R“ програмског језика, а сви искоришћени подаци су доступни за слободно преузимање и коришћење.
PB  - ГИС Центар, Београд, Србија
C3  - ГИС форум 2019.
T1  - Analysis Of Breast Cancer Screening Equipment In The Republic Of Serbia
T1  - Анализа опреме за скрининг рака дојке у Републици Србији
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1850
ER  - 

@conference{
author = "Kovačević, Jovan and Stančić, Nikola",
year = "2019",
abstract = "Breast cancer screening involves recognizing so far unrecognized disease using a screening test, in particular case using the mammographic examination method. The high price of a single mammogram and the relatively large population of the women who need to be examined make screening challenging, especially for less developed countries such as the Republic of Serbia. Within this paper an analysis of available equipment for breast cancer screening – mammography in the Republic of Serbia was performed. As a result, series of choropleth maps were made, from which potentially problematic areas in the Republic of Serbia can be determined. All processing is done using the "R" programming language, and all used data are available for free download and use., Скрининг рака дојке подразумева препознавање до тог тренутка непрепознате болести коришћењем скрининг теста, методом мaмогрaфског прегледа. Висока цена појединачног мамографа, а релативно велика популација жена коју треба прегледати, чине организовани скрининг изазовом, посебно за слабије развијене државе попут Републике Србије. У оквиру овог рада извршена је анализа расположиве опреме за скрининг рака дојке – мамографа у Републици Србији. Као резултат, направљена је серија хороплет карата на којима се одговарајућом скалом боја могу уочити потенцијално проблематичне области у Републици Србији. Сва обрада је извршена коришћењем „R“ програмског језика, а сви искоришћени подаци су доступни за слободно преузимање и коришћење.",
publisher = "ГИС Центар, Београд, Србија",
journal = "ГИС форум 2019.",
title = "Analysis Of Breast Cancer Screening Equipment In The Republic Of Serbia, Анализа опреме за скрининг рака дојке у Републици Србији",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1850"
}

Kovačević, J.,& Stančić, N.. (2019). Analysis Of Breast Cancer Screening Equipment In The Republic Of Serbia. in ГИС форум 2019.
ГИС Центар, Београд, Србија..
https://hdl.handle.net/21.15107/rcub_grafar_1850

Kovačević J, Stančić N. Analysis Of Breast Cancer Screening Equipment In The Republic Of Serbia. in ГИС форум 2019.. 2019;.
https://hdl.handle.net/21.15107/rcub_grafar_1850 .

Kovačević, Jovan, Stančić, Nikola, "Analysis Of Breast Cancer Screening Equipment In The Republic Of Serbia" in ГИС форум 2019. (2019),
https://hdl.handle.net/21.15107/rcub_grafar_1850 .

TY  - CONF
AU  - Stančić, Nikola
AU  - Kovačević, Jovan
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1849
AB  - This paper presents the possibility of applications of GIS technologies on remote sensing data in order to understand the trends of the mine expansion and thereby enable putting these processes under control. The proposed solution includes creating a web mapping service that provides the opportunity for an interested user to gain insight into the status of the mine excavation in different epochs, as well as an overview of the changes that occurred during the period between certain two epochs. The final web service is in the form of a geoportal and has a set of functionalities that meet the needs of the different profiles of users. The example shows оpen-pit copper mines of copper mining and smelting complex located in Bor, Serbia.
AB  - У раду је предочена могућност примене ГИС технологија над подацима даљинске детекције, са циљем да се сагледају трендови ширења копова и омогућило увођење ових процеса под контролу. Предлог решења јесте креирање веб-картографског сервиса који заинтересованом кориснику омогућује да добије увид у стање површинских копова у различитим епохама, као и преглед промена које су настале у периоду између одређених двеју епоха. Коначни веб-сервис има форму геопортала и поседује сет функционалности које задовољавају потребе корисника различитих профила. За пример су узети површински копови рудника бакра Рударско-топионичарског басена Бор.
PB  - ГИС Центар, Београд, Србија
C3  - ГИС форум 2018.
T1  - GIS Technologies In Monitoring Changes Of Bor Оpen-Pit Copper Mine
T1  - ГИС технологије у праћењу промена на површинским коповима рудника бакра Бор
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1849
ER  - 

@conference{
author = "Stančić, Nikola and Kovačević, Jovan",
year = "2018",
abstract = "This paper presents the possibility of applications of GIS technologies on remote sensing data in order to understand the trends of the mine expansion and thereby enable putting these processes under control. The proposed solution includes creating a web mapping service that provides the opportunity for an interested user to gain insight into the status of the mine excavation in different epochs, as well as an overview of the changes that occurred during the period between certain two epochs. The final web service is in the form of a geoportal and has a set of functionalities that meet the needs of the different profiles of users. The example shows оpen-pit copper mines of copper mining and smelting complex located in Bor, Serbia., У раду је предочена могућност примене ГИС технологија над подацима даљинске детекције, са циљем да се сагледају трендови ширења копова и омогућило увођење ових процеса под контролу. Предлог решења јесте креирање веб-картографског сервиса који заинтересованом кориснику омогућује да добије увид у стање површинских копова у различитим епохама, као и преглед промена које су настале у периоду између одређених двеју епоха. Коначни веб-сервис има форму геопортала и поседује сет функционалности које задовољавају потребе корисника различитих профила. За пример су узети површински копови рудника бакра Рударско-топионичарског басена Бор.",
publisher = "ГИС Центар, Београд, Србија",
journal = "ГИС форум 2018.",
title = "GIS Technologies In Monitoring Changes Of Bor Оpen-Pit Copper Mine, ГИС технологије у праћењу промена на површинским коповима рудника бакра Бор",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1849"
}

Stančić, N.,& Kovačević, J.. (2018). GIS Technologies In Monitoring Changes Of Bor Оpen-Pit Copper Mine. in ГИС форум 2018.
ГИС Центар, Београд, Србија..
https://hdl.handle.net/21.15107/rcub_grafar_1849

Stančić N, Kovačević J. GIS Technologies In Monitoring Changes Of Bor Оpen-Pit Copper Mine. in ГИС форум 2018.. 2018;.
https://hdl.handle.net/21.15107/rcub_grafar_1849 .

Stančić, Nikola, Kovačević, Jovan, "GIS Technologies In Monitoring Changes Of Bor Оpen-Pit Copper Mine" in ГИС форум 2018. (2018),
https://hdl.handle.net/21.15107/rcub_grafar_1849 .

TY  - CONF
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1848
AB  - Air temperature is one of the most often measured meteorological parameters. Precise air temperature measurements are done in meteorological stations, whose spatial distribution may be uneven and for some applications unsuitable. Therefore, in order to provide the necessary temperature model for the appropriate applications, prediction of air temperature is performed. This paper presents a methodology of stochastic prediction of air temperature using the programming language "R". An example of the analysis and selection of the optimal set of predictors necessary for the prediction of temperature is provided. As "R" is basically statistical package, at the same time its possibilities as a GIS tool are shown.
AB  - Температура ваздуха представља један од метеоролошких параметара који се најчешће мере. Прецизна мерења температуре ваздуха врше се у метеоролошким станицама, чији просторни размештај може бити неравномеран и за поједине примене неодговарајући. Због тога се прибегава предикцији температуре ваздуха, како би се обезбедио неопходни температурни модел за одговарајуће примене. У оквиру овог рада приказана је техника стохастичке предикције температуре ваздуха користећи се програмским језиком „R“. Приказан је и пример анализе и одабира оптималног сета предиктора неопходних за предикцију температуре. Како „R“ у основи представља статистички пакет, истовремено су приказане и његове могућности коришћења као ГИС алата.
PB  - ГИС Центар, Београд, Србија
T1  - Air Temperature Prediction
T1  - Предикција температуре ваздуха
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1848
ER  - 

@conference{
author = "Kovačević, Jovan and Stančić, Nikola",
year = "2018",
abstract = "Air temperature is one of the most often measured meteorological parameters. Precise air temperature measurements are done in meteorological stations, whose spatial distribution may be uneven and for some applications unsuitable. Therefore, in order to provide the necessary temperature model for the appropriate applications, prediction of air temperature is performed. This paper presents a methodology of stochastic prediction of air temperature using the programming language "R". An example of the analysis and selection of the optimal set of predictors necessary for the prediction of temperature is provided. As "R" is basically statistical package, at the same time its possibilities as a GIS tool are shown., Температура ваздуха представља један од метеоролошких параметара који се најчешће мере. Прецизна мерења температуре ваздуха врше се у метеоролошким станицама, чији просторни размештај може бити неравномеран и за поједине примене неодговарајући. Због тога се прибегава предикцији температуре ваздуха, како би се обезбедио неопходни температурни модел за одговарајуће примене. У оквиру овог рада приказана је техника стохастичке предикције температуре ваздуха користећи се програмским језиком „R“. Приказан је и пример анализе и одабира оптималног сета предиктора неопходних за предикцију температуре. Како „R“ у основи представља статистички пакет, истовремено су приказане и његове могућности коришћења као ГИС алата.",
publisher = "ГИС Центар, Београд, Србија",
title = "Air Temperature Prediction, Предикција температуре ваздуха",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1848"
}

Kovačević, J.,& Stančić, N.. (2018). Air Temperature Prediction. 
ГИС Центар, Београд, Србија..
https://hdl.handle.net/21.15107/rcub_grafar_1848

Kovačević J, Stančić N. Air Temperature Prediction. 2018;.
https://hdl.handle.net/21.15107/rcub_grafar_1848 .

Kovačević, Jovan, Stančić, Nikola, "Air Temperature Prediction" (2018),
https://hdl.handle.net/21.15107/rcub_grafar_1848 .

TY  - JOUR
AU  - Kovačević, Jovan
AU  - Stančić, Nikola
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/920
AB  - The airborne laser scanning has been proven as very efficient method for collecting the surface data. As ALS collects extremely large amount of data, efficient use of this data involves the use of some semi-automatic or automatic methods. For this purpose, large number of solutions, different in scope, cost and efficiency are available on the market. One of the available solutions is LAStools software package. Focus of this paper is on the functionalities of the LAStools software package, which are tested and assessed through the experiment. The experiment covered creation of standard topographic products from ALS point cloud using LAStools. At the end of this paper, conclusions about the possibilities of the LAStools software package are made, with a special overview of the advantages and disadvantages, the possibilities and shortcomings.
AB  - Laserska metoda snimanja iz vazduha se pokazala kao veoma efikasna za prikupljanje podataka o površi terena. Zbog izuzetno velike količine podataka koja je nastaje avio-laserskim skeniranjem, efikasno korišćenje ovih podataka podrazumeva korišćenje nekih poluautomatskih ili automatskih metoda. Za potrebe obrade podataka laserskog skeniranja na tržištu je na raspolaganju veliki broj rešenja, različitih po mogućnostima, ceni i efikasnosti. Jedno od takvih rešenja predstavlja LAStools softverski paket. Tema ovog rada su funkcionalnosti LAStools softverskog paketa, koje su eksperimentalno ispitane i ocenjene. Eksperiment je podrazumevao kreiranje standardnih topografskih produkata iz avio-oblaka tačaka primenom LAStools-a. Na kraju rada su doneti zaključci o mogućnostima LAStools softverskog paketa, uz poseban osvrt na prednosti i mane, mogućnosti i nedostatke.
PB  - Savez inženjera i tehničara Srbije, Beograd
T2  - Tehnika
T1  - Processing of ALS data using LAStools
T1  - Obrada podataka laserskog skeniranja korišćenjem LAStools softverskog paketa
EP  - 345
IS  - 3
SP  - 339
VL  - 73
DO  - 10.5937/tehnika1803339K
ER  - 

@article{
author = "Kovačević, Jovan and Stančić, Nikola",
year = "2018",
abstract = "The airborne laser scanning has been proven as very efficient method for collecting the surface data. As ALS collects extremely large amount of data, efficient use of this data involves the use of some semi-automatic or automatic methods. For this purpose, large number of solutions, different in scope, cost and efficiency are available on the market. One of the available solutions is LAStools software package. Focus of this paper is on the functionalities of the LAStools software package, which are tested and assessed through the experiment. The experiment covered creation of standard topographic products from ALS point cloud using LAStools. At the end of this paper, conclusions about the possibilities of the LAStools software package are made, with a special overview of the advantages and disadvantages, the possibilities and shortcomings., Laserska metoda snimanja iz vazduha se pokazala kao veoma efikasna za prikupljanje podataka o površi terena. Zbog izuzetno velike količine podataka koja je nastaje avio-laserskim skeniranjem, efikasno korišćenje ovih podataka podrazumeva korišćenje nekih poluautomatskih ili automatskih metoda. Za potrebe obrade podataka laserskog skeniranja na tržištu je na raspolaganju veliki broj rešenja, različitih po mogućnostima, ceni i efikasnosti. Jedno od takvih rešenja predstavlja LAStools softverski paket. Tema ovog rada su funkcionalnosti LAStools softverskog paketa, koje su eksperimentalno ispitane i ocenjene. Eksperiment je podrazumevao kreiranje standardnih topografskih produkata iz avio-oblaka tačaka primenom LAStools-a. Na kraju rada su doneti zaključci o mogućnostima LAStools softverskog paketa, uz poseban osvrt na prednosti i mane, mogućnosti i nedostatke.",
publisher = "Savez inženjera i tehničara Srbije, Beograd",
journal = "Tehnika",
title = "Processing of ALS data using LAStools, Obrada podataka laserskog skeniranja korišćenjem LAStools softverskog paketa",
pages = "345-339",
number = "3",
volume = "73",
doi = "10.5937/tehnika1803339K"
}

Kovačević, J.,& Stančić, N.. (2018). Processing of ALS data using LAStools. in Tehnika
Savez inženjera i tehničara Srbije, Beograd., 73(3), 339-345.
https://doi.org/10.5937/tehnika1803339K

Kovačević J, Stančić N. Processing of ALS data using LAStools. in Tehnika. 2018;73(3):339-345.
doi:10.5937/tehnika1803339K .

Kovačević, Jovan, Stančić, Nikola, "Processing of ALS data using LAStools" in Tehnika, 73, no. 3 (2018):339-345,
https://doi.org/10.5937/tehnika1803339K . .

TY  - JOUR
AU  - Stančić, Nikola
AU  - Kovačević, Jovan
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/927
AB  - Vehicle routing plays a major role in the industry, primarily in companies that organize the transport of goods to end-users. The theoretical background of the vehicle routing problem has been known for many years and it has been the basis for developing a lot of commercial software solutions. However, in practice, there is a barrier in the form of the lack of affordable software solutions. The difficult access to quality and reliable spatial data relating to the road network is also a limitation. This paper looks into the possibilities of applying open source software to solve this NP-difficult problem. The free spatial data from OpenStreetMap, a joint project of the virtual community, was used as a basis for modeling the graph of the road network. The experiment was carried out over the data on vehicles and users of the specific retail chain and relates to the territory of Serbia.
AB  - Rutiranje vozila ima veliku ulogu u industriji, prvenstveno u kompanijama koje se bave organizovanjem transporta dobara do krajnjih korisnika. Teorijska pozadina problema rutiranja vozila je već dugi niz godina poznata i na osnovu nje je razvijeno mnoštvo komercijalnih softverskih rešenja. Međutim, u praksi se javlja prepreka u vidu nedostatka pristupačnih softverskih rešenja. Ograničenje predstavlja i otežan pristup kvalitetnim i pouzdanim prostornim podacima koji se odnose na putnu mrežu. U radu su ispitane mogućnosti primene softvera otvorenog koda za rešavanje ovog NP-teškog problema. Kao osnova za modelovanje grafa mreže saobraćajnica, uzeti su slobodni prostorni podaci OpenStreetMapa, udruženog projekta virtualne zajednice. Eksperiment je izvršen nad podacima o vozilima i korisnicima jednog trgovinskog lanca i odnosi se na područje Srbije.
PB  - Savez inženjera i tehničara Srbije, Beograd
T2  - Tehnika
T1  - Designing optimal transport routes using open-source software
T1  - Izrada optimalnih transportnih ruta korišćenjem softvera otvorenog koda
EP  - 493
IS  - 4
SP  - 486
VL  - 73
DO  - 10.5937/tehnika1804486S
ER  - 

@article{
author = "Stančić, Nikola and Kovačević, Jovan",
year = "2018",
abstract = "Vehicle routing plays a major role in the industry, primarily in companies that organize the transport of goods to end-users. The theoretical background of the vehicle routing problem has been known for many years and it has been the basis for developing a lot of commercial software solutions. However, in practice, there is a barrier in the form of the lack of affordable software solutions. The difficult access to quality and reliable spatial data relating to the road network is also a limitation. This paper looks into the possibilities of applying open source software to solve this NP-difficult problem. The free spatial data from OpenStreetMap, a joint project of the virtual community, was used as a basis for modeling the graph of the road network. The experiment was carried out over the data on vehicles and users of the specific retail chain and relates to the territory of Serbia., Rutiranje vozila ima veliku ulogu u industriji, prvenstveno u kompanijama koje se bave organizovanjem transporta dobara do krajnjih korisnika. Teorijska pozadina problema rutiranja vozila je već dugi niz godina poznata i na osnovu nje je razvijeno mnoštvo komercijalnih softverskih rešenja. Međutim, u praksi se javlja prepreka u vidu nedostatka pristupačnih softverskih rešenja. Ograničenje predstavlja i otežan pristup kvalitetnim i pouzdanim prostornim podacima koji se odnose na putnu mrežu. U radu su ispitane mogućnosti primene softvera otvorenog koda za rešavanje ovog NP-teškog problema. Kao osnova za modelovanje grafa mreže saobraćajnica, uzeti su slobodni prostorni podaci OpenStreetMapa, udruženog projekta virtualne zajednice. Eksperiment je izvršen nad podacima o vozilima i korisnicima jednog trgovinskog lanca i odnosi se na područje Srbije.",
publisher = "Savez inženjera i tehničara Srbije, Beograd",
journal = "Tehnika",
title = "Designing optimal transport routes using open-source software, Izrada optimalnih transportnih ruta korišćenjem softvera otvorenog koda",
pages = "493-486",
number = "4",
volume = "73",
doi = "10.5937/tehnika1804486S"
}

Stančić, N.,& Kovačević, J.. (2018). Designing optimal transport routes using open-source software. in Tehnika
Savez inženjera i tehničara Srbije, Beograd., 73(4), 486-493.
https://doi.org/10.5937/tehnika1804486S

Stančić N, Kovačević J. Designing optimal transport routes using open-source software. in Tehnika. 2018;73(4):486-493.
doi:10.5937/tehnika1804486S .

Stančić, Nikola, Kovačević, Jovan, "Designing optimal transport routes using open-source software" in Tehnika, 73, no. 4 (2018):486-493,
https://doi.org/10.5937/tehnika1804486S . .