Identifying the relationship between forest roads and wildfires in forest ecosystems is a crucial priority to integrate suppression and prevention within wildfire management. In various investigations, the interaction of these elements has been studied by using road density as one of the anthropogenic dependent variables. This study focused on the use of a broader set of metrics associated with forest road networks, such as road density, the number of links (edges), and access percentage based on two effect zones (road buffers of 75 m and 97 m). These metrics were employed as response variables to assess forest road network suitability in relation to wildfires, specifically the number and size of fires (2000–2021), using the Apulia region (Italy) as a case study. In addition, to enhance the comprehensive understanding of road networks in forest ecosystems in relation to wildfires, this study considered various affecting factors, including land-cover data (forest, maquis, natural grassland), geomorphology (slope, aspect), vegetation (Normalized Difference Vegetation Index (NDVI)), and morphometric indexes (Topographic Position Index (TPI), Terrain Ruggedness Index (TRI), Topographic Wetness Index (TWI)). We used geographically weighted regression (GWR) and ordinary least squares (OLS) to analyze the interaction between forest road metrics and dependent variables. Results showed that the GWR models outperformed the OLS models in term of statistical results such as R2 and the Akaike Information Criterion (AICc). We found that among road metrics, road density and number of links do not effectively demonstrate the correlation between roads and wildfires as a singular criterion. However, they prove to be a beneficial supplementary variable when considered alongside access percentage, particularly within the 75-m buffer zone. Our findings are used to discuss implications for forest road network planning in a broader wildfire management analysis. Our findings demonstrate that forest roads are not one-dimensional and static infrastructure; rather, they are a multi-dimensional and dynamic structure. Hence, they need to be analyzed from various perspectives, including accessibility and ecological approaches, in order to obtain an integrated understating of their interaction with wildfire.
Assessing Forest Road Network Suitability in Relation to the Spatial Occurrence of Wildfires in Mediterranean Forest Ecosystems
Mostafa, MohsenInvestigation
;Elia, Mario
Writing – Original Draft Preparation
;Giannico, VincenzoWriting – Review & Editing
;Lafortezza, RaffaeleWriting – Review & Editing
;Sanesi, GiovanniSupervision
2024-01-01
Abstract
Identifying the relationship between forest roads and wildfires in forest ecosystems is a crucial priority to integrate suppression and prevention within wildfire management. In various investigations, the interaction of these elements has been studied by using road density as one of the anthropogenic dependent variables. This study focused on the use of a broader set of metrics associated with forest road networks, such as road density, the number of links (edges), and access percentage based on two effect zones (road buffers of 75 m and 97 m). These metrics were employed as response variables to assess forest road network suitability in relation to wildfires, specifically the number and size of fires (2000–2021), using the Apulia region (Italy) as a case study. In addition, to enhance the comprehensive understanding of road networks in forest ecosystems in relation to wildfires, this study considered various affecting factors, including land-cover data (forest, maquis, natural grassland), geomorphology (slope, aspect), vegetation (Normalized Difference Vegetation Index (NDVI)), and morphometric indexes (Topographic Position Index (TPI), Terrain Ruggedness Index (TRI), Topographic Wetness Index (TWI)). We used geographically weighted regression (GWR) and ordinary least squares (OLS) to analyze the interaction between forest road metrics and dependent variables. Results showed that the GWR models outperformed the OLS models in term of statistical results such as R2 and the Akaike Information Criterion (AICc). We found that among road metrics, road density and number of links do not effectively demonstrate the correlation between roads and wildfires as a singular criterion. However, they prove to be a beneficial supplementary variable when considered alongside access percentage, particularly within the 75-m buffer zone. Our findings are used to discuss implications for forest road network planning in a broader wildfire management analysis. Our findings demonstrate that forest roads are not one-dimensional and static infrastructure; rather, they are a multi-dimensional and dynamic structure. Hence, they need to be analyzed from various perspectives, including accessibility and ecological approaches, in order to obtain an integrated understating of their interaction with wildfire.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.