Landslide is defined as a slow to rapid downward movement of instable rock and debris masses under the action of gravity. Landslides are one of the major natural hazards that account for hundreds of lives besides enormous damage to properties and blocking the communication links every year. The area chosen in the present study is Uttarkashi district of Uttarakhand, suffering from frequent landslides every year. Present study focused on the possible factors that are responsible for the landslide in hilly regions of Uttarakashi, Uttarakhand. In present study we used the already existing topographical maps, satellite imageries and field work. Integrated them together using GIS and soft computing to create a database that will generate the output for the future use for prediction of susceptibility of landslide. The main aim of present study is to integrate the result of our study with spatial data, soil parameters, land inventory and used the output as a user friendly application using GIS which could predict the future susceptibility of region to landslide and% contribution of each factor for the same. In this study, layers are evaluated with the help of stability studies used to produce landslide susceptibility map by Artificial Neural Network (ANN). ArcGIS 9.3, ERDAS and Excel software have been used for zonation, and statistical analysis respectively. Database of this information layer is used to train, test, and validate the ANN model. A three-layered ANN with an input layer, two hidden layers, and one output layer is found to be optimal. Finally, an overlay analysis will be carried out by evaluating the layers obtained according to their accepted coefficient in final model.. Efficiency of the application will be calculated by the help of previously acquired data of the study area at different places and then the reliability of the application will be judged.
| Published in | American Journal of Neural Networks and Applications (Volume 3, Issue 6) |
| DOI | 10.11648/j.ajnna.20170306.12 |
| Page(s) | 63-74 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2018. Published by Science Publishing Group |
India, Uttarkashi, Landslide Susceptibility, Artificial Neural Network (ANN), GIS
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APA Style
Dilip Kumar, Neha lakhwan, Anita Rawat. (2018). Study and Prediction of Landslide in Uttarkashi, Uttarakhand, India Using GIS and ANN. American Journal of Neural Networks and Applications, 3(6), 63-74. https://doi.org/10.11648/j.ajnna.20170306.12
ACS Style
Dilip Kumar; Neha lakhwan; Anita Rawat. Study and Prediction of Landslide in Uttarkashi, Uttarakhand, India Using GIS and ANN. Am. J. Neural Netw. Appl. 2018, 3(6), 63-74. doi: 10.11648/j.ajnna.20170306.12
AMA Style
Dilip Kumar, Neha lakhwan, Anita Rawat. Study and Prediction of Landslide in Uttarkashi, Uttarakhand, India Using GIS and ANN. Am J Neural Netw Appl. 2018;3(6):63-74. doi: 10.11648/j.ajnna.20170306.12
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Download@article{10.11648/j.ajnna.20170306.12,
author = {Dilip Kumar and Neha lakhwan and Anita Rawat},
title = {Study and Prediction of Landslide in Uttarkashi, Uttarakhand, India Using GIS and ANN},
journal = {American Journal of Neural Networks and Applications},
volume = {3},
number = {6},
pages = {63-74},
doi = {10.11648/j.ajnna.20170306.12},
url = {https://doi.org/10.11648/j.ajnna.20170306.12},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajnna.20170306.12},
abstract = {Landslide is defined as a slow to rapid downward movement of instable rock and debris masses under the action of gravity. Landslides are one of the major natural hazards that account for hundreds of lives besides enormous damage to properties and blocking the communication links every year. The area chosen in the present study is Uttarkashi district of Uttarakhand, suffering from frequent landslides every year. Present study focused on the possible factors that are responsible for the landslide in hilly regions of Uttarakashi, Uttarakhand. In present study we used the already existing topographical maps, satellite imageries and field work. Integrated them together using GIS and soft computing to create a database that will generate the output for the future use for prediction of susceptibility of landslide. The main aim of present study is to integrate the result of our study with spatial data, soil parameters, land inventory and used the output as a user friendly application using GIS which could predict the future susceptibility of region to landslide and% contribution of each factor for the same. In this study, layers are evaluated with the help of stability studies used to produce landslide susceptibility map by Artificial Neural Network (ANN). ArcGIS 9.3, ERDAS and Excel software have been used for zonation, and statistical analysis respectively. Database of this information layer is used to train, test, and validate the ANN model. A three-layered ANN with an input layer, two hidden layers, and one output layer is found to be optimal. Finally, an overlay analysis will be carried out by evaluating the layers obtained according to their accepted coefficient in final model.. Efficiency of the application will be calculated by the help of previously acquired data of the study area at different places and then the reliability of the application will be judged.},
year = {2018}
}
TY - JOUR T1 - Study and Prediction of Landslide in Uttarkashi, Uttarakhand, India Using GIS and ANN AU - Dilip Kumar AU - Neha lakhwan AU - Anita Rawat Y1 - 2018/01/22 PY - 2018 N1 - https://doi.org/10.11648/j.ajnna.20170306.12 DO - 10.11648/j.ajnna.20170306.12 T2 - American Journal of Neural Networks and Applications JF - American Journal of Neural Networks and Applications JO - American Journal of Neural Networks and Applications SP - 63 EP - 74 PB - Science Publishing Group SN - 2469-7419 UR - https://doi.org/10.11648/j.ajnna.20170306.12 AB - Landslide is defined as a slow to rapid downward movement of instable rock and debris masses under the action of gravity. Landslides are one of the major natural hazards that account for hundreds of lives besides enormous damage to properties and blocking the communication links every year. The area chosen in the present study is Uttarkashi district of Uttarakhand, suffering from frequent landslides every year. Present study focused on the possible factors that are responsible for the landslide in hilly regions of Uttarakashi, Uttarakhand. In present study we used the already existing topographical maps, satellite imageries and field work. Integrated them together using GIS and soft computing to create a database that will generate the output for the future use for prediction of susceptibility of landslide. The main aim of present study is to integrate the result of our study with spatial data, soil parameters, land inventory and used the output as a user friendly application using GIS which could predict the future susceptibility of region to landslide and% contribution of each factor for the same. In this study, layers are evaluated with the help of stability studies used to produce landslide susceptibility map by Artificial Neural Network (ANN). ArcGIS 9.3, ERDAS and Excel software have been used for zonation, and statistical analysis respectively. Database of this information layer is used to train, test, and validate the ANN model. A three-layered ANN with an input layer, two hidden layers, and one output layer is found to be optimal. Finally, an overlay analysis will be carried out by evaluating the layers obtained according to their accepted coefficient in final model.. Efficiency of the application will be calculated by the help of previously acquired data of the study area at different places and then the reliability of the application will be judged. VL - 3 IS - 6 ER -
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