An application of geospatial-based multi-criteria decision-making technique to identify landslide susceptibility zones in the Ragnu Khola River Basin of Darjeeling Himalayan region, India

被引:4
|
作者
Roy, Dipesh [1 ]
Das, Satyajit [1 ]
Mitra, Rajib [1 ]
机构
[1] Univ North Bengal, Dept Geog & Appl Geog, Siliguri, W Bengal, India
关键词
Landslide susceptibility zones (LSZ); River morphometry; MCDM technique; ROC-AUC; FUZZY INFERENCE SYSTEM; HIERARCHY PROCESS AHP; LOGISTIC-REGRESSION; FREQUENCY RATIO; HAZARD ZONATION; DRAINAGE BASINS; RANDOM FOREST; MODELS; MULTIVARIATE; ENTROPY;
D O I
10.1007/s12518-022-00468-6
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
One of the most dangerous geo-hazards, landslides cause a progressive loss of rock and soil that have a negative impact on human lives, the ecosystem, and the global economy. Darjeeling Himalaya is one of the world's young fold mountainous areas, often suffering from landslide hazards. Hence, the study identifies the landslide susceptibility zone in the Ragnu Khola River Basin of the Darjeeling Himalayan region by applying the geospatial-based MCDM technique. This research's major goal is to identify whether this GIS-based multi-criteria decision-making (MCDM) technique is validated or not for landslide susceptibility zones (LSZ); if validated, then how much manifests for describing the LSZ in the study area. MCDM evaluation applies to determining weight value to integrate different thematic layers of river morphometry like drainage diversity (DD) parameters and relief diversity (RD) parameters. Both DD and RD have significant impacts on landslide intensity. Hence, both layers are combined using the analytical hierarchy process (AHP) of the MCDM technique for the final LSZ. The final result has been validated by ROC analysis using landslide occurring point data obtained from the Geological Survey of India (GSI). The outcome of the study shows that 1.45% and 17.83% of areas of the region fall in "very high" and "high" LSZ, which belongs to near Mull Gaon, Sanchal forest, and Alubri basty. Most of the area (47.70%) is observed in "moderate" LSZ. Only 1.32% and 31.7% are kept in "very low" and "low" LSZ, respectively, throughout the study area. The description capability of the technique for LSZ is significant as the area under the curve (AUC) is 72.10%. The validation of the study using the frequency density of the landslides (FDL) also indicates the "very high" LSZ is associated with the maximum (2.19/km(2)) FDL. The work will be necessary to develop the overall socio-economic condition of such kind of tectonically sensitive region through proper and effective planning.
引用
收藏
页码:731 / 749
页数:19
相关论文
共 41 条
  • [1] An application of geospatial-based multi-criteria decision-making technique to identify landslide susceptibility zones in the Ragnu Khola River Basin of Darjeeling Himalayan region, India
    Dipesh Roy
    Satyajit Das
    Rajib Mitra
    [J]. Applied Geomatics, 2022, 14 : 731 - 749
  • [2] Multi-criteria decision process to identify groundwater potential zones using geospatial tools in the Arghandab river basin, Afghanistan
    Asadullah Farahmand
    Mohammad Salem Hussaini
    Hussain Ali Jawadi
    Manuel Abrunhosa
    Brian F. Thomas
    [J]. Environmental Earth Sciences, 2023, 82
  • [3] Multi-criteria decision process to identify groundwater potential zones using geospatial tools in the Arghandab river basin, Afghanistan
    Farahmand, Asadullah
    Hussaini, Mohammad Salem
    Jawadi, Hussain Ali
    Abrunhosa, Manuel
    Thomas, Brian F.
    [J]. ENVIRONMENTAL EARTH SCIENCES, 2023, 82 (14)
  • [4] Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
    Mantovani, Jose Roberto
    Bueno, Guilherme Taitson
    Alcantara, Enner
    Park, Edward
    Cunha, Ana Paula
    Londe, Luciana
    Massi, Klecia
    Marengo, Jose A. A.
    [J]. JOURNAL OF GEOVISUALIZATION AND SPATIAL ANALYSIS, 2023, 7 (01)
  • [5] Novel Landslide Susceptibility Mapping Based on Multi-criteria Decision-Making in Ouro Preto, Brazil
    José Roberto Mantovani
    Guilherme Taitson Bueno
    Enner Alcântara
    Edward Park
    Ana Paula Cunha
    Luciana Londe
    Klécia Massi
    Jose A. Marengo
    [J]. Journal of Geovisualization and Spatial Analysis, 2023, 7
  • [6] Delineation of groundwater potential zones through the integration of remote sensing, geographic information system, and multi-criteria decision-making technique in the sub-Himalayan foothills region, India
    Mitra R.
    Roy D.
    [J]. International Journal of Energy and Water Resources, 2023, 7 (4) : 581 - 601
  • [7] Analyzing landslide susceptibility, health vulnerability and risk using multi-criteria decision-making analysis in Arunachal Pradesh, India
    Rehman, Sufia
    Azhoni, Adani
    [J]. ACTA GEOPHYSICA, 2023, 71 (01) : 101 - 128
  • [8] Analyzing landslide susceptibility, health vulnerability and risk using multi-criteria decision-making analysis in Arunachal Pradesh, India
    Sufia Rehman
    Adani Azhoni
    [J]. Acta Geophysica, 2023, 71 : 101 - 128
  • [9] Evaluating Flood Susceptibility in the Brahmaputra River Basin: An Insight into Asia's Eastern Himalayan Floodplains Using Machine Learning and Multi-Criteria Decision-Making
    Jatan Debnath
    Dhrubajyoti Sahariah
    Meghna Mazumdar
    Durlov Lahon
    Gowhar Meraj
    Shizuka Hashimoto
    Pankaj Kumar
    Suraj Kumar Singh
    Shruti Kanga
    Kesar Chand
    Anup Saikia
    [J]. Earth Systems and Environment, 2023, 7 : 733 - 760
  • [10] Evaluating Flood Susceptibility in the Brahmaputra River Basin: An Insight into Asia's Eastern Himalayan Floodplains Using Machine Learning and Multi-Criteria Decision-Making
    Debnath, Jatan
    Sahariah, Dhrubajyoti
    Mazumdar, Meghna
    Lahon, Durlov
    Meraj, Gowhar
    Hashimoto, Shizuka
    Kumar, Pankaj
    Singh, Suraj Kumar
    Kanga, Shruti
    Chand, Kesar
    Saikia, Anup
    [J]. EARTH SYSTEMS AND ENVIRONMENT, 2023, 7 (04) : 733 - 760