WILDFIRE VULNERABILITY ASSESSMENT AND MAPPING USING REMOTE SENSING, GIS AND WEIGHTED OVERLAY METHOD IN THE EASTERN AURES IN KHENCHELA, ALGERIA

被引:0
作者
Djabri, Ahmed Djaber [1 ]
Bouhata, Rabah [2 ]
Guellouh, Sami [2 ]
Bensekhria, Aida [2 ]
机构
[1] Univ Constantine 1, Fac Earth Sci, Geog & Spatial Planning Lab LASTERNE, RN79, Constantine, Algeria
[2] Univ Batna 2, Dept Geog & Spatial Planning, Batna 05078, Algeria
关键词
weighted overlay method; eastern Aures; forest fire; Khenchela; vul nerability; FOREST-FIRE RISK; ANALYTIC HIERARCHY PROCESS; MULTICRITERIA ANALYSIS; STATISTICAL-ANALYSIS; INFORMATION-SYSTEM; FREQUENCY RATIO; MODELS; IRAN; NORTHEAST; SEVERITY;
D O I
10.15291/geoadria.4218
中图分类号
P9 [自然地理学]; K9 [地理];
学科分类号
0705 ; 070501 ;
摘要
Wildfires are one of the natural disasters that cause harmful environmental and economic losses and pose a threat to ecosystems around the world. Consequently, measures must be carefully developed to predict their occurrence and mitigate their damage. This study aims to map the vulnerability to forest fires in the eastern Aures region of Algeria, which is exposed to frequent fires, by using Geographic Information Systems (GIS) and Remote Sensing (RS). In this respect, a geodatabase has been created, with 12 criteria influencing identifying areas of vulnerability to forest fires and grouping them into four main categories (forest characteristics, human factors, relief, and climate). In this context, the Weighted Overlay (WOA) technique was used, as this technique relies on calculating the numerical weights for each factor through the Analytical Hierarchy Process (AHP), and then the Forest Fire Vulnerability Index (FFVI) was derived. Through overlaying criterion, raster layers for each criterion and the results are represented in a vulnerability map. The vulnerability map shows very high, high, medium, low, and very low classes. High and very high vulnerabilities occupy 31.54% of the total studied surface. Moreover, the burned areas in the study area for 2021 were determined using Senti-nel-2 satellite images and calculating the Natural Burning Ratio (NBR) to assess the FFVI. We performed a spatial overlay between the NBR and the FFVI to validate the results. This overlay was translated into the ROC curve (receiver operating characteristic curve) using GIS software. The precision coefficient (AUC) was determined to be 0.778, indicating that the weighted overlay technique is effective. Therefore, it indicates that the WOA technique is effective and will help decision-makers improve emergency management and forest protection to minimize damage.
引用
收藏
页码:191 / 210
页数:20
相关论文
共 98 条
  • [1] Spatial-statistical analysis of factors determining forest fires: a case study from Golestan, Northeast Iran
    Abdi, Omid
    Kamkar, Behnam
    Shirvani, Zeinab
    Teixeira da Silva, Jaime A.
    Buchroithner, Manfred F.
    [J]. GEOMATICS NATURAL HAZARDS & RISK, 2018, 9 (01) : 267 - 280
  • [2] GIS-Based Frequency Ratio and Analytic Hierarchy Process for Forest Fire Susceptibility Mapping in the Western Region of Syria
    Abdo, Hazem Ghassan
    Almohamad, Hussein
    Al Dughairi, Ahmed Abdullah
    Al-Mutiry, Motirh
    [J]. SUSTAINABILITY, 2022, 14 (08)
  • [3] Landfire hazard assessment in the Caspian Hyrcanian forest ecoregion with the long-term MODIS active fire data
    Adab, Hamed
    [J]. NATURAL HAZARDS, 2017, 87 (03) : 1807 - 1825
  • [4] Modeling forest fire risk in the northeast of Iran using remote sensing and GIS techniques
    Adab, Hamed
    Kanniah, Kasturi Devi
    Solaimani, Karim
    [J]. NATURAL HAZARDS, 2013, 65 (03) : 1723 - 1743
  • [5] Ajin R., 2016, Journal of Earth, Environment and Health Sciences, V2, P109, DOI [10.4103/2423-7752.199288, DOI 10.4103/2423-7752.199288]
  • [6] Ajin R. S., International Journal of Advanced Earth Science and Engineering, V5, P308
  • [7] Akay A. E., 2019, European Journal of Forest Engineering, V5, P25, DOI [10.33904/ejfe.579075, DOI 10.33904/EJFE.579075]
  • [8] Wildland Fire Susceptibility Mapping Using Support Vector Regression and Adaptive Neuro-Fuzzy Inference System-Based Whale Optimization Algorithm and Simulated Annealing
    Al-Fugara, A'kif
    Mabdeh, Ali Nouh
    Ahmadlou, Mohammad
    Pourghasemi, Hamid Reza
    Al-Adamat, Rida
    Pradhan, Biswajeet
    Al-Shabeeb, Abdel Rahman
    [J]. ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2021, 10 (06)
  • [9] Albini F. A., 1976, General Technical Report, USDA Forest Service, Intermountain Forest and Range Experiment Station, p92pp
  • [10] Normalized Burn Ratio Plus (NBR plus ): A New Index for Sentinel-2 Imagery
    Alcaras, Emanuele
    Costantino, Domenica
    Guastaferro, Francesca
    Parente, Claudio
    Pepe, Massimiliano
    [J]. REMOTE SENSING, 2022, 14 (07)