GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques

被引:0
|
作者
Anuj Tiwari
Mohammad Shoab
Abhilasha Dixit
机构
[1] Indian Institute of Technology,Department of Civil Engineering
[2] Shaqra University,Department of Computer Science, College of Science and Humanities
[3] Indian Institute of Technology,Centre of Excellence in Disaster Mitigation and Management
来源
Natural Hazards | 2021年 / 105卷
关键词
Forest fire susceptibility map (FFSM); Multi-criteria decision analysis (MCDA); Frequency ratio (FR); Analytical hierarchical process (AHP); Fuzzy analytical hierarchical process (FAHP);
D O I
暂无
中图分类号
学科分类号
摘要
This study performs a comparative evaluation of Frequency Ratio (FR), Analytic Hierarchy Process (AHP), and Fuzzy AHP (FAHP) modeling techniques for forest fire susceptibility mapping in Pauri Garhwal, Uttarakhand, India. Locations of past forest fire events reported from November 2002 to July 2019 were collected from the Uttarakhand Forest Department and Forest Survey of India and combined with the ground observations obtained from the manual survey. Then, the locations were categorized into two groups of 70% (10,500 locations) and 30% (4500 locations), randomly, for training and validation purposes, respectively. Forest fire susceptibility mapping was performed on the basis of fourteen different topographic, biological, human-induced and climatic criteria such as Digital Elevation Model, Slope, Aspect, Curvature, Normalized Difference Vegetation Index, Normalized Difference Moisture Index, Topographic Wetness Index, Soil, Distance to Settlement, Distance to Road, Distance to Drainage, Rainfall, Temperature, and Wind Speed. The Receiver Operating Characteristic curve and the Area Under the Curve (AUC) were implemented for validation of the three achieved Forest Fire Susceptibility Maps. The AUC plot evaluation revealed that FAHP has a maximum prediction accuracy of 83.47%, followed by AHP (81.75%) and FR (77.21%). Thus, the map produced by FAHP exhibits the most satisfactory properties. Results and findings of this study will help in developing more efficient fire management strategies in both the open and the protected forest areas (Rajaji and Jim Corbett National Park) of the district.
引用
收藏
页码:1189 / 1230
页数:41
相关论文
共 46 条
  • [1] GIS-based forest fire susceptibility modeling in Pauri Garhwal, India: a comparative assessment of frequency ratio, analytic hierarchy process and fuzzy modeling techniques
    Tiwari, Anuj
    Shoab, Mohammad
    Dixit, Abhilasha
    NATURAL HAZARDS, 2021, 105 (02) : 1189 - 1230
  • [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
    SUSTAINABILITY, 2022, 14 (08)
  • [3] A GIS-based comparative evaluation of analytical hierarchy process and frequency ratio models for landslide susceptibility mapping
    Wang, Qiqing
    Li, Wenping
    PHYSICAL GEOGRAPHY, 2017, 38 (04) : 318 - 337
  • [4] Modeling forest fire risk based on GIS-based analytical hierarchy process and statistical analysis in Mediterranean region
    Sivrikaya, Fatih
    Kucuk, Omer
    ECOLOGICAL INFORMATICS, 2022, 68
  • [5] A GIS-based comparative study of the analytic hierarchy process, bivariate statistics and frequency ratio methods for landslide susceptibility mapping in part of the Tehran metropolis, Iran
    Moradi, Samad
    Rezaei, Mohsen
    GEOPERSIA, 2014, 4 (01): : 45 - 61
  • [6] ASSESSMENT OF THE MONTHLY FOREST FIRE DANGER POTENTIAL USING GIS-BASED ANALYTIC HIERARCHY PROCESS IN SOUTHWEST TÜRKÎYE
    Goltas, Merih
    Ayberk, Hamit
    Kucuk, Omer
    SUMARSKI LIST, 2024, 148 (1-2): : 59 - 68
  • [7] GIS-based landscape vulnerability assessment to forest fire susceptibility of Rudraprayag district, Uttarakhand, India
    Mehebub Sahana
    Tariq Ahmad Ganaie
    Environmental Earth Sciences, 2017, 76
  • [8] GIS-based landscape vulnerability assessment to forest fire susceptibility of Rudraprayag district, Uttarakhand, India
    Sahana, Mehebub
    Ganaie, Tariq Ahmad
    ENVIRONMENTAL EARTH SCIENCES, 2017, 76 (20)
  • [9] A Comparison of the Qualitative Analytic Hierarchy Process and the Quantitative Frequency Ratio Techniques in Predicting Forest Fire-Prone Areas in Bhutan Using GIS
    Tshering, Kinley
    Thinley, Phuntsho
    Tehrany, Mahyat Shafapour
    Thinley, Ugyen
    Shabani, Farzin
    FORECASTING, 2020, 2 (02): : 36 - 58
  • [10] New forest fire assessment model based on artificial neural network and analytic hierarchy process or fuzzy-analytic hierarchy process methodology for fire vulnerability map
    Tahri, Meryem
    Badr, Sanaa
    Mohammadi, Zohreh
    Kašpar, Jan
    Berčák, Roman
    Holuša, Jaroslav
    Surový, Peter
    Marušák, Róbert
    Yousfi, Noura
    Engineering Applications of Artificial Intelligence, 2024, 138