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Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A Case Study in Kullu Valley, Himalayas
Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool...
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Published in: | Geosciences (Basel) 2019-08, Vol.9 (8), p.360 |
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description | Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region. |
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The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.</description><identifier>ISSN: 2076-3263</identifier><identifier>EISSN: 2076-3263</identifier><identifier>DOI: 10.3390/geosciences9080360</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Accuracy ; ALOS-PALSAR ; ASTER ; ASTER (radiometer) ; Digital Elevation Models ; Earth science ; Elevation ; frequency ratio (FR) ; Geographic information systems ; Geological hazards ; Geology ; Global positioning systems ; GPS ; landslide susceptibility mapping (LSM) ; Landslides ; Landslides & mudslides ; Lithology ; Mapping ; Mitigation ; Mountain regions ; natural hazards ; Phased arrays ; Physiographic features ; Positioning systems ; Probability theory ; Radar ; Radiometers ; Regions ; Resolution ; SAR (radar) ; Satellite observation ; Spatial discrimination ; Spatial distribution ; Spatial resolution ; SRTM ; Synthetic aperture radar ; Thermal emission ; Topography ; Valleys</subject><ispartof>Geosciences (Basel), 2019-08, Vol.9 (8), p.360</ispartof><rights>2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-a408t-adcf17c7c203037f443ac1ae57f4fdf90a3fe864fd3f6ee26d078398e14547d33</citedby><cites>FETCH-LOGICAL-a408t-adcf17c7c203037f443ac1ae57f4fdf90a3fe864fd3f6ee26d078398e14547d33</cites><orcidid>0000-0001-6175-6491</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2548494134/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2548494134?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,780,784,25753,27924,27925,37012,44590,75126</link.rule.ids></links><search><creatorcontrib>Meena, Sansar Raj</creatorcontrib><creatorcontrib>Gudiyangada Nachappa, Thimmaiah</creatorcontrib><title>Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A Case Study in Kullu Valley, Himalayas</title><title>Geosciences (Basel)</title><description>Landslides are one of the most damaging geological hazards in mountainous regions such as the Himalayas. The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.</description><subject>Accuracy</subject><subject>ALOS-PALSAR</subject><subject>ASTER</subject><subject>ASTER (radiometer)</subject><subject>Digital Elevation Models</subject><subject>Earth science</subject><subject>Elevation</subject><subject>frequency ratio (FR)</subject><subject>Geographic information systems</subject><subject>Geological hazards</subject><subject>Geology</subject><subject>Global positioning systems</subject><subject>GPS</subject><subject>landslide susceptibility mapping (LSM)</subject><subject>Landslides</subject><subject>Landslides & mudslides</subject><subject>Lithology</subject><subject>Mapping</subject><subject>Mitigation</subject><subject>Mountain regions</subject><subject>natural hazards</subject><subject>Phased arrays</subject><subject>Physiographic features</subject><subject>Positioning systems</subject><subject>Probability theory</subject><subject>Radar</subject><subject>Radiometers</subject><subject>Regions</subject><subject>Resolution</subject><subject>SAR (radar)</subject><subject>Satellite observation</subject><subject>Spatial discrimination</subject><subject>Spatial distribution</subject><subject>Spatial resolution</subject><subject>SRTM</subject><subject>Synthetic aperture radar</subject><subject>Thermal emission</subject><subject>Topography</subject><subject>Valleys</subject><issn>2076-3263</issn><issn>2076-3263</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNplUU1rGzEQXUoLDUn-QE-CXutW0sj70Vtwk9rEodC0vYqxNDIyymq70gb2nh8eJS4h0LnM483w3jCvqj4I_hmg41_2FJPx1BtKHW851PxNdSJ5Uy9A1vD2FX5fnad04KU6AS2ok-phczegySw6djtg9hjYT0oxTNnH_on95vc-F_Yy0D0-kzfRUmAFbLG3KXhL7HZKhobsdz74PLMbHAbf77-yC7bCVMZ5sjPzPbueQpjYHwyB5k9s7e8w4IzprHrnMCQ6_9dPq99Xl79W68X2x_fN6mK7QMXbvEBrnGhMYyQHDo1TCtAIpGWBzrqOIzhq64LB1USytrxpoWtJqKVqLMBptTnq2ogHPYzFf5x1RK-fiTjuNY7Zm0BaQANCLB3suFOtpF1XTISwEsov650sWh-PWsMY_06Usj7EaezL-VouVas6JUCVLXncMmNMaST34iq4fgpP_x8ePALbfY_h</recordid><startdate>20190801</startdate><enddate>20190801</enddate><creator>Meena, Sansar Raj</creator><creator>Gudiyangada Nachappa, Thimmaiah</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7TN</scope><scope>7UA</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>BKSAR</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>F1W</scope><scope>GNUQQ</scope><scope>H96</scope><scope>HCIFZ</scope><scope>KL.</scope><scope>L.G</scope><scope>PATMY</scope><scope>PCBAR</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PYCSY</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0001-6175-6491</orcidid></search><sort><creationdate>20190801</creationdate><title>Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A Case Study in Kullu Valley, Himalayas</title><author>Meena, Sansar Raj ; 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The Himalayan region is, tectonically, the most active region in the world that is highly vulnerable to landslides and associated hazards. Landslide susceptibility mapping (LSM) is a useful tool for understanding the probability of the spatial distribution of future landslide regions. In this research, the landslide inventory datasets were collected during the field study of the Kullu valley in July 2018, and 149 landslide locations were collected as global positioning system (GPS) points. The present study evaluates the LSM using three different spatial resolution of the digital elevation model (DEM) derived from three different sources. The data-driven traditional frequency ratio (FR) model was used for this study. The FR model was used for this research to assess the impact of the different spatial resolution of DEMs on the LSM. DEM data was derived from Advanced Land Observing Satellite-1 (ALOS) Phased Array type L-band Synthetic Aperture Radar (PALSAR) ALOS-PALSAR for 12.5 m, the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global for 30 m, and the Shuttle Radar Topography Mission (SRTM) for 90 m. As an input, we used eight landslide conditioning factors based on the study area and topographic features of the Kullu valley in the Himalayas. The ASTER-Global 30m DEM showed higher accuracy of 0.910 compared to 0.839 for 12.5 m and 0.824 for 90 m DEM resolution. This study shows that that 30 m resolution is better suited for LSM for the Kullu valley region in the Himalayas. The LSM can be used for mitigation and future planning for spatial planners and developmental authorities in the region.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/geosciences9080360</doi><orcidid>https://orcid.org/0000-0001-6175-6491</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Accuracy ALOS-PALSAR ASTER ASTER (radiometer) Digital Elevation Models Earth science Elevation frequency ratio (FR) Geographic information systems Geological hazards Geology Global positioning systems GPS landslide susceptibility mapping (LSM) Landslides Landslides & mudslides Lithology Mapping Mitigation Mountain regions natural hazards Phased arrays Physiographic features Positioning systems Probability theory Radar Radiometers Regions Resolution SAR (radar) Satellite observation Spatial discrimination Spatial distribution Spatial resolution SRTM Synthetic aperture radar Thermal emission Topography Valleys |
title | Impact of Spatial Resolution of Digital Elevation Model on Landslide Susceptibility Mapping: A Case Study in Kullu Valley, Himalayas |
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