Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)-Reference-Cited by-同舟云学术

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Land subsidence hazard assessment based on novel hybrid approach: BWM, weighted overlay index (WOI), and support vector machine (SVM)

Published:2022-09-23 Issue:3 Volume:115 Page:1997-2030
ISSN:0921-030X
Container-title:Natural Hazards
language:en
Short-container-title:Nat Hazards

Author:

Mehrnoor Shabnam,Robati Maryam,Kheirkhah Zarkesh Mir Masoud,Farsad Forough,Baikpour Shahram

Publisher

Springer Science and Business Media LLC

Subject

Earth and Planetary Sciences (miscellaneous),Atmospheric Science,Water Science and Technology

Link

https://link.springer.com/content/pdf/10.1007/s11069-022-05624-0.pdf

Reference91 articles.

1. Abdollahi S, Pourghasemi HR, Ghanbarian GA, Safaeian R (2019) Prioritization of effective factors in the occurrence of land subsidence and its susceptibility mapping using an SVM model and their different kernel functions. Bull Eng Geol Environ 78(6):4017–4034. https://doi.org/10.1007/s10064-018-1403-6

2. Abidin HZ, Andreas H, Gumilar I, Brinkman JJ (2015) Study on the risk and impacts of land subsidence in Jakarta. Proc Int Assoc Hydrol Sci 372:115–120. https://doi.org/10.5194/piahs-372-115-2015

3. Aditiya A, Takeuchi W, Aoki Y (2017) Land Subsidence Monitoring by InSAR Time Series Technique Derived From ALOS-2 PALSAR-2 over Surabaya City, Indonesia. In: IOP Conference Series: Earth and Environmental Science 98(1): 012010, https://iopscience.iop.org/article/https://doi.org/10.1088/1755-1315/98/1/012010/meta

4. Agarwal R, Garg PK (2016) Remote sensing and GIS based groundwater potential & recharge zones mapping using multi-criteria decision making technique. Water Resour Manage 30(1):243–260. https://doi.org/10.1007/s11269-015-1159-8

5. Arabameri A, Saha S, Roy J, Tiefenbacher JP, Cerda A, Biggs T, Collins AL (2020) A novel ensemble computational intelligence approach for the spatial prediction of land subsidence susceptibility. Sci Total Environ 726:138595. https://doi.org/10.1016/j.scitotenv.2020.138595

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