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  - Višnjevac, Nenad
AU  - Cvijetinović, Željko
AU  - Bajat, Branislav
AU  - Radić, Boris
AU  - Ristić, Ratko
AU  - Milčanović, Vukašin
PY  - 2013
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/491
AB  - Very often, outputs provided by GIS functions and analysis are assumed as exact results. However, they are influenced by certain uncertainty which may affect the decisions based on those results. It is very complex and almost impossible to calculate that uncertainty using classical mathematical models because of very complex algorithms that are used in GIS analyses. In this paper we discuss an alternative method, i.e. the use of stochastic Monte Carlo simulations to estimate the uncertainty of flow accumulation. The case study area included the broader area of the Municipality of Čačak, where Monte Carlo stochastic simulations were applied in order to create one hundred possible outputs of flow accumulation. A statistical analysis was performed on the basis of these versions, and the 'most likely' version of flow accumulation in association with its confidence bounds (standard deviation) was created. Further, this paper describes the most important phases in the process of estimating uncertainty, such as variogram modelling and chooses the right number of simulations. Finally, it makes suggestions on how to effectively use and discuss the results and their practical significance.
AB  - Izlazni rezultati dobijeni primenom GIS funkcija i alatki za analizu, obično se podrazumevaju kao tačni, međutim i oni su podložni nesigurnostima koje mogu uticati na odluke bazirane na tim istim rezultatima. Ocena uticaja nesigurnosti rezultata je veoma kompleksna i često nemoguća primenom standardnih matematičkih metoda s obzirom na veoma kompleksne algoritme koji se koriste u GIS analizama. U ovom radu razmatrano je alternativno rešenje kod ocene nesigurnosti prostorne koncentracije oticaja, primenom Monte Karlo stohastičkih simulacija. Za područje šireg obuhvata opštine Čačak generisano je sto mogućih izlaznih verzija rezultata prostorne koncentracije oticaja primenom Monte Karlo stohastičkih simulacija. Na osnovu njih, uz odgovarajuće statističke analize dobijena je 'najverovatnija' verzija prostorne koncentracije oticaja uz pripadajući interval poverenja odnosno standardne devijacije dobijenih rešenja. U radu su opisane najznačajnije faze u procesu ocene nesigurnosti, poput modeliranja variograma i odabira broja simulacija. Takođe je data i preporuka kako najefikasnije primeniti i diskutovati dobijene rezultate i njihovu značajnost.
PB  - Univerzitet u Beogradu - Šumarski fakultet, Beograd
T2  - Glasnik Šumarskog fakulteta
T1  - Estimation of flow accumulation uncertainty by Monte Carlo stochastic simulations
T1  - Ocena nesigurnosti prostorne koncentracije oticaja primenom Monte Karlo stohastičkih simulacija
EP  - 24
IS  - 108
SP  - 7
DO  - 10.2298/GSF1308007V
ER  - 

@article{
author = "Višnjevac, Nenad and Cvijetinović, Željko and Bajat, Branislav and Radić, Boris and Ristić, Ratko and Milčanović, Vukašin",
year = "2013",
abstract = "Very often, outputs provided by GIS functions and analysis are assumed as exact results. However, they are influenced by certain uncertainty which may affect the decisions based on those results. It is very complex and almost impossible to calculate that uncertainty using classical mathematical models because of very complex algorithms that are used in GIS analyses. In this paper we discuss an alternative method, i.e. the use of stochastic Monte Carlo simulations to estimate the uncertainty of flow accumulation. The case study area included the broader area of the Municipality of Čačak, where Monte Carlo stochastic simulations were applied in order to create one hundred possible outputs of flow accumulation. A statistical analysis was performed on the basis of these versions, and the 'most likely' version of flow accumulation in association with its confidence bounds (standard deviation) was created. Further, this paper describes the most important phases in the process of estimating uncertainty, such as variogram modelling and chooses the right number of simulations. Finally, it makes suggestions on how to effectively use and discuss the results and their practical significance., Izlazni rezultati dobijeni primenom GIS funkcija i alatki za analizu, obično se podrazumevaju kao tačni, međutim i oni su podložni nesigurnostima koje mogu uticati na odluke bazirane na tim istim rezultatima. Ocena uticaja nesigurnosti rezultata je veoma kompleksna i često nemoguća primenom standardnih matematičkih metoda s obzirom na veoma kompleksne algoritme koji se koriste u GIS analizama. U ovom radu razmatrano je alternativno rešenje kod ocene nesigurnosti prostorne koncentracije oticaja, primenom Monte Karlo stohastičkih simulacija. Za područje šireg obuhvata opštine Čačak generisano je sto mogućih izlaznih verzija rezultata prostorne koncentracije oticaja primenom Monte Karlo stohastičkih simulacija. Na osnovu njih, uz odgovarajuće statističke analize dobijena je 'najverovatnija' verzija prostorne koncentracije oticaja uz pripadajući interval poverenja odnosno standardne devijacije dobijenih rešenja. U radu su opisane najznačajnije faze u procesu ocene nesigurnosti, poput modeliranja variograma i odabira broja simulacija. Takođe je data i preporuka kako najefikasnije primeniti i diskutovati dobijene rezultate i njihovu značajnost.",
publisher = "Univerzitet u Beogradu - Šumarski fakultet, Beograd",
journal = "Glasnik Šumarskog fakulteta",
title = "Estimation of flow accumulation uncertainty by Monte Carlo stochastic simulations, Ocena nesigurnosti prostorne koncentracije oticaja primenom Monte Karlo stohastičkih simulacija",
pages = "24-7",
number = "108",
doi = "10.2298/GSF1308007V"
}

Višnjevac, N., Cvijetinović, Ž., Bajat, B., Radić, B., Ristić, R.,& Milčanović, V.. (2013). Estimation of flow accumulation uncertainty by Monte Carlo stochastic simulations. in Glasnik Šumarskog fakulteta
Univerzitet u Beogradu - Šumarski fakultet, Beograd.(108), 7-24.
https://doi.org/10.2298/GSF1308007V

Višnjevac N, Cvijetinović Ž, Bajat B, Radić B, Ristić R, Milčanović V. Estimation of flow accumulation uncertainty by Monte Carlo stochastic simulations. in Glasnik Šumarskog fakulteta. 2013;(108):7-24.
doi:10.2298/GSF1308007V .

Višnjevac, Nenad, Cvijetinović, Željko, Bajat, Branislav, Radić, Boris, Ristić, Ratko, Milčanović, Vukašin, "Estimation of flow accumulation uncertainty by Monte Carlo stochastic simulations" in Glasnik Šumarskog fakulteta, no. 108 (2013):7-24,
https://doi.org/10.2298/GSF1308007V . .