COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

Mijani, Naeim; Samani, Najmeh Neysani

doi:10.5194/isprs-archives-xlii-4-w4-407-2017

Cited by 13 publications

(5 citation statements)

References 44 publications

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“…Nonetheless, the study, by incorporating linguistic variables, offers a more accurate assessment of safe site suitability mapping. The data's fuzziness introduces errors in estimation that can be effectively corrected by using fuzzy-AHP weights [79]. This study's findings are consistent with those of Aburas et al [80].…”

Section: Discussionsupporting

confidence: 91%

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

et al. 2022

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The site selection process for a building entails evaluating a variety of factors with varying degrees of importance or percentage influence. In order to ensure that critical site selection factors are not overlooked, a methodology for calculating a building’s safe site selection must be developed. The study identified three broad aspects widely considered in site selection, namely environmental, physical, and socioeconomic criteria. To assess the safest site selection of residential building construction for sustainable urban growth, we used GIS-based multi-criteria decision-making approach that combined Fuzzy-AHP and weighted linear combination (WLC) aggregation method used to calculate the SSPZ. The final safe site suitability map was generated by aggregating all aspects such as geophysical, socio-economic and Geo-environmental thematic layers and their associated Fuzzy-AHP weights using the weighted linear combination method. The sites potential index’s mean value of 0.513 with standard deviation of 0.340, minimum and maximum GeoPhySSSI are 0.0 and 0.91, respectively, SSS index is classified into zones by histogram profile using natural breaks (jenks)” Subsequently, safe sites identified and divided into six classes namely no construction, very low suitable site low suitable site, moderate suitable site, high suitable site, and very high suitable site.“ According to the statistical analysis, 3.64% and 32.12% of the total area were under very high and high SSSZ, while 26.40% and 6.22% accounted to the moderate and low suitable potential, respectively” Our findings suggest that integrating the fuzzy collection with AHP is highly desirable in terms of alternative and decision-making effectiveness. The study reveals that the areas of high and moderate suitability are located near existing habitant area, major roads, and educational and health services; they are not located in restricted/protected areas or are vulnerable to natural hazards. The findings indicate that unsuitable and less-suitable land uses such as vegetation, protected areas, and agriculture lands cover nearly one-third area of Abha-Khamis Mushyet regions, implying that using Fuzzy-AHP and GIS techniques will significantly aid in the conservation of the environment. This would significantly mitigate adverse effects on the ecosystem and climate.

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Section: Discussionsupporting

confidence: 91%

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

et al. 2022

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“…Though a few authors pointed out the lack of matrix consistency in fuzzy AHp studies (Duru et al 2012), several authors established that the integrated fuzzy sets with AHP give high adaptability in decision making (Mallick et al 2018;Noorollahi et al 2018). The fuzzy logic adopted with AHP technique is much easier to comprehend and implement; hence, the weighting can be defined by the experts and data for any measurement scale can be contained within the system (Chen et al 2011;Feizizadeh et al 2013;Mijani and Samani 2017).…”

Section: Discussionmentioning

confidence: 99%

Landslide susceptibility assessment in a lesser Himalayan road corridor (India) applying fuzzy AHP technique and earth-observation data

Sur

Singh

Meena

2020

Geomatics, Natural Hazards and Risk

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The Kalsi-Chakrata road corridor, located in the Lesser Himalayas, experiences several landslides every year, resulting in a considerable amount of damage to roads, assets, and other infrastructure and even loss of lives. During the monsoon season (June-August), the disruption of routes due to landslide resulted in economic losses and barred villagers from accessing critical and essential facilities, thus impacting the livelihood of the communities residing along the road corridor. Hence immediate requirement was to systematically assess the landslide susceptibility for the study area that would support in the preparation of the planning and mitigation goal, both short and long term. The present study adopted the fuzzy analytic hierarchy process (fuzzy AHP) method integrated with geospatial technology that may be highly effective for landslide susceptibility assessment in the landslide-prone Lesser Himalayas. The use of validated landslide inventory data and high-resolution remote sensing images for selection and mapping of landslide conditioning factors gratifies the geospatial aspect of local variations across the Kalsi-Chakrata road corridor. For fuzzy AHP model setup, prominent landslide contributing factors viz., slope, aspect, altitude, lithology, proximity to road, fault & drainage, Stream Power Index (SPI), Topographical Wetness Index (TWI), rainfall, land use/land cover (LULC), soil, and seismicity, were mapped and classified into significant classes. The resultant landslide susceptibility map (LSM) shows that about 55% (45.23 km 2) of the study area was categorized as a very high and high landslide susceptibility zone. Of this, about 21% (17.7 km 2) was within very high LSM zone, while 33% (27.5 km 2) fell under high landslide susceptibility categories. Approximately 17.6% (14.5 km 2) areas fall within the moderately susceptible zone, where chances of future landslides may be amplified without periodic observation and prospective study. At the village level, it was observed that Jhutaya village, located nearer foothill of Lesser Himalayas, is most susceptible to landslide followed by Dhaira, Chapanu, and Sairi villages. The fuzzy AHP model shows ARTICLE HISTORY

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“…Each of these numbers indicates the importance of criteria. In the modeling process, the greatest weight is assigned to the most effective criterion (Mijani & Samani, 2017; Saaty, 2008). Verification of consistency .…”

Section: Methodsmentioning

confidence: 99%

Spatial modeling of migration using GIS‐based multi‐criteria decision analysis: A case study of Iran

Mijani

Sani

Dastaran

et al. 2021

Transactions in GIS

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Spatial modeling of migration and the identification of the effective parameters are imperative for planning and managing demographic, economic, social, and environmental changes on various geographical scales. The recent climate change stressors as well as inequality in terms of education and life quality have triggered internal mass migrations in Iran, causing pressure on housing, the job market, and potential slums around large cities. This study proposes a new approach to modeling migration patterns in Iran based on multi‐criteria decision analysis. For this purpose, a total of 23 individual criteria embedded within four criteria groups (economic, socio‐cultural, welfare, and environmental) affecting national migration were used. The analytic hierarchy process was employed to determine weights for the input factors and the weighted linear combination (WLC) model was used for the integration of criteria, based on which maps of migration potential were produced. The model applied was evaluated based on the correlation coefficient between migration potential values obtained from the WLC model and the actual net migration rate. Among the input individual criteria, unemployment, higher education centers, number of physicians, and dust storms were found to influence national migration. Furthermore, our findings reveal that the potential for migration across Iranian provinces is heterogeneous, with the spatial potential for emigration being the highest and lowest in the border and central provinces, respectively. The correlation coefficient calculated between outputs from the WLC model and the net migration rate from 2011 to 2016, was .81, indicating the relatively high performance of the proposed model in producing a migration spatial potential map. Our proposed approach, along with the results achieved, can be useful to decision‐makers and planners in designing data‐driven policies against inequality‐ and climate‐induced stressors.

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COMPARISON of FUZZY-BASED MODELS in LANDSLIDE HAZARD MAPPING

Cited by 13 publications

References 44 publications

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

GIS-Based Decision Support System for Safe and Sustainable Building Construction Site in a Mountainous Region

Landslide susceptibility assessment in a lesser Himalayan road corridor (India) applying fuzzy AHP technique and earth-observation data

Spatial modeling of migration using GIS‐based multi‐criteria decision analysis: A case study of Iran

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