Montenegro has different influences on the weather and climate; in general, according to Köppen’s classification, there are two climate zones: warm temperate (C) and cold temperate (D). The aim of this study is to determine the susceptibility to wildfires in the Montenegrin coastal municipality of Budva and the northern municipality of Rožaje, which are located in different climatic conditions, using multicriteria GIS decision analysis (GIS-MCDA). Nine natural and anthropogenic criteria were used for the analysis. Open geospatial data were used as input data for all criteria. The assignment of weighting coefficients for the criteria in relation to wildfire susceptibility importance was based on the Analytic Hierarchy Process (AHP) and Fuzzy Analytic Hierarchy Process (F-AHP) procedures. The results for the AHP and F-AHP models were obtained using the Weighted Linear Combination (WLC) method. According to the AHP model, the very high and high category covers 80.93% of the total area in Budva and 80.65% in Rožaje. According to the F-AHP model, the very high and high category occupies 80.71% of the total area in Budva and 82.30% in Rožaje. The validation shows that the models of GIS-MCDA perform fair in both climatic zones. The proposed models, especially in the absence of geospatial data, can be a strategic and operational advantage in the development of plans and strategies for protection against wildfires.

Wildfire is one of the most dangerous environmental stressors in most vegetation zones worldwide. Determining and monitoring this stressor is important because of the disturbances that occur during the burning of biomass in ecosystems, as well as because of the damage or suffering of organisms. In the last decade, a greater number of wildfires and burnt areas were recorded in Southern Europe and Montenegro. Therefore, it is important to develop optimal methodology and models to help in better management of forest protection against wildfire. The spatial component in firefighting plays a significant role in management. In this context, Remote Sensing and Geographic Information Systems (GIS) come to the fore, which analyze spatial data and turn it into useful information - models applied in practice. The study aims to geospatial assess condition of vegetation pre-wildfire and post-wildfire in study area of the Luštica peninsula in Montenegro during the summer of 2017. Open and publicly available Sentinel 2 satellite was used. The scaled index differenced Normalized Burn Ratio (dNBR) of burned vegetation was applied as an indicator for assessing the state of vegetation after a wildfire in the open source software Quantum GIS (QGIS). The results of the damage assessment of the burned area based on the applied scaled index reveal that the category of low severity occupies an area of 335.86 ha (7%), moderately-low severity 250.13 ha (5%), moderately-high severity 406.22 ha (8%), high severity 238.03 ha (5%). The unburned areas occupy an area of 3624.95 ha (75%). This study contributes to assessing vegetation conditions and other accompanying activities pre-wildfire and post-wildfire using modern open-source geospatial tools.