Improved Landslide Susceptibility mapping using statistical MLR model
Author:
Affiliation:
1. Indian Institute of Technology (IIT)-Mandi,School of Civil and Environmental Engineering (SCENE),Himachal Pradesh,India
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10064385/10064489/10064594.pdf?arnumber=10064594
Reference16 articles.
1. Landslide susceptibility maps comparing frequency ratio and artificial neural networks: a case study from the Nepal Himalaya
2. A Comparison of Image-Based and Physics-Based Atmospheric Correction Methods for Extracting Snow and Vegetation Cover in Nepal Himalayas Using Landsat 8 OLI Images
3. Landslide susceptibility mapping in a part of Uttarkashi district (India) by multiple linear regression method;onagh;Int J Geol Earth Environ Sci,2012
4. Calculating the vegetation index faster
5. ANALYSIS OF LANDSLIDE REACTIVATION USING SATELLITE DATA: A CASE STUDY OF KOTRUPI LANDSLIDE, MANDI, HIMACHAL PRADESH, INDIA
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1. Effect of the Normalized Difference Vegetation Index (NDVI) on GIS-Enabled Bivariate and Multivariate Statistical Models for Landslide Susceptibility Mapping;Journal of the Indian Society of Remote Sensing;2023-07-28
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