GIS Based Landslide Susceptibility Mapping using a Fuzzy Logic Approach: A Case Study from Ghurmi-Dhad Khola Area, Eastern Nepal

Kayastha, Prabin; Bijukchhen, Subeg; Dhital, Megh Raj; Smedt, Florimond De

doi:10.1007/s12594-013-0147-y

Cited by 47 publications

(13 citation statements)

References 30 publications

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“…In every study, the basic and first step is to build a dataset for criteria which is specifically designed for the study area. In this study, based on the surveys and researches, nine criteria were selected (precipitation, 39 slope, [39][40][41][42][43] aspect, [39][40][41][42][43] lithology, 21,39,40,43,44 landuse, [40][41][42][43][44][45][46] distance to road, [39][40][41][42] distance to river, 39,41 distance to faults, 39,43 and curvature. [39][40][41][42] In order to produce and analyze the data layers, ArcGIS was used and all factors were prepared as a raster dataset.…”

Section: Criteria Defining and Localizingmentioning

confidence: 99%

“…Landslide susceptibility maps are helpful tools for decision makers and future constructors for spatial plannings, 13 therefore many different approaches have been applied to make the most optimum prediction of landslide disasters, some examples of these approaches are Index of Entropy (IOE) 14 Weigh of Evidence 15 Statistical Index method, 16 Logistic Regression 4,16,17 Analytic Hierarchy Process technique 16,18,19 Fuzzy Logic. [20][21][22][23] Barrile et al. 24 used GIS-based fuzzy logic in order for road network planning.…”

Section: Introductionmentioning

confidence: 99%

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Landslide modelling and susceptibility mapping using AHP and fuzzy approaches

Noorollahi

Sadeghi

Yousefi

et al. 2018

IJH

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Landslide is one of the most destructive natural hazards that can impose economical and life loss. Fortunately, through numerical and spatial analysis we can lessen the damages caused by landslides. In this study which goes through landslide susceptibility mapping, a combination of AHP and Fuzzy approaches is applied. AHP is used in order to prioritize the effective criteria and Fuzzy method is used in two steps, factor map fuzzification, and factor maps are calculated and overlaid after fuzzification. In order to achieve the best output susceptibility map, 6 scenarios has been proposed in fuzzy overlay step for a study area in Iran as a case study and the best scenario has been chosen according to the comparison of every output with observed landslides layer. The susceptibility map that has the greatest overlap area was the result of using fuzzy Or in overlap step which is considered as a suitable way in hazard risk zonnation. Analysis of the final landslide susceptibility map shows that scenario 6 which is proven to be the most suitable outcome, has the least AUC= 0.3 and matches with observed landslides much better than other scenarios, and through physiographical analysis, we found that most landslides have occurred and are probable in are used as good ranges, are in middle slope angle, and have northern slope aspects.

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Section: Criteria Defining and Localizingmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Landslide modelling and susceptibility mapping using AHP and fuzzy approaches

Noorollahi

Sadeghi

Yousefi

et al. 2018

IJH

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show abstract

“…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%

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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“…Slope failure is typical problem of mountain landscape and landslide constitute most common type of slope failure in the HKH region (Kuenza et al 2004;Pareta et al 2012;Bhattarai and Pradhan 2013;Kayastha et al 2013). In addition to primary impact, mega landslide like recent case of Jure landslide in Nepal, and Tsatichhu landslide in Bhutan (Dunning et al 2006) can result long term secondary and tertiary impact, and can undermine national economy.…”

Section: Landslide Susceptibility Mapping Initiativementioning

confidence: 99%

Multi scale Disaster Risk Reduction Systems Space and Community based Experiences over HKH Region

Gurung

Shrestha

et al. 2014

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:An increasing trend in the recurrence of natural disasters and associated impacts due to Floods, Glacier Lake out bursts, landslides and forest fire is reported over Hindu Kush Himalyan (HKH) region. Climate change and anthropogenic coupled factors are identified as primary factors for such increased vulnerability. The large degree of poverty, lack of infrastructure, poor accessibility and uncertainties involved in understanding high altitude land surface and climate dynamics poses serious challenges in reducing disaster vulnerability and mitigating disaster impacts. In this context effective development of Disaster Risk Reduction (DRR) protocols and mechanisms have been realized as an urgent need. The paper presents the adoption and experiences of multi scale DRR systems across different Himalayan member countries ranging from community based indigenous early warning to space based emergency response and decision support systems.The Establishment of a Regional Flood Information System (HKH-HYCOS) over Ganges-Brahmaputra-Meghna (GBM) and Indus river basins promoted the timely exchange of flood data and information for the reduction of flood vulnerability within and among the participating countries. Satellite based forest fire alert systems evoked significant response among diverse stakeholders to optimize fire incidence and control. Satellite rainfall estimation products, satellite altimetry based flood early warning systems, flood inundation modelling and products, model derived hydrology flow products from different global data-sharing networks constitutes diverse information to support multi scale DRR systems. Community-based Flood Early Warning System (FEWS) enabled by wireless technology established over the Singara and Jiadhal rivers in Assam also stands as one of the promising examples of minimizing flood risk. Disaster database and information system and decision support tools in Nepal serves as potential tool to support diverse stakeholders. * Corresponding author. This is useful to know for communication with the appropriate person in cases with more than one author.

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GIS Based Landslide Susceptibility Mapping using a Fuzzy Logic Approach: A Case Study from Ghurmi-Dhad Khola Area, Eastern Nepal

Cited by 47 publications

References 30 publications

Landslide modelling and susceptibility mapping using AHP and fuzzy approaches

Landslide modelling and susceptibility mapping using AHP and fuzzy approaches

Earthquake Prediction Using Expert Systems: A Systematic Mapping Study

Multi scale Disaster Risk Reduction Systems Space and Community based Experiences over HKH Region

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