Landslide susceptibility zonation of the Western Ghats region in Thiruvananthapuram district (Kerala) using geospatial tools: A comparison of the AHP and Fuzzy-AHP methods

Akshaya, M.; Danumah, Jean Homian; Saha, Sunil; Ajin, R. S.; Kuriakose, Sekhar L.

doi:10.1007/s42797-021-00042-0

Cited by 11 publications

(18 citation statements)

References 81 publications

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“…They considered both PEV and SEV indicators, but the study was limited to a smaller area. The present study found that the F-AHP model is more effective than the AHP model for the assessment of PEV and SEV, whereas the AHP model was found to be slightly better than the F-AHP for the flood vulnerability assessment Akshaya et al (2021),Khashei-Siuki et al (2020), andTripathi et al (2021). also found that the F-AHP model is effective than the AHP model.According to the PEV modelling, very high and high vulnerable zones have lower slopes, clayey soil, agricultural land, the lowest stream density, and are coastal plains.…”

supporting

confidence: 47%

“…The present study found that the F-AHP model is more effective than the AHP model for the assessment of PEV and SEV, whereas the AHP model was found to be slightly better than the F-AHP for the flood vulnerability assessment. Akshaya et al ( 2021 ), Khashei-Siuki et al ( 2020 ), and Tripathi et al ( 2021 ) also found that the F-AHP model is effective than the AHP model.…”

Section: Discussionmentioning

confidence: 97%

“…The AHP method, developed by Thomas L. Saaty (Saaty 1980 ) is used to make difficult problems into a hierarchy and find the best answer for the goal (Qazi and Abushammala 2020 ). The creation of the matrix for pair-wise comparisons, the computation of the eigen vector, the weighting coefficient (Tables 2 and 3 ), and the consistency ratio (Tables 4 and 5 ) are the major procedures involved with the AHP modelling (Akshaya et al 2021 ; Amrutha et al 2022 ; Nikhil et al 2021 ; Thomas et al 2021 ).…”

Section: Methodsmentioning

confidence: 99%

“…Using Eqs. 5 and 6 , the eigen vector (Vp), and the weighting coefficient (Cp) were determined (as in Akshaya et al 2021 ; Nikhil et al 2021 ; Thomas et al 2021 ). where k = number of factors, and W = ratings.…”

Section: Methodsmentioning

confidence: 99%

“…Equations 7 , 8 , and 9 (Akshaya et al 2021 ; Nikhil et al 2021 ; Thomas et al 2021 ), were employed to compute the eigen value (λmax), consistency index (CI), and consistency ratio (CR). where RI = random index (Saaty 1980 ).…”

Section: Methodsmentioning

confidence: 99%

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Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

Senan

Ajin

Danumah

et al. 2022

Stoch Environ Res Risk Assess

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Flooding is one of the most destructive natural catastrophes that can strike anywhere in the world. With the recent, but frequent catastrophic flood events that occurred in the narrow stretch of land in southern India, sandwiched between the Western Ghats and the Arabian Sea, this study was initiated. The goal of this research is to identify flood-vulnerable zones in this area by making the local self governing bodies as the mapping unit. This study also assessed the predictive accuracy of analytical hierarchy process (AHP) and fuzzy-analytical hierarchy process (F-AHP) models. A total of 20 indicators (nine physical-environmental variables and 11 socio-economic variables) have been considered for the vulnerability modelling. Flood-vulnerability maps, created using remotely sensed satellite data and geographic information systems, was divided into five zones. AHP and F-AHP flood vulnerability models identified 12.29% and 11.81% of the area as very highvulnerable zones, respectively. The receiver operating characteristic (ROC) curve is used to validate these flood vulnerability maps. The flood vulnerable maps, created using the AHP and F-AHP methods, were found to be outstanding based on the area under the ROC curve (AUC) values. This demonstrates the effectiveness of these two models. The results of AUC for the AHP and F-AHP models were 0.946 and 0.943, respectively, articulating that the AHP model is more efficient than its chosen counterpart in demarcating the flood vulnerable zones. Decision-makers and land-use planners will find the generated vulnerable zone maps useful, particularly in implementing flood mitigation plans.

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supporting

confidence: 47%

Section: Discussionmentioning

confidence: 97%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

See 3 more Smart Citations

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

Senan

Ajin

Danumah

et al. 2022

Stoch Environ Res Risk Assess

Self Cite

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Vulnerability evaluation utilizing AHP and an ensemble model in a few landslide-prone areas of the Western Ghats, India

Anchima,

Gokul,

Senan

et al. 2023

Environ Dev Sustain

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Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

et al. 2022

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Dengue fever, which is spread by Aedes mosquitoes, has claimed many lives in Kerala, with the Thiruvananthapuram district bearing the brunt of the toll. This study aims to demarcate the dengue risk zones in Thiruvananthapuram district using the analytical hierarchy process (AHP) and the fuzzy-AHP (F-AHP) methods. For the risk modelling, geo-environmental factors (normalized difference vegetation index, land surface temperature, topographic wetness index, land use/land cover types, elevation, normalized difference built-up index) and demographic factors (household density, population density) have been utilized. The ArcGIS 10.8 and ERDAS Imagine 8.4 software tools have been used to derive the risk zone maps. The area of the risk maps is classified into five zones. The dengue risk zone maps were validated using dengue case data collected from the Integrated Disease Surveillance Programme portal. From the receiver operating characteristic (ROC) curve analysis and the area under the ROC curve (AUC) values, it is proved that the F-AHP method (AUC value of 0.971) has comparatively more prediction capability than the AHP method (AUC value of 0.954) in demarcating the dengue risk zones. Also, based on the comparison of the risk zone map with actual case data, it was confirmed that around 82.87% of the dengue cases occurred in the very high and high-risk zones, thus proving the efficacy of the model. According to the dengue risk map prepared using the F-AHP model, 9.09% of the area of Thiruvananthapuram district is categorized as very high risk. The prepared dengue risk maps will be helpful for decision-makers, staff with the health, and disaster management departments in adopting effective measures to prevent the risks of dengue spread and thereby minimize loss of life.

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Landslide susceptibility zonation of the Western Ghats region in Thiruvananthapuram district (Kerala) using geospatial tools: A comparison of the AHP and Fuzzy-AHP methods

Cited by 11 publications

References 81 publications

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models

Vulnerability evaluation utilizing AHP and an ensemble model in a few landslide-prone areas of the Western Ghats, India

Dengue risk zone mapping of Thiruvananthapuram district, India: a comparison of the AHP and F-AHP methods

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