TY  - JOUR
AU  - Novkovic, Ivan
AU  - Markovic, Goran B.
AU  - Lukic, Djordje B.
AU  - Dragicevic, Slavoljub S.
AU  - Milosevic, Marko
AU  - Djurdjic, Snezana
AU  - Samardzic, Ivan
AU  - Lezaic, Tijana
AU  - Tadic, Marija
PY  - 2021
UR  - https://gery.gef.bg.ac.rs/handle/123456789/1110
AB  - The territory of the Republic of Serbia is vulnerable to various natural disasters, among which forest fires stand out. In relation with climate changes, the number of forest fires in Serbia has been increasing from year to year. Protected natural areas are especially endangered by wildfires. For Nature Park Golija, as the second largest in Serbia, with an area of 75,183 ha, and with MaB Reserve Golija-Studenica on part of its territory (53,804 ha), more attention should be paid in terms of forest fire mitigation. GIS and multi-criteria decision analysis are indispensable when it comes to spatial analysis for the purpose of natural disaster risk management. Index-based and fuzzy AHP methods were used, together with TOPSIS method for forest fire susceptibility zonation. Very high and high forest fire susceptibility zone were recorded on 26.85% (Forest Fire Susceptibility Index) and 25.75% (fuzzy AHP). The additional support for forest fire prevention is realized through an additional Internet of Thing (IoT)-based sensor network that enables the continuous collection of local meteorological and environmental data, which enables low-cost and reliable real-time fire risk assessment and detection and the improved long-term and short-term forest fire susceptibility assessment. Obtained results can be applied for adequate forest fire risk management, improvement of the monitoring, and early warning systems in the Republic of Serbia, but are also important for relevant authorities at national, regional, and local level, which will be able to coordinate and intervene in a case of emergency events.
PB  - MDPI
T2  - Sensors
T1  - GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia
VL  - 21
IS  - 19
SP  - 6520
DO  - 10.3390/s21196520
UR  - https://hdl.handle.net/21.15107/rcub_gery_1110
ER  - 

@article{
author = "Novkovic, Ivan and Markovic, Goran B. and Lukic, Djordje B. and Dragicevic, Slavoljub S. and Milosevic, Marko and Djurdjic, Snezana and Samardzic, Ivan and Lezaic, Tijana and Tadic, Marija",
year = "2021",
abstract = "The territory of the Republic of Serbia is vulnerable to various natural disasters, among which forest fires stand out. In relation with climate changes, the number of forest fires in Serbia has been increasing from year to year. Protected natural areas are especially endangered by wildfires. For Nature Park Golija, as the second largest in Serbia, with an area of 75,183 ha, and with MaB Reserve Golija-Studenica on part of its territory (53,804 ha), more attention should be paid in terms of forest fire mitigation. GIS and multi-criteria decision analysis are indispensable when it comes to spatial analysis for the purpose of natural disaster risk management. Index-based and fuzzy AHP methods were used, together with TOPSIS method for forest fire susceptibility zonation. Very high and high forest fire susceptibility zone were recorded on 26.85% (Forest Fire Susceptibility Index) and 25.75% (fuzzy AHP). The additional support for forest fire prevention is realized through an additional Internet of Thing (IoT)-based sensor network that enables the continuous collection of local meteorological and environmental data, which enables low-cost and reliable real-time fire risk assessment and detection and the improved long-term and short-term forest fire susceptibility assessment. Obtained results can be applied for adequate forest fire risk management, improvement of the monitoring, and early warning systems in the Republic of Serbia, but are also important for relevant authorities at national, regional, and local level, which will be able to coordinate and intervene in a case of emergency events.",
publisher = "MDPI",
journal = "Sensors",
title = "GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia",
volume = "21",
number = "19",
pages = "6520",
doi = "10.3390/s21196520",
url = "https://hdl.handle.net/21.15107/rcub_gery_1110"
}

Novkovic, I., Markovic, G. B., Lukic, D. B., Dragicevic, S. S., Milosevic, M., Djurdjic, S., Samardzic, I., Lezaic, T.,& Tadic, M.. (2021). GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia. in Sensors
MDPI., 21(19), 6520.
https://doi.org/10.3390/s21196520
https://hdl.handle.net/21.15107/rcub_gery_1110

Novkovic I, Markovic GB, Lukic DB, Dragicevic SS, Milosevic M, Djurdjic S, Samardzic I, Lezaic T, Tadic M. GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia. in Sensors. 2021;21(19):6520.
doi:10.3390/s21196520
https://hdl.handle.net/21.15107/rcub_gery_1110 .

Novkovic, Ivan, Markovic, Goran B., Lukic, Djordje B., Dragicevic, Slavoljub S., Milosevic, Marko, Djurdjic, Snezana, Samardzic, Ivan, Lezaic, Tijana, Tadic, Marija, "GIS-Based Forest Fire Susceptibility Zonation with IoT Sensor Network Support, Case Study—Nature Park Golija, Serbia" in Sensors, 21, no. 19 (2021):6520,
https://doi.org/10.3390/s21196520 .,
https://hdl.handle.net/21.15107/rcub_gery_1110 .