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Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh

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Institute for Risk and Disaster Reduction, University College London (UCL), Gower Street, London WC1E 6BT, UK
2
Center for Spatial Information Science and Systems, George Mason University, Fairfax, VA 22030, USA
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BUET-Japan Institute of Disaster Prevention and Urban Safety (BUET-JIDPUS), Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh
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International Centre for Diarrhoeal Disease Research, Bangladesh (icddr,b), Mohakhali, Dhaka 1212, Bangladesh
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Engineering Faculty, China University of Geosciences, Wuhan 430074, China
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Geospatial Solutions Theme, International Centre for Integrated Mountain Development (ICIMOD), Kathmandu 44073, Nepal
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Department of Civil Engineering, Bangladesh University of Engineering and Technology (BUET), Dhaka 1000, Bangladesh
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2018, 7(12), 485; https://doi.org/10.3390/ijgi7120485
Received: 22 August 2018 / Revised: 26 October 2018 / Accepted: 15 December 2018 / Published: 19 December 2018
This article aims to develop a Web-GIS based landslide early warning system (EWS) for the Chittagong Metropolitan Area (CMA), Bangladesh, where, in recent years, rainfall-induced landslides have caused great losses of lives and property. A method for combining static landslide susceptibility maps and rainfall thresholds is proposed by introducing a purposely-build hazard matrix. To begin with, eleven factor maps: soil permeability; surface geology; landcover; altitude; slope; aspect; distance to stream; fault line; hill cut; road cut; and drainage network along with a detailed landslide inventory map were produced. These maps were used, and four methods were applied: artificial neural network (ANN); multiple regressions; principal component analysis; and support vector machine to produce landslide susceptibility maps. After model validation, the ANN map was found best fitting and was classified into never warning, low, medium, and high susceptibility zones. Rainfall threshold analysis (1960–2017) revealed consecutive 5-day periods of rainfall of 71–282 mm could initiate landslides in CMA. Later, the threshold was classified into three rainfall rates: low rainfall (70–160 mm), medium rainfall (161–250 mm), and high rainfall (>250 mm). Each landslide was associated with a hazard class (no warning vs. warning state) based on the assumption that the higher the susceptibility, the lower the rainfall. Finally, the EWS was developed using various libraries and frameworks that is connected with a reliable online-based weather application programming interface. The system is publicly available, dynamic, and replicable to similar contexts and is able to disseminate alerts five days in advance via email notifications. The proposed EWS is novel and the first of its kind in Bangladesh, and can be applied to mitigate landslide disaster risks. View Full-Text
Keywords: landslides; early warning system; remote sensing; GIS; susceptibility mapping; rainfall thresholds; disaster risk reduction landslides; early warning system; remote sensing; GIS; susceptibility mapping; rainfall thresholds; disaster risk reduction
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MDPI and ACS Style

Ahmed, B.; Rahman, M.S.; Islam, R.; Sammonds, P.; Zhou, C.; Uddin, K.; Al-Hussaini, T.M. Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh. ISPRS Int. J. Geo-Inf. 2018, 7, 485. https://doi.org/10.3390/ijgi7120485

AMA Style

Ahmed B, Rahman MS, Islam R, Sammonds P, Zhou C, Uddin K, Al-Hussaini TM. Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh. ISPRS International Journal of Geo-Information. 2018; 7(12):485. https://doi.org/10.3390/ijgi7120485

Chicago/Turabian Style

Ahmed, Bayes, Md. S. Rahman, Rahenul Islam, Peter Sammonds, Chao Zhou, Kabir Uddin, and Tahmeed M. Al-Hussaini 2018. "Developing a Dynamic Web-GIS Based Landslide Early Warning System for the Chittagong Metropolitan Area, Bangladesh" ISPRS International Journal of Geo-Information 7, no. 12: 485. https://doi.org/10.3390/ijgi7120485

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