Application of AHP with GIS in drought risk assessment for Puruliya district, India

Palchaudhuri, Moumita; Biswas, Sujata

doi:10.1007/s11069-016-2526-3

Cited by 102 publications

(43 citation statements)

References 27 publications

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“…Urban rainstorm disaster is the result of the combination of various natural and social factors. In the past, scholars mostly analyzed the risk of urban storm flood disaster from the vulnerability of hazard-affected body, the danger of hazard factors, the fragility of disaster-pregnant environment, and the ability of disaster prevention and mitigation [ 23 , 24 , 25 , 26 , 27 , 28 ]. Based on the research of these scholars, this paper considers that the vulnerability of the hazard-affected body has obvious correlation with the ability of disaster prevention and mitigation, that is, the higher the economic level and population quality of the disaster-bearing body, the stronger its ability of disaster prevention and mitigation.…”

Section: Methodsmentioning

confidence: 99%

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China

Chen

Wang

et al. 2020

IJERPH

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Nanjing city is taken as a case in this urban rainstorm disaster risk research. Using the data of meteorology and social-economy statistics of Nanjing area, the paper selected ten indicators to establish the risk assessment system of urban rainstorm disaster from the aspects of the vulnerability of hazard-affected body, the fragility of disaster-pregnant environment, and the danger of hazard factors. Multi-layer weighted principal component analysis (MLWPCA) is an extension of the principal component analysis (PCA). The MLWPCA is based on factor analysis for the division subsystem. Then the PCA is used to analyze the indicators in each subsystem and weighted to synthesize. ArcGIS is used to describe regional differences in the urban rainstorm disaster risk. Results show that the MLWPCA is more targeted and discriminatory than principal component analysis in the risk assessment of urban rainstorm disaster. Hazard-affected body and disaster-pregnant environment have greater impacts on the risk assessment of rainstorm disaster in Nanjing, but the influence of hazard factors is few. Spatially, there is a large gap in the rainstorm disaster risk in Nanjing. The areas with high-risk rainstorm disaster are mainly concentrated in the central part of Nanjing, and the areas with low-risk rainstorm disaster are in the south and north of the city.

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Section: Methodsmentioning

confidence: 99%

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China

Chen

Wang

et al. 2020

IJERPH

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“…The above-mentioned thematic layers were combined by using a weight-of-factors approach determined by AHP to develop the landslide susceptibility map. The use of AHP to develop landslide susceptibility maps has been successfully applied in various regions [61,66,67]. The weights required to carry out AHP were calculated by performing pairwise comparisons for each landslide factor and assigning values from 1 to 9 [63,[68][69][70].…”

Section: Landslide Susceptibility Mappingmentioning

confidence: 99%

Temporal Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan

Dikshit

Sarkar

Pradhan

et al. 2020

Water

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Landslides are one of the major natural disasters that Bhutan faces every year. The monsoon season in Bhutan is usually marked by heavy rainfall, which leads to multiple landslides, especially across the highways, and affects the entire transportation network of the nation. The determinations of rainfall thresholds are often used to predict the possible occurrence of landslides. A rainfall threshold was defined along Samdrup Jongkhar–Trashigang highway in eastern Bhutan using cumulated event rainfall and antecedent rainfall conditions. Threshold values were determined using the available daily rainfall and landslide data from 2014 to 2017, and validated using the 2018 dataset. The threshold determined was used to estimate temporal probability using a Poisson probability model. Finally, a landslide susceptibility map using the analytic hierarchy process was developed for the highway to identify the sections of the highway that are more susceptible to landslides. The accuracy of the model was validated using the area under the receiver operating characteristic curves. The results presented here may be regarded as a first step towards understanding of landslide hazards and development of an early warning system for a region where such studies have not previously been conducted.

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“…Drought is one of the natural hazards characterized by a prolonged water shortage. The impacts of drought are multifaceted, ranging from the environment of a country to its economy and society [1][2][3][4][5][6]. Various components including agriculture, vegetation, ecosystem, and water resources can be affected by drought [7,8].…”

Section: Introductionmentioning

confidence: 99%

Assessing Agricultural Vulnerability to Drought in a Heterogeneous Environment: A Remote Sensing-Based Approach

Faridatul

Ahmed

2020

Remote Sensing

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Agriculture is one of the fundamental economic activities in most countries; however, this sector suffers from various natural hazards including flood and drought. The determination of drought-prone areas is essential to select drought-tolerant crops in climate sensitive vulnerable areas. This study aims to enhance the detection of agricultural areas with vulnerability to drought conditions in a heterogeneous environment, taking Bangladesh as a case study. The normalized difference vegetation index (NDVI) and land cover products from the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite images have been incorporated to compute the vegetation index. In this study, a modified vegetation condition index (mVCI) is proposed to enhance the estimation of agricultural drought. The NDVI values ranging between 0.44 to 0.66 for croplands are utilized for the mVCI. The outcomes of the mVCI are compared with the traditional vegetation condition index (VCI). Precipitation and crop yield data are used for the evaluation. The mVCI maps from multiple years (2006–2018) have been produced to compute the drought hazard index (DHI) using a weighted sum overlay method. The results show that the proposed mVCI enhances the detection of agricultural drought compared to the traditional VCI in a heterogeneous environment. The “Aus” rice-growing season (sown in mid-March to mid-April and harvested in mid-July to early August) receives the highest average precipitation (>400 mm), and thereby this season is less vulnerable to drought. A comparison of crop yields reveals the lowest productivity in the drought year (2006) compared to the non-drought year (2018), and the DHI map presents that the north-west region of Bangladesh is highly vulnerable to agricultural drought. This study has undertaken a large-scale analysis that is important to prioritize agricultural zones and initiate development projects based on the associated level of vulnerability.

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Application of AHP with GIS in drought risk assessment for Puruliya district, India

Cited by 102 publications

References 27 publications

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China

Risk Assessment of Urban Rainstorm Disaster Based on Multi-Layer Weighted Principal Component Analysis: A Case Study of Nanjing, China

Temporal Probability Assessment and Its Use in Landslide Susceptibility Mapping for Eastern Bhutan

Assessing Agricultural Vulnerability to Drought in a Heterogeneous Environment: A Remote Sensing-Based Approach

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