The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON COMPUTER RESEARCH
Transactions ID Number: 32-281
Full Name: Prabu Sevugan
Position: Researcher
Age: ON
Sex: Male
Address: Institute of Remote Sensing,College of Engineering Guindy, Anna University,sardar patel road, guindy
Country: INDIA
Tel:
Tel prefix:
Fax:
E-mail address: sevu_prabu@yahoo.co.in
Other E-mails: prabu.sevugan@gmail.com
Title of the Paper: Assessment of landslide hazards using Analytical Hierarchic Process (AHP) method and Back Propagation Network model
Authors as they appear in the Paper: S.Prabu, Dr.S.S.Ramakrishnan, Dr.R.Vidhya,Dr. Hema A Murthy
Email addresses of all the authors: ssramki@annauniv.edu,rvidhya@annauniv.edu,hema@lantana.tenet.res.in
Number of paper pages: 10
Abstract: Landslides are significant natural hazards in southern hilly region parts of India with respect to economic losses and casualties. The work presented in this paper is to use of remote sensing and Geographical Information Systems (GIS) technology for developing techniques for landslide susceptibility mapping using Analytical Hierarchical Process (AHP) and assessed the accuracy of hazard map with artificial neural networks model. The AHP method assigns scores to each landslide causing factors of micro-topography of landslide-prone areas identified in aerial photographs, and assesses the susceptibility of landslide from the total score. The landslide-related factors (slope, aspect, curvature, topographic type, soil, rainfall, geology and land use) were extracted from the spatial database. Using those factors, landslide susceptibility was analyzed by artificial neural network (ANN) methods. For this, the weights of each factor were determined by the back propagation ne!
twork, which is a type of artificial neural network method. Then the landslide susceptibility indexes were calculated and the susceptibility maps were made with a GIS program The results of the landslide susceptibility maps were verified and compared using landslide location data. A GIS was used to efficiently analyze the vast amount of data, and an artificial neural network was turned out be an effective tool to maintain precision and accuracy.
Keywords: Landslide susceptibility mapping, Geographical Information System, Analytical Hierarchical Process, Artificial Neural Networks, Back Propagation Network.
EXTENSION of the file: .pdf
Special (Invited) Session:
Organizer of the Session:
How Did you learn about congress:
IP ADDRESS: 220.225.214.2
