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

被引:60
作者
Sur, Ujjwal [1 ]
Singh, Prafull [1 ,2 ]
Meena, Sansar Raj [3 ,4 ]
机构
[1] Amity Univ, Amity Inst Geoinformat & Remote Sensing, Sect 125, Noida, India
[2] Cent Univ South Bihar, Dept Geol, Gaya, India
[3] Univ Salzburg, Dept Geoinformat Z GIS, Salzburg, Austria
[4] Univ Twente, Fac Geoinformat Sci & Earth Observat ITC, Enschede, Netherlands
关键词
Landslide susceptibility index (LSI); fuzzy analytic hierarchy process (fuzzy AHP); lesser Himalayas; road corridor; GIS; WEIGHTS-OF-EVIDENCE; FREQUENCY RATIO; LOGISTIC-REGRESSION; RISK-ASSESSMENT; HAZARD; MODEL; PRIORITIZATION; DECISION; PROVINCE; COUNTY;
D O I
10.1080/19475705.2020.1836038
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
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 86.52% accuracy in landslide prediction evaluated through the ROC curve (at 95% confidence level). Hence, the output LSI may be referred by the planners and engineers for monitoring, prevention, and mitigation of landslide hazards and development of infrastructure in the Kalsi-Chakrata road corridor, and the fuzzy AHP methodology adopted may be applied in other areas of the Lesser Himalayas.
引用
收藏
页码:2176 / 2209
页数:34
相关论文
共 68 条
[61]  
Varnes D.J., 1984, Natural Hazards, V3, P61
[62]   Predictive modeling of landslide hazards in Wen County, northwestern China based on information value, weights-of-evidence, and certainty factor [J].
Wang, Qiqing ;
Guo, Yinghai ;
Li, Wenping ;
He, Jianghui ;
Wu, Zhiyong .
GEOMATICS NATURAL HAZARDS & RISK, 2019, 10 (01) :820-835
[63]   Comparative study of landslide susceptibility mapping with different recurrent neural networks [J].
Wang, Yi ;
Fang, Zhice ;
Wang, Mao ;
Peng, Ling ;
Hong, Haoyuan .
COMPUTERS & GEOSCIENCES, 2020, 138
[64]   Landslide susceptibility assessment using frequency ratio, statistical index and certainty factor models for the Gangu County, China [J].
Wu, Yanli ;
Li, Wenping ;
Wang, Qiqing ;
Liu, Qiangqiang ;
Yang, Dongdong ;
Xing, Maolin ;
Pei, Yabing ;
Yan, Shishun .
ARABIAN JOURNAL OF GEOSCIENCES, 2016, 9 (02) :1-16
[65]   Formation mechanism of Ruddlesden-Popper-type antiphase boundaries during the kinetically limited growth of Sr rich SrTiO3 thin films [J].
Xu, Chencheng ;
Du, Hongchu ;
van der Torren, Alexander J. H. ;
Aarts, Jan ;
Jia, Chun-Lin ;
Dittmann, Regina .
SCIENTIFIC REPORTS, 2016, 6
[66]   FUZZY SETS [J].
ZADEH, LA .
INFORMATION AND CONTROL, 1965, 8 (03) :338-&
[67]   Risk assessment model of expansive soil slope stability based on Fuzzy-AHP method and its engineering application [J].
Zhang, Jian ;
He, Peng ;
Xiao, Jie ;
Xu, Fei .
GEOMATICS NATURAL HAZARDS & RISK, 2018, 9 (01) :389-402
[68]  
Zimmermann H-J., 1992, FUZZY SET THEORY, V2