GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia

Mallick, Javed; Singh, Ram Karan; AlAwadh, Mohammed A.; Islam, Saiful; Khan, Roohul Abad; Qureshi, M.N.

doi:10.1007/s12665-018-7451-1

Cited by 110 publications

(49 citation statements)

References 94 publications

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“…In order to take advantage of both the fuzzy technique and the AHP, Van Laarhoven and Pedrycz [118] used the principles of fuzzy logic in AHP. Over the last decade, Fuzzy-AHP was one of the widely accepted techniques for multi-criteria decision making in various applications, such as groundwater quality assessment [119], landslide [120], ecosystem and environment vulnerability [121], groundwater vulnerability analysis [122], and extracting the water quality [123]. In this study also, the competence of the proposed GIS-based Fuzzy-AHP models made the application more realistic and reliable.…”

Section: Analysis Of Gwpz Classification Mapmentioning

confidence: 89%

Modeling Groundwater Potential Zone in a Semi-Arid Region of Aseer Using Fuzzy-AHP and Geoinformation Techniques

Mallick

Khan

Ahmed

et al. 2019

Water

Self Cite

164

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Saudi Arabia’s arid and semi-arid regions suffer from water scarcity because of climatic constraints and rapid growth of domestic and industrial water uses. The growing demand for high-quality water supplies and to reduce the dependency on desalination creates an urgent need to explore groundwater resources as an alternative. The weighted overlay analysis method using the fuzzy-analytical hierarchy process (FAHP) multi-criteria decision making (MCDM) techniques combined with geoinformation technology was used in this study to explore the groundwater potential zones in the Itwad-Khamis watershed of Saudi Arabia. Twelve thematic layers were prepared and processed in a GIS setting to produce the groundwater potential zone map (GPZM). Subsequently, potential groundwater areas were delineated and drawn into five classes: very good potential, good potential, moderate potential, poor potential, and very poor potential. The estimated GWPZ (groundwater potential zones) was validated by analyzing the existing open wells distribution and the yield data of selected wells within the studied watershed. With this quality-based zoning, it was found that 82% of existing wells were located in a very good and good potential area. The statistical analysis showed that 14.6% and 28.8% of the total area were under very good and good, while 27.3% and 20.2% were accounted for the moderate and poor potential zone, respectively. To achieve sustainable groundwater management in the Aseer region, Saudi Arabia, this research provided a primary estimate and significant insights for local water managers and authorities by providing groundwater potential zone map.

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Section: Analysis Of Gwpz Classification Mapmentioning

confidence: 89%

Modeling Groundwater Potential Zone in a Semi-Arid Region of Aseer Using Fuzzy-AHP and Geoinformation Techniques

Mallick

Khan

Ahmed

et al. 2019

Water

Self Cite

164

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“…e difference may be caused by the ANP which considers the connection of Hierarchy 2 such as A: potential and B: hazard. Since the ANP is an expansion of the AHP, it more accurately reflects the real weights of factors, so the ANP is considered a better choice for the overlay analysis of the geographic information system (GIS) [34][35][36].…”

Section: Results Of the Expert Questionnaire Surveymentioning

confidence: 99%

Analysis of the Potential for a Hillside Collapse for a Community in Changhua County, Taiwan

Liu

Tsai

Peng

2019

Advances in Civil Engineering

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To create communities that are resistant to disasters, public disaster prevention and response must be reinforced by promoting disaster prevention and knowledge and technology to ensure an adequate response through public participation. Promoting disaster prevention measures reduces the number of factors in communities that pertain to disasters. Changhua County contains 589 villages, 81 of which are prone to hillsides (including protected forest). In addition to original potential debris flow torrent communities, disaster-resistant communities have been established under the guidance of Soil and Water Conservation Bureau (SWCB), Council of Agriculture in Taiwan; Changhua County Government also plans to establish disaster-resistant communities in other hillside communities. This study proposes an expert questionnaire to determine the potential for a hillside disaster and uses an analytical hierarchy process (AHP) and an analytical network process (ANP) to determine the weights of factors that pertain to potential disasters in hillside communities so that these communities can become resistant to disasters.

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“…In this mapping study, main techniques used for earthquake prediction including rule-based, fuzzy, neuro-fuzzy and machine learning have been explored. Expert systems based approaches have been used for seismic risk assessment for landslide susceptibility through seismic hazard analysis [50][51][52] and soil classification [53]. ES have also been applied in earthquake engineering for seismic hazard analysis and assessment of bridges and buildings under multiple hazards [24,54,55].…”

Section: Discussionmentioning

confidence: 99%

“…These tools and techniques have been summarized in Table 9. Annealing, Sparsespike 1.8 [25] Classification and regression trees(CART) 1.8 [49] Fuzzy C-mean 4 [28,77] Upgraded IF THEN ELSE 4 [27,83] Normalized fuzzy peak ground acceleration (FPGA) 1.8 [8] Aeronautical reconnaissance coverage Geographic information system (ARC/INFO GIS) 1.8 [84] Geographic information system (GIS), Multi criteria decision analysis (MCDA) 4 [15,82] Multilayer Preceptron -Rule Based (MLP-RB) 1.8 [21] Nearest neighbor Invariant Riemannian metric (AIRM) 1.8 [52] WI (Weighted index) 1.8 [5] Knowledge extraction based on evolutionary learning (KEEL) 1.8 [10] Particle SWARM Optimization (PSO) 1.8 [56] Apache SPARK 1.8 [59] Kernal Fisher Discriminant Algoritthm (KFDA) 1.8 [60] Novel earthquake early warning system (NEEWS) 1.8 [64] Accuracy of results obtained through the proposed expert system for making earthquake predictions using a training set (TS) or independent test set (ITS) has been listed in Table 10.…”

Section: Basic Analysismentioning

confidence: 99%

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

2020

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Earthquake is one of the most hazardous natural calamity. Many algorithms have been proposed for earthquake prediction using expert systems (ES). We aim to identify and compare methods, models, frameworks, and tools used to forecast earthquakes using different parameters. We have conducted a systematic mapping study based upon 70 systematically selected high quality peer reviewed research articles involving ES for earthquake prediction, published between January 2010 and January 2020.To the best of our knowledge, there is no recent study that provides a comprehensive survey of this research area. The analysis shows that most of the proposed models have attempted long term predictions about time, intensity, and location of future earthquakes. The article discusses different variants of rule-based, fuzzy, and machine learning based expert systems for earthquake prediction. Moreover, the discussion covers regional and global seismic data sets used, tools employed, to predict earth quake for different geographical regions. Bibliometric and meta-information based analysis has been performed by classifying the articles according to research type, empirical type, approach, target area, and system specific parameters. Lastly, it also presents a taxonomy of earthquake prediction approaches, and research evolution during the last decade.

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GIS-based landslide susceptibility evaluation using fuzzy-AHP multi-criteria decision-making techniques in the Abha Watershed, Saudi Arabia

Cited by 110 publications

References 94 publications

Modeling Groundwater Potential Zone in a Semi-Arid Region of Aseer Using Fuzzy-AHP and Geoinformation Techniques

Modeling Groundwater Potential Zone in a Semi-Arid Region of Aseer Using Fuzzy-AHP and Geoinformation Techniques

Analysis of the Potential for a Hillside Collapse for a Community in Changhua County, Taiwan

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

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