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128076 - A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping.pdf (3.05 MB)

A new GIS-based technique using an adaptive neuro-fuzzy inference system for land subsidence susceptibility mapping

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journal contribution
posted on 2023-05-19, 20:54 authored by Ghorbanzadeh, O, Rostamzadeh, H, Blaschke, T, Gholaminia, K, Jagannath Aryal
In this study, we evaluated the predictive performance of an adaptive neuro-fuzzy inference system (ANFIS) with six different membership functions (MFs). Using a geographic information system (GIS), we applied ANFIS to land subsidence susceptibility mapping (LSSM) in the study area of Amol County, northern Iran. As a novelty, we derived a land subsidence inventory from the differential synthetic aperture radar interferometry (DInSAR) of two Sentinel-1 images. We used 70% of surface subsidence deformation areas for training, while 30% were reserved for testing and validation. We then investigated regions that are susceptible to subsidence via the ANFIS method and evaluated the resulting prediction maps using receiver operating characteristics (ROC) curves. Out of the six different versions, the most accurate map was generated with a Gaussian membership function, yielding an accuracy of 84%.

History

Publication title

Journal of Spatial Science

Volume

94

Pagination

1-18

ISSN

1449-8596

Department/School

School of Geography, Planning and Spatial Sciences

Publisher

Taylor & Francis Asia Pacific

Place of publication

Singapore

Rights statement

Copyright 2018 the authors. Licensed under Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) https://creativecommons.org/licenses/by-nc-nd/4.0/

Repository Status

  • Open

Socio-economic Objectives

Other environmental management not elsewhere classified