scholarly journals Mapping the Wildland-Urban Interfaces for Forest Fire Prevention in the Province of Mila (Algeria)

2020 ◽  
Vol 76 (2) ◽  
pp. 76-90
Author(s):  
Ahmed Laala ◽  
Amina Beldjazia ◽  
Djamel Alatou
Keyword(s):  
Spatial Analysis ◽  
Forest Fire ◽  
Urban Areas ◽  
Fire Risk ◽  
Fire Prevention ◽  
Environment Protection ◽  
Wildland Urban Interface ◽  
Housing Structure ◽  
Different Types ◽  
Forest Fire Prevention

Areas where the habitat is in contact with the forest represent danger and become a real concern for managers who need location tools to act and limit fire risks in these territories. In this context, our study focuses on determining and mapping the different types of wildland-urban interface (WUI) existing in the Zouagha forest. The methodology integrates four types of a housing structure, limited to a radius of 100 meters around each house and three classes of vegetation aggregation. The GIS tool maps and identifies twelve types of WUI in the study area. Our results show that WUI areas in the Zouagha forest increased rapidly over the last decade. New houses were the main cause for new WUI. In 2019, the number of buildings in the study area was 51% higher than in 2009. These urban areas are more exposed to wildfire risks due to their proximity to flammable fuels. The spatial analysis allows highlighting the WUI type most sensitive to a fire risk that needs the interventions of environment protection institutions to limit the damage of wildfires.

Waldbrandprävention im Kanton Graubünden | Forest fire prevention in Canton Grisons

2010 ◽  
Vol 161 (11) ◽  
pp. 460-464
Author(s):  
Andrea Kaltenbrunner
Keyword(s):  
Water Supply ◽  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Fire Fighting ◽  
Fire Prevention ◽  
Insurance Company ◽  
Forest Fire Prevention ◽  
Precautionary Measures ◽  
Regional Forest

Thanks to fast alarm systems and modern fire-fighting equipment most forest fires can be extinguished while still very small. Nevertheless, the fire brigade and forest organisations in the Grisons are recurringly confronted with larger fires. Over the past twenty years the Grisons Forestry Service and the fire section of the cantonal Building Insurance Company have invested in fire prevention and improved fire-fighting techniques. To monitor and assess the risk of forest fires, the computer-aided forest fire forecasting system “Incendi” was developed. On its basis, regional forest fire risk maps are drawn up and bans on the lighting of fires are imposed. For use in case of fire, the Forestry Service has drawn up maps of the whole Canton Grisons showing water supply points in and near the forest. Where there are gaps in the water supply, artificial water sources are being created. Fifteen years ago a concept of forest fire-fighting bases was elaborated. The most important elements of this concept are the 18 regional depots of mobile fire-fighting material, which in case of emergency can be transported where needed. The present-day administrative structures and the precautionary measures taken in the Grisons fulfil the conditions for efficient forest fire prevention and control.

scholarly journals Remote Sensing and GIS Application to Establish a Forest Fire Risk Map for Planning of Forest Fire Prevention and Mitigation in Son La Province, Vietnam

2017 ◽  
Vol 33 (3) ◽  
Author(s):  
Pham Xuan Canh
Keyword(s):  
Forest Fire ◽  
Forest Fires ◽  
Fire Risk ◽  
Fire Prevention ◽  
Risk Map ◽  
Natural Reserve ◽  
Landsat 7 ◽  
Forest Fire Prevention ◽  
Reserve Forest ◽  
Forest Fire Risk

Son La is a mountainous province in the Northwest of Vietnam with many ethnic groups, and has an area of ​​14,125 km², accounting for 4.27% of the total area of ​​Vietnam. The ​​forest land accounts for 73% of the total natural area of ​​the province with 357,000 ha of forest. Among this having 4 areas of special use and the natural reserve forest. Every year, hundreds of forest fires cause huge natural, economic and ecological damages to the province. Due to the climate change, forest fires tend to increase in recent years. In order to prevent the fires, warning maps of the forest fire risk are needed. The research has analyzed mechanism and causes of the forest fires, and built a forest fire-related database with multi-layers of natural, social and economic information, in these, some layers were extracted from the Landsat 7 images. The expert method was applied for assessement and Saaty's Hierarchical Analysis (AHP) methods were applied to determine the weight for separated parameters related to forest fires. The research applied the MCA method to build a multi-indicator function with 9 parameters for establishing the forest fire risk map at the scale of 1:100,000 for provincial levels. In verifying the results by regression correlation analysis, the R2 value reached 0.71.These maps have been used for the purpose of forest fire prevention planning for Son La province.

La protezione dagli incendi boschivi nelle Alpi centro-occidentali | Forest Fire-Prevention in the Central Eastern Alps

2000 ◽  
Vol 151 (9) ◽  
pp. 325-335 ◽  
Author(s):  
Giovanni Bovio
Keyword(s):  
Forest Fire ◽  
Eastern Alps ◽  
Fire Prevention ◽  
Forest Fire Prevention ◽  
Central Eastern

Important forest fire prevention developments of the Lombardy, Piedmont and Aosta Valley regions are highlighted in this study and a certain number of activities considered able to improve the situation are proposed.

scholarly journals Forest Fire Prevention Using WSN Assisted IOT

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1317 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav Ji Nigam
Keyword(s):  
Internet Of Things ◽  
Sensor Network ◽  
Forest Fire ◽  
Clustering Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Fire Prevention ◽  
New Era ◽  
Data Flows ◽  
Forest Fire Prevention

Internet of Things is the mainstay of the new era since its application becomes the future of day-to-day life. This work targets the IoT network assisted by WSN to prevent forest fire. We propose two-layer architecture of sensor network assisted by IoT enabled UAVs. The data flows in the proposed architecture in bottom-up fashion i.e., data is sensed by the nodes, which are deployed in the forest area (and sense temperature continuously). This data is transmitted to upper layer consisting of UAVs, which take appropriate action (to sprinkle water to bring temperature down to prevent fire). All the UAVs are interconnected to each other as well as to base station. The sensor nodes are clustered using two-step clustering algorithm, which takes care of the isolated nodes. The scheme has been equated to another WSN assisted IoT clustering technique. The proposed scheme outperforms the existing in terms of congestion at the UAV stations, number of alive nodes and remaining energy of the network.  

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