Open AccessTesting NDVI, tree cover density and land cover type as fuel indicators in the wildfire spread capacity index (WSCI): case of Montenegro
Author(s) -
Artan Hysa,
Velibor Spalević
Publication year - 2020
Publication title -
notulae botanicae horti agrobotanici cluj-napoca
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.332
H-Index - 32
eISSN - 1842-4309
pISSN - 0255-965X
DOI - 10.15835/nbha48411993
Subject(s) - normalized difference vegetation index , land cover , computer science , search engine indexing , context (archaeology) , analytic hierarchy process , montenegro , multispectral image , index (typography) , remote sensing , geography , environmental science , data mining , environmental resource management , land use , operations research , mathematics , civil engineering , engineering , leaf area index , artificial intelligence , ecology , archaeology , regional science , world wide web , biology
This paper presents an updated version of our previous GIS-based method developed for indexing the forest surfaces by their wildfire ignition probability (WIPI) and wildfire spreading capacity (WSCI). The previous study relied on a multi-criteria approach including a variety of factors of social, hydro-meteorological, and geo-physical character of the context. However, this study is challenging the drawbacks of the previous work, by introducing three new criteria regarding the vegetation properties in the area. Normalized Difference Vegetation Index (NDVI), Tree Cover Density (TCD), and land cover type are launched as indicators of fuel properties of the forest being indexed. The materials and software utilized here belongs to different open sources. CORINE Land Cover (CLC), Open Street Map (OSM), TCD via Copernicus high resolution data, and multispectral satellite images via Landsat 8 (Semi-Automatic Classification Plugin- SCP) are utilized as raw materials in a workflow in QGIS software. At this stage, the study area is the territory of Montenegro. Following the inventory stage, the indexing method relies on a normalizing procedure in QGIS and the assignment of weighted impact factor to each criterion via analytical hierarchy process (AHP). The WSCI value is derived as the sum of the products between the normalized class and the respective weighted impact factor of each criterion. Besides the methodological improvements the results of this work deliver tangible outputs in support of forest fire risk reduction in disaster risk management and fire safety agendas.