TY  - CONF
AU  - Marjanović, M.
AU  - Stojaković, A.
AU  - Abolmasov, Biljana
AU  - Đurić, D.
AU  - Đurić, Uroš
AU  - Krušić, Jelka
AU  - Andrejev, Katarina
AU  - Samardžić-Petrović, Mileva
PY  - 2018
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1602
AB  - Terroir depicts a set of pedologic, micro‐climatic and historical factors that have a say in deciding whether and where to practice viticulture and determines its qualitative and quantitative exploitation potential. For winemakers, it is paramount for targeting a viticulture variety. European winemakers use to guide their choices by the family tradition. Scientific breakthroughs, i.e. pedological characterization of the soil, introduced a new approach for viticulture, and drove the world‐leading wineries to turn to scientific approach in the last 30 years. In this research, we went one step further in respect to pedological approach. Since the soil itself is considered as a product of its bedrock and climate, it is logical to also include those factors that condition the properties of the soil itself in the terroir context, such as geological and morphologic factors (Burns, 2010). It is thereby, possible to perform a preliminary delineation of zones with suitable set of factors at regional scales, and direct the subsequent, more detailed soil investigations. By analyzing wider areas, it becomes possible to plan more strategically, especially when it comes to preservation of rare and indigenous vine varieties. From winemakers’ perspective, indigenous vine varieties represent the true genetic potential. Smederevka, which is shyly re‐introduced, but without any planning and consulting the profession is one such example. Before the 2nd World War, Smederevka (colloquially known as “the Yellow”) was grown predominantly in the Smederevo wine region, but with caution to the micro‐location, soil composition, slope aspect, sun reflection off the water surface, etc. The quality was unparalleled in comparison to the same vine from 1950–1990, a period marked by a high‐yield, collective farming practice of the “Godomin” company back in the socialism. Locality Plavinac in Smederevo (from experience) has the Smederevka vine with the best sensory characteristics, although micro‐localities Zlatno Brdo (Mons Aureus) and Petrijevo are more familiar.
PB  - Srpsko geološko društvo, Beograd
C3  - Knjiga apstrakata / 17. Kongres geologa Srbije, Vrnjačka Banja, 17-20. maj 2018. = Book of abstracts / 17th Serbian Geological Congress, Vrnjačka banja, Maz 17-20, 2018. Vol. 2
T1  - Geological, morphologic and pedologic components of the teroir of Smederevka
T1  - Geološki, morfološki i pedološki činioci teorara Smederevke
EP  - 813
SP  - 808
VL  - 2
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1602
ER  - 

@conference{
author = "Marjanović, M. and Stojaković, A. and Abolmasov, Biljana and Đurić, D. and Đurić, Uroš and Krušić, Jelka and Andrejev, Katarina and Samardžić-Petrović, Mileva",
year = "2018",
abstract = "Terroir depicts a set of pedologic, micro‐climatic and historical factors that have a say in deciding whether and where to practice viticulture and determines its qualitative and quantitative exploitation potential. For winemakers, it is paramount for targeting a viticulture variety. European winemakers use to guide their choices by the family tradition. Scientific breakthroughs, i.e. pedological characterization of the soil, introduced a new approach for viticulture, and drove the world‐leading wineries to turn to scientific approach in the last 30 years. In this research, we went one step further in respect to pedological approach. Since the soil itself is considered as a product of its bedrock and climate, it is logical to also include those factors that condition the properties of the soil itself in the terroir context, such as geological and morphologic factors (Burns, 2010). It is thereby, possible to perform a preliminary delineation of zones with suitable set of factors at regional scales, and direct the subsequent, more detailed soil investigations. By analyzing wider areas, it becomes possible to plan more strategically, especially when it comes to preservation of rare and indigenous vine varieties. From winemakers’ perspective, indigenous vine varieties represent the true genetic potential. Smederevka, which is shyly re‐introduced, but without any planning and consulting the profession is one such example. Before the 2nd World War, Smederevka (colloquially known as “the Yellow”) was grown predominantly in the Smederevo wine region, but with caution to the micro‐location, soil composition, slope aspect, sun reflection off the water surface, etc. The quality was unparalleled in comparison to the same vine from 1950–1990, a period marked by a high‐yield, collective farming practice of the “Godomin” company back in the socialism. Locality Plavinac in Smederevo (from experience) has the Smederevka vine with the best sensory characteristics, although micro‐localities Zlatno Brdo (Mons Aureus) and Petrijevo are more familiar.",
publisher = "Srpsko geološko društvo, Beograd",
journal = "Knjiga apstrakata / 17. Kongres geologa Srbije, Vrnjačka Banja, 17-20. maj 2018. = Book of abstracts / 17th Serbian Geological Congress, Vrnjačka banja, Maz 17-20, 2018. Vol. 2",
title = "Geological, morphologic and pedologic components of the teroir of Smederevka, Geološki, morfološki i pedološki činioci teorara Smederevke",
pages = "813-808",
volume = "2",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1602"
}

Marjanović, M., Stojaković, A., Abolmasov, B., Đurić, D., Đurić, U., Krušić, J., Andrejev, K.,& Samardžić-Petrović, M.. (2018). Geological, morphologic and pedologic components of the teroir of Smederevka. in Knjiga apstrakata / 17. Kongres geologa Srbije, Vrnjačka Banja, 17-20. maj 2018. = Book of abstracts / 17th Serbian Geological Congress, Vrnjačka banja, Maz 17-20, 2018. Vol. 2
Srpsko geološko društvo, Beograd., 2, 808-813.
https://hdl.handle.net/21.15107/rcub_grafar_1602

Marjanović M, Stojaković A, Abolmasov B, Đurić D, Đurić U, Krušić J, Andrejev K, Samardžić-Petrović M. Geological, morphologic and pedologic components of the teroir of Smederevka. in Knjiga apstrakata / 17. Kongres geologa Srbije, Vrnjačka Banja, 17-20. maj 2018. = Book of abstracts / 17th Serbian Geological Congress, Vrnjačka banja, Maz 17-20, 2018. Vol. 2. 2018;2:808-813.
https://hdl.handle.net/21.15107/rcub_grafar_1602 .

Marjanović, M., Stojaković, A., Abolmasov, Biljana, Đurić, D., Đurić, Uroš, Krušić, Jelka, Andrejev, Katarina, Samardžić-Petrović, Mileva, "Geological, morphologic and pedologic components of the teroir of Smederevka" in Knjiga apstrakata / 17. Kongres geologa Srbije, Vrnjačka Banja, 17-20. maj 2018. = Book of abstracts / 17th Serbian Geological Congress, Vrnjačka banja, Maz 17-20, 2018. Vol. 2, 2 (2018):808-813,
https://hdl.handle.net/21.15107/rcub_grafar_1602 .

TY  - JOUR
AU  - Krušić, Jelka
AU  - Marjanović, Miloš
AU  - Samardžić-Petrović, Mileva
AU  - Abolmasov, Biljana
AU  - Andrejev, Katarina
AU  - Miladinović, Aleksandar
PY  - 2017
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1084
T2  - Geofizika
T1  - Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia
EP  - 273
IS  - 2
SP  - 251
VL  - 34
DO  - 10.15233/gfz.2017.34.15
ER  - 

@article{
author = "Krušić, Jelka and Marjanović, Miloš and Samardžić-Petrović, Mileva and Abolmasov, Biljana and Andrejev, Katarina and Miladinović, Aleksandar",
year = "2017",
journal = "Geofizika",
title = "Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia",
pages = "273-251",
number = "2",
volume = "34",
doi = "10.15233/gfz.2017.34.15"
}

Krušić, J., Marjanović, M., Samardžić-Petrović, M., Abolmasov, B., Andrejev, K.,& Miladinović, A.. (2017). Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia. in Geofizika, 34(2), 251-273.
https://doi.org/10.15233/gfz.2017.34.15

Krušić J, Marjanović M, Samardžić-Petrović M, Abolmasov B, Andrejev K, Miladinović A. Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia. in Geofizika. 2017;34(2):251-273.
doi:10.15233/gfz.2017.34.15 .

Krušić, Jelka, Marjanović, Miloš, Samardžić-Petrović, Mileva, Abolmasov, Biljana, Andrejev, Katarina, Miladinović, Aleksandar, "Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia" in Geofizika, 34, no. 2 (2017):251-273,
https://doi.org/10.15233/gfz.2017.34.15 . .

TY  - CONF
AU  - Andrejev, Katarina
AU  - Krušić, Jelka
AU  - Đurić, Uroš
AU  - Marjanović, Miloš
AU  - Abolmasov, Biljana
PY  - 2017
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/896
AB  - This paper represents a relative landslide risk assessment of the City of Valjevo in Western Serbia. After the extreme rainfall during the May 2014, many new landslides were triggered, and Valjevo was one of the most affected areas in Serbia. The modeling was preceded by the data selection, and included ranging and preprocessing of the conditioning factors. The following eight factors were chosen as representative: stream distance, slope, lithology, elevation, distance from hydrogeological borders, land use, erodibility and aspect. Landslide susceptibility analysis was completed using the Analytical Hierarchy Process (AHP) multi-criteria method. Validation was performed by cross-referencing with an existing landslide inventory, which was made by field mapping and interpretation of satellite images. Finally, the relative risk was determined for the City of Valjevo by using a realistic population distribution model as a source for elements at risk. The results show the distribution of risk and suggest that 20% of the inhabited area falls into the high risk class, but this encompasses less than 5% of the total population.
C3  - Advancing Culture of Living With Landslides, Vol 5: Landslides in Different Environments
T1  - Relative Landslide Risk Assessment for the City of Valjevo
EP  - 533
SP  - 525
DO  - 10.1007/978-3-319-53483-1_62
ER  - 

@conference{
author = "Andrejev, Katarina and Krušić, Jelka and Đurić, Uroš and Marjanović, Miloš and Abolmasov, Biljana",
year = "2017",
abstract = "This paper represents a relative landslide risk assessment of the City of Valjevo in Western Serbia. After the extreme rainfall during the May 2014, many new landslides were triggered, and Valjevo was one of the most affected areas in Serbia. The modeling was preceded by the data selection, and included ranging and preprocessing of the conditioning factors. The following eight factors were chosen as representative: stream distance, slope, lithology, elevation, distance from hydrogeological borders, land use, erodibility and aspect. Landslide susceptibility analysis was completed using the Analytical Hierarchy Process (AHP) multi-criteria method. Validation was performed by cross-referencing with an existing landslide inventory, which was made by field mapping and interpretation of satellite images. Finally, the relative risk was determined for the City of Valjevo by using a realistic population distribution model as a source for elements at risk. The results show the distribution of risk and suggest that 20% of the inhabited area falls into the high risk class, but this encompasses less than 5% of the total population.",
journal = "Advancing Culture of Living With Landslides, Vol 5: Landslides in Different Environments",
title = "Relative Landslide Risk Assessment for the City of Valjevo",
pages = "533-525",
doi = "10.1007/978-3-319-53483-1_62"
}

Andrejev, K., Krušić, J., Đurić, U., Marjanović, M.,& Abolmasov, B.. (2017). Relative Landslide Risk Assessment for the City of Valjevo. in Advancing Culture of Living With Landslides, Vol 5: Landslides in Different Environments, 525-533.
https://doi.org/10.1007/978-3-319-53483-1_62

Andrejev K, Krušić J, Đurić U, Marjanović M, Abolmasov B. Relative Landslide Risk Assessment for the City of Valjevo. in Advancing Culture of Living With Landslides, Vol 5: Landslides in Different Environments. 2017;:525-533.
doi:10.1007/978-3-319-53483-1_62 .

Andrejev, Katarina, Krušić, Jelka, Đurić, Uroš, Marjanović, Miloš, Abolmasov, Biljana, "Relative Landslide Risk Assessment for the City of Valjevo" in Advancing Culture of Living With Landslides, Vol 5: Landslides in Different Environments (2017):525-533,
https://doi.org/10.1007/978-3-319-53483-1_62 . .

TY  - JOUR
AU  - Abolmasov, Biljana
AU  - Krušić, Jelka
AU  - Andrejev, Katarina
AU  - Marjanović, Miloš
AU  - Stanković, Ranka
AU  - Đurić, Uroš
PY  - 2017
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/830
AB  - This paper is an example of landslide susceptibility assessment in Krupanj municipality in western Serbia, using two different multicriteria methods: Analytical Hierarchy Process (AHP) and Weight of Evidence (WoE). AHP is based on quantified expert judgement on the individual importance of conditioning factors, as geological, morphological and environmental proxies for landsliding. WoE is data-driven, i.e. it uses conditional probability of landslide occurrence to grade conditioning factors by their importance. Validation was performed by cross-referencing with an existing landslide inventory, which was made by field mapping and interpretation of satellite images. Both models have relatively good performance, but WoE has slightly better validation parameters. These results are a solid background for general overview of the landslide susceptibility distribution at municipality scale, and can be successfully used for further landslide risk assessment or large scale planning.
AB  - U radu su prikazani rezultati dve metode procene podložnosti terena na kliženje: višekriterijumske AHP (Analytical Hierarchy Process) metode i metode uslovne verovatnoće, odnosno metode težine dokaza WoE (Weight of Evidence) primenjene na područje opštine Krupanj u zapadnoj Srbiji. Validacija dobijenih rezultata procene izvršena je za svaki dobijeni model poređenjem sa realnim podacima evidentiranih pojava nestabilnosti dobijenih terenskim kartiranjem i analizom satelitskih snimaka visoke rezolucije. Nakon toga izvršena je uporedna analiza dobijenih rezultata.Oba modela pokazuju zadovoljavajuću tačnost, gde je statistička metoda dala nešto preciznije rezultate. Rezultati procene podložnosti predstavljaju dobru osnovu za procenu relativnog rizika od procesa kliženja i podlogu za izradu planskih dokumenata opštine Krupanj.
PB  - Udruženje inženjera građevinarstva, geotehnike, arhitekture i urbanista "Izgradnja", Beograd
T2  - Izgradnja
T1  - Application of AHP and WoE methods for landslide susceptibility assessment on Krupanj municipality
T1  - Primena AHP i WoE metode u proceni podložnosti terena na kliženje za područje opštine Krupanj
EP  - 246
IS  - 7-10
SP  - 239
UR  - https://hdl.handle.net/21.15107/rcub_grafar_830
ER  - 

@article{
author = "Abolmasov, Biljana and Krušić, Jelka and Andrejev, Katarina and Marjanović, Miloš and Stanković, Ranka and Đurić, Uroš",
year = "2017",
abstract = "This paper is an example of landslide susceptibility assessment in Krupanj municipality in western Serbia, using two different multicriteria methods: Analytical Hierarchy Process (AHP) and Weight of Evidence (WoE). AHP is based on quantified expert judgement on the individual importance of conditioning factors, as geological, morphological and environmental proxies for landsliding. WoE is data-driven, i.e. it uses conditional probability of landslide occurrence to grade conditioning factors by their importance. Validation was performed by cross-referencing with an existing landslide inventory, which was made by field mapping and interpretation of satellite images. Both models have relatively good performance, but WoE has slightly better validation parameters. These results are a solid background for general overview of the landslide susceptibility distribution at municipality scale, and can be successfully used for further landslide risk assessment or large scale planning., U radu su prikazani rezultati dve metode procene podložnosti terena na kliženje: višekriterijumske AHP (Analytical Hierarchy Process) metode i metode uslovne verovatnoće, odnosno metode težine dokaza WoE (Weight of Evidence) primenjene na područje opštine Krupanj u zapadnoj Srbiji. Validacija dobijenih rezultata procene izvršena je za svaki dobijeni model poređenjem sa realnim podacima evidentiranih pojava nestabilnosti dobijenih terenskim kartiranjem i analizom satelitskih snimaka visoke rezolucije. Nakon toga izvršena je uporedna analiza dobijenih rezultata.Oba modela pokazuju zadovoljavajuću tačnost, gde je statistička metoda dala nešto preciznije rezultate. Rezultati procene podložnosti predstavljaju dobru osnovu za procenu relativnog rizika od procesa kliženja i podlogu za izradu planskih dokumenata opštine Krupanj.",
publisher = "Udruženje inženjera građevinarstva, geotehnike, arhitekture i urbanista "Izgradnja", Beograd",
journal = "Izgradnja",
title = "Application of AHP and WoE methods for landslide susceptibility assessment on Krupanj municipality, Primena AHP i WoE metode u proceni podložnosti terena na kliženje za područje opštine Krupanj",
pages = "246-239",
number = "7-10",
url = "https://hdl.handle.net/21.15107/rcub_grafar_830"
}

Abolmasov, B., Krušić, J., Andrejev, K., Marjanović, M., Stanković, R.,& Đurić, U.. (2017). Application of AHP and WoE methods for landslide susceptibility assessment on Krupanj municipality. in Izgradnja
Udruženje inženjera građevinarstva, geotehnike, arhitekture i urbanista "Izgradnja", Beograd.(7-10), 239-246.
https://hdl.handle.net/21.15107/rcub_grafar_830

Abolmasov B, Krušić J, Andrejev K, Marjanović M, Stanković R, Đurić U. Application of AHP and WoE methods for landslide susceptibility assessment on Krupanj municipality. in Izgradnja. 2017;(7-10):239-246.
https://hdl.handle.net/21.15107/rcub_grafar_830 .

Abolmasov, Biljana, Krušić, Jelka, Andrejev, Katarina, Marjanović, Miloš, Stanković, Ranka, Đurić, Uroš, "Application of AHP and WoE methods for landslide susceptibility assessment on Krupanj municipality" in Izgradnja, no. 7-10 (2017):239-246,
https://hdl.handle.net/21.15107/rcub_grafar_830 .

TY  - JOUR
AU  - Krušić, Jelka
AU  - Marjanović, Miloš
AU  - Samardžić-Petrović, Mileva
AU  - Abolmasov, Biljana
AU  - Andrejev, Katarina
AU  - Miladinović, Aleksandar
PY  - 2017
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1936
AB  - Landslide  Susceptibility  Assessment  is  becoming  a  very  productive  re-search area, wherein different modeling approaches are practiced to delineate zones of the high-low likelihood of landslide occurrence. However, there is no strong consensus on which approach is the most adequate. The reason behind the lack of the general view on the performance of different approaches could be partially explained by the particularity of each study. To evaluate the effi-ciency of different approaches they need to be applied under the same conditions for the same study area. Herein, we examined three different approaches, in-cluding expert, deterministic and Machine Learning, on the example of Ljubo-vija Municipality in western Serbia. The study area has been known as suscep-tible to landslides, and represents good ground for assessing the chosen methods. It  is  represented  by  complex  geology,  prone  to  landslides  that  are  commonly  hosted in thick weathering crust of Paleozoic formations, composed of schists and meta-sediments. Under extreme triggering conditions, such as the one that unfolded in May 2014, these thick weathering crusts saturate, and give way to a variety of landslide and flash-flood processes that we will be focusing on in this study. The application of the expert-approach, through Analytical Hierarchy Process  provided  a  rough  assessment  map.  The  deterministic  model,  which  couples simple infinite slope and hydrological model, provided us with lower quality results, when compared to the expert-based one. This could be explained by the assumptions used in the model are too simplistic to generically model a wide range of landslide typology. Finally, Machine Learning approach, using the Random Forest algorithm, provided significantly better results and showed that  it  can  cope  with  versatile  landslide  typology  over  larger  scales.  Its  AUC  performance is about 0.75 which is considerably outperforming the AUC values of the other two models, which were up to 0.55, i.e. at the level of random guess
T2  - Geofizika
T1  - Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia
VL  - 34
DO  - 10.15233/gfz.2017.34.15
DO  - 10.15233/gfz.2017.34.15
ER  - 

@article{
author = "Krušić, Jelka and Marjanović, Miloš and Samardžić-Petrović, Mileva and Abolmasov, Biljana and Andrejev, Katarina and Miladinović, Aleksandar",
year = "2017",
abstract = "Landslide  Susceptibility  Assessment  is  becoming  a  very  productive  re-search area, wherein different modeling approaches are practiced to delineate zones of the high-low likelihood of landslide occurrence. However, there is no strong consensus on which approach is the most adequate. The reason behind the lack of the general view on the performance of different approaches could be partially explained by the particularity of each study. To evaluate the effi-ciency of different approaches they need to be applied under the same conditions for the same study area. Herein, we examined three different approaches, in-cluding expert, deterministic and Machine Learning, on the example of Ljubo-vija Municipality in western Serbia. The study area has been known as suscep-tible to landslides, and represents good ground for assessing the chosen methods. It  is  represented  by  complex  geology,  prone  to  landslides  that  are  commonly  hosted in thick weathering crust of Paleozoic formations, composed of schists and meta-sediments. Under extreme triggering conditions, such as the one that unfolded in May 2014, these thick weathering crusts saturate, and give way to a variety of landslide and flash-flood processes that we will be focusing on in this study. The application of the expert-approach, through Analytical Hierarchy Process  provided  a  rough  assessment  map.  The  deterministic  model,  which  couples simple infinite slope and hydrological model, provided us with lower quality results, when compared to the expert-based one. This could be explained by the assumptions used in the model are too simplistic to generically model a wide range of landslide typology. Finally, Machine Learning approach, using the Random Forest algorithm, provided significantly better results and showed that  it  can  cope  with  versatile  landslide  typology  over  larger  scales.  Its  AUC  performance is about 0.75 which is considerably outperforming the AUC values of the other two models, which were up to 0.55, i.e. at the level of random guess",
journal = "Geofizika",
title = "Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia",
volume = "34",
doi = "10.15233/gfz.2017.34.15, 10.15233/gfz.2017.34.15"
}

Krušić, J., Marjanović, M., Samardžić-Petrović, M., Abolmasov, B., Andrejev, K.,& Miladinović, A.. (2017). Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia. in Geofizika, 34.
https://doi.org/10.15233/gfz.2017.34.15

Krušić J, Marjanović M, Samardžić-Petrović M, Abolmasov B, Andrejev K, Miladinović A. Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia. in Geofizika. 2017;34.
doi:10.15233/gfz.2017.34.15 .

Krušić, Jelka, Marjanović, Miloš, Samardžić-Petrović, Mileva, Abolmasov, Biljana, Andrejev, Katarina, Miladinović, Aleksandar, "Comparison of expert, deterministic and Machine Learning approach for landslide susceptibility assessment in Ljubovija Municipality, Serbia" in Geofizika, 34 (2017),
https://doi.org/10.15233/gfz.2017.34.15 . .

TY  - CONF
AU  - Abolmasov, Biljana
AU  - Marjanović, Miloš
AU  - Đurić, Uroš
AU  - Krušić, Jelka
AU  - Andrejev, Katarina
PY  - 2017
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/817
AB  - The IPL project No 210, titled "Massive landsliding in Serbia following Cyclone Tamara in May 2014", started in March 2016. The study area is located in the Western and Central part of the Republic of Serbia territory affected by Cyclone Tamara in May 2014. The project aims to summarize and analyse all collected relevant data, including historic and current rainfall, landslide records, aftermath reports, and environmental features datasets from the May 2014 sequence. Objectives of the proposed project include: collecting all available and acquired landslide data, analysing the trigger/landslide relation in a feasible time span and in the May 2014 event, relating the landslide mechanisms and magnitudes versus the trigger, identifying spatial patterns and relationships between landslides and geological and environmental controls, proposing an overview susceptibility map of the event and numerical modelling of the site-specific location and landslide mechanisms. The Project will be organized by University of Belgrade, Faculty of Mining and Geology and Faculty of Civil Engineering. Project beneficiaries are local community and local and regional authorities. In this paper we will present preliminary results of the proposed project targets performed by project participants.
C3  - Advancing Culture of Living With Landslides, Vol 1: Isdr-Icl Sendai Partnerships 2015-2025
T1  - Massive Landsliding in Serbia Following Cyclone Tamara in May 2014 (IPL-210)
EP  - 484
SP  - 473
DO  - 10.1007/978-3-319-59469-9_41
ER  - 

@conference{
author = "Abolmasov, Biljana and Marjanović, Miloš and Đurić, Uroš and Krušić, Jelka and Andrejev, Katarina",
year = "2017",
abstract = "The IPL project No 210, titled "Massive landsliding in Serbia following Cyclone Tamara in May 2014", started in March 2016. The study area is located in the Western and Central part of the Republic of Serbia territory affected by Cyclone Tamara in May 2014. The project aims to summarize and analyse all collected relevant data, including historic and current rainfall, landslide records, aftermath reports, and environmental features datasets from the May 2014 sequence. Objectives of the proposed project include: collecting all available and acquired landslide data, analysing the trigger/landslide relation in a feasible time span and in the May 2014 event, relating the landslide mechanisms and magnitudes versus the trigger, identifying spatial patterns and relationships between landslides and geological and environmental controls, proposing an overview susceptibility map of the event and numerical modelling of the site-specific location and landslide mechanisms. The Project will be organized by University of Belgrade, Faculty of Mining and Geology and Faculty of Civil Engineering. Project beneficiaries are local community and local and regional authorities. In this paper we will present preliminary results of the proposed project targets performed by project participants.",
journal = "Advancing Culture of Living With Landslides, Vol 1: Isdr-Icl Sendai Partnerships 2015-2025",
title = "Massive Landsliding in Serbia Following Cyclone Tamara in May 2014 (IPL-210)",
pages = "484-473",
doi = "10.1007/978-3-319-59469-9_41"
}

Abolmasov, B., Marjanović, M., Đurić, U., Krušić, J.,& Andrejev, K.. (2017). Massive Landsliding in Serbia Following Cyclone Tamara in May 2014 (IPL-210). in Advancing Culture of Living With Landslides, Vol 1: Isdr-Icl Sendai Partnerships 2015-2025, 473-484.
https://doi.org/10.1007/978-3-319-59469-9_41

Abolmasov B, Marjanović M, Đurić U, Krušić J, Andrejev K. Massive Landsliding in Serbia Following Cyclone Tamara in May 2014 (IPL-210). in Advancing Culture of Living With Landslides, Vol 1: Isdr-Icl Sendai Partnerships 2015-2025. 2017;:473-484.
doi:10.1007/978-3-319-59469-9_41 .

Abolmasov, Biljana, Marjanović, Miloš, Đurić, Uroš, Krušić, Jelka, Andrejev, Katarina, "Massive Landsliding in Serbia Following Cyclone Tamara in May 2014 (IPL-210)" in Advancing Culture of Living With Landslides, Vol 1: Isdr-Icl Sendai Partnerships 2015-2025 (2017):473-484,
https://doi.org/10.1007/978-3-319-59469-9_41 . .

TY  - JOUR
AU  - Abolmasov, Biljana
AU  - Marjanović, Miloš
AU  - Đurić, Uroš
AU  - Stanković, Ranka
AU  - Krušić, Jelka
AU  - Andrejev, Katarina
AU  - Vulović, Nikola
AU  - Petrović, Rastko
PY  - 2015
UR  - https://grafar.grf.bg.ac.rs/handle/123456789/1889
PB  - Програм Уједињених нација за развој (UNDP) Србија
T1  - Брошура "BEWARE" пројекта - Информатор о пројекту и приручник за практичан рад
EP  - 56
UR  - https://hdl.handle.net/21.15107/rcub_grafar_1889
ER  - 

@article{
author = "Abolmasov, Biljana and Marjanović, Miloš and Đurić, Uroš and Stanković, Ranka and Krušić, Jelka and Andrejev, Katarina and Vulović, Nikola and Petrović, Rastko",
year = "2015",
publisher = "Програм Уједињених нација за развој (UNDP) Србија",
title = "Брошура "BEWARE" пројекта - Информатор о пројекту и приручник за практичан рад",
pages = "56",
url = "https://hdl.handle.net/21.15107/rcub_grafar_1889"
}

Abolmasov, B., Marjanović, M., Đurić, U., Stanković, R., Krušić, J., Andrejev, K., Vulović, N.,& Petrović, R.. (2015). Брошура "BEWARE" пројекта - Информатор о пројекту и приручник за практичан рад. 
Програм Уједињених нација за развој (UNDP) Србија..
https://hdl.handle.net/21.15107/rcub_grafar_1889

Abolmasov B, Marjanović M, Đurić U, Stanković R, Krušić J, Andrejev K, Vulović N, Petrović R. Брошура "BEWARE" пројекта - Информатор о пројекту и приручник за практичан рад. 2015;:null-56.
https://hdl.handle.net/21.15107/rcub_grafar_1889 .

Abolmasov, Biljana, Marjanović, Miloš, Đurić, Uroš, Stanković, Ranka, Krušić, Jelka, Andrejev, Katarina, Vulović, Nikola, Petrović, Rastko, "Брошура "BEWARE" пројекта - Информатор о пројекту и приручник за практичан рад" (2015),
https://hdl.handle.net/21.15107/rcub_grafar_1889 .