NDLI: Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)

Content Provider	Springer Nature Link
Author	Aghdam, Iman Nasiri Varzandeh, Mohammad Hossein Morshed Pradhan, Biswajeet
Copyright Year	2016
Abstract	The main aim of this paper is to develop a new hybrid method to assess landslide susceptibility mapping (LSM) in neighboring provinces of Alborz Mountains in Iran. In the last centuries, this region has experienced a large number of landslides due to its location on earthquake belt, with high precipitation in some parts and having varied topography. Besides, the largest city of Iran (Tehran), a lot of important infrastructures, congested roads and a large population are located in this region. Therefore, determining the spatial outlines of the regions which are prone to future landslides is a critical issue. To reach this goal, the LSM is provided by applying a hybrid model of statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) in a Geographic Information System. In the first step, landslide inventory map was divided into two groups randomly. These groups are training dataset including 70 % recorded landslides and the remaining 30 % was used to test the model output. The first and second groups are used to determine the weights in model and validation of results, respectively. Then, 12 landslide conditioning factors are selected and categorized into two groups which are continuous numerical and nominal. After that, each factor is classified and the weight of each class is determined using Wi. The outputs of Wi and Wi-ANFIS were employed to determine nominal and continuous numerical data, respectively. In the Wi-ANFIS approach, the calculated weights of each class is allocated to the center of each class, and the rest weights of values are determined by ANFIS which is an artificial algorithm using training data (in this paper, the weights were calculated by Wi) in terms of predicting and interpolating. The results are evaluated using receiver operation curves including success rate curve and predicted rate curve. The validation results of the proposed hybrid method shows that the area under the curve of success rate curve and predicted rate curve are 0.90 and 0.89, respectively, which have been improved in comparison with Wi. The results pr oved that the suggested model applied in this study generated reliable LSM which can be applicable for primary land use planning and infrastructure site selection.
Starting Page	1
Ending Page	20
Page Count	20
File Format	PDF
ISSN	18666280
Journal	Environmental Earth Sciences
Volume Number	75
Issue Number	7
e-ISSN	18666299
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-03-25
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Landslide susceptibility ANFIS Ensemble GIS Alborz Mountain Iran Geology Hydrology/Water Resources Geochemistry Environmental Science and Engineering Terrestrial Pollution Biogeosciences
Content Type	Text
Resource Type	Article
Subject	Global and Planetary Change Earth-Surface Processes Soil Science Environmental Chemistry Pollution Geology Water Science and Technology

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Landslide susceptibility assessment using a novel hybrid model of statistical bivariate methods (FR and WOE) and adaptive neuro-fuzzy inference system (ANFIS) at southern Zagros Mountains in Iran

Forecasting and validation of landslide susceptibility using an integration of frequency ratio and neuro-fuzzy models: a case study of Seorak mountain area in Korea

Preliminary landslide susceptibility zonation using GIS-based fuzzy logic in Vitória, Brazil

Evaluation of blast-induced ground vibrations in open-pit mines by using adaptive neuro-fuzzy inference systems

Spatial variability of rock depth using adaptive neuro-fuzzy inference system (ANFIS) and multivariate adaptive regression spline (MARS)

Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia

Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran

Application of GIS-based fuzzy logic and rock engineering system (RES) approaches for landslide susceptibility mapping in Selelkula area of the Lower Jema River Gorge, Central Ethiopia

Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China

Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)

Similar Documents

Landslide susceptibility assessment using a novel hybrid model of statistical bivariate methods (FR and WOE) and adaptive neuro-fuzzy inference system (ANFIS) at southern Zagros Mountains in Iran

Forecasting and validation of landslide susceptibility using an integration of frequency ratio and neuro-fuzzy models: a case study of Seorak mountain area in Korea

Preliminary landslide susceptibility zonation using GIS-based fuzzy logic in Vitória, Brazil

Evaluation of blast-induced ground vibrations in open-pit mines by using adaptive neuro-fuzzy inference systems

Spatial variability of rock depth using adaptive neuro-fuzzy inference system (ANFIS) and multivariate adaptive regression spline (MARS)

Landslide susceptibility mapping using ensemble bivariate and multivariate statistical models in Fayfa area, Saudi Arabia

Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran

Application of GIS-based fuzzy logic and rock engineering system (RES) approaches for landslide susceptibility mapping in Selelkula area of the Lower Jema River Gorge, Central Ethiopia

Landslide susceptibility mapping based on GIS and support vector machine models for the Qianyang County, China

Landslide susceptibility mapping using an ensemble statistical index (Wi) and adaptive neuro-fuzzy inference system (ANFIS) model at Alborz Mountains (Iran)