{"title":"利用遥感和地理信息系统建立查谟和克什米尔多达-基什特瓦尔-兰班(DKR)地区的滑坡易发性模型","authors":"Ajay Kumar Taloor, Abid Abraham, Gurnam Parsad","doi":"10.1016/j.qsa.2024.100189","DOIUrl":null,"url":null,"abstract":"<div><p>The present study represents a significant understanding, employing cutting-edge Remote Sensing (RS) and Geographic Information System (GIS) technologies by conducting a comprehensive landslide susceptibility modelling in the Doda, Kishtwar, and Ramban (DKR) districts of the Union Territory of the Jammu and Kashmir in the NW Himalaya. The primary objective of this study is to determine the areas that are at high risk of landslides and accordingly classified these risk zones into five distinct categories, ranging from very high (VH) to very low (VL) susceptibility. To achieve this, a multifaceted approach, involving the utilization of various terrain thematic layers in the GIS environment was applied. The preferred framework employed in this study is the Weighted Overlay (WO) analysis. The final outcome of the study is the final landslide susceptibility map which is a significant and valuable resource for a wide range of stakeholders, including decision-makers, land managers, and local communities. It equips these stakeholders with the information and insights required to adopt proactive strategies in response to the identified landslide susceptibility zones.</p></div>","PeriodicalId":34142,"journal":{"name":"Quaternary Science Advances","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666033424000273/pdfft?md5=9198c6b76a153544d158c39cd53eaf12&pid=1-s2.0-S2666033424000273-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Landslide susceptibility modelling in the Doda Kishtwar Ramban (DKR) region of Jammu and Kashmir using Remote Sensing and Geographic Information System\",\"authors\":\"Ajay Kumar Taloor, Abid Abraham, Gurnam Parsad\",\"doi\":\"10.1016/j.qsa.2024.100189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>The present study represents a significant understanding, employing cutting-edge Remote Sensing (RS) and Geographic Information System (GIS) technologies by conducting a comprehensive landslide susceptibility modelling in the Doda, Kishtwar, and Ramban (DKR) districts of the Union Territory of the Jammu and Kashmir in the NW Himalaya. The primary objective of this study is to determine the areas that are at high risk of landslides and accordingly classified these risk zones into five distinct categories, ranging from very high (VH) to very low (VL) susceptibility. To achieve this, a multifaceted approach, involving the utilization of various terrain thematic layers in the GIS environment was applied. The preferred framework employed in this study is the Weighted Overlay (WO) analysis. The final outcome of the study is the final landslide susceptibility map which is a significant and valuable resource for a wide range of stakeholders, including decision-makers, land managers, and local communities. It equips these stakeholders with the information and insights required to adopt proactive strategies in response to the identified landslide susceptibility zones.</p></div>\",\"PeriodicalId\":34142,\"journal\":{\"name\":\"Quaternary Science Advances\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-04-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S2666033424000273/pdfft?md5=9198c6b76a153544d158c39cd53eaf12&pid=1-s2.0-S2666033424000273-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Quaternary Science Advances\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2666033424000273\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOGRAPHY, PHYSICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Quaternary Science Advances","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2666033424000273","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOGRAPHY, PHYSICAL","Score":null,"Total":0}
Landslide susceptibility modelling in the Doda Kishtwar Ramban (DKR) region of Jammu and Kashmir using Remote Sensing and Geographic Information System
The present study represents a significant understanding, employing cutting-edge Remote Sensing (RS) and Geographic Information System (GIS) technologies by conducting a comprehensive landslide susceptibility modelling in the Doda, Kishtwar, and Ramban (DKR) districts of the Union Territory of the Jammu and Kashmir in the NW Himalaya. The primary objective of this study is to determine the areas that are at high risk of landslides and accordingly classified these risk zones into five distinct categories, ranging from very high (VH) to very low (VL) susceptibility. To achieve this, a multifaceted approach, involving the utilization of various terrain thematic layers in the GIS environment was applied. The preferred framework employed in this study is the Weighted Overlay (WO) analysis. The final outcome of the study is the final landslide susceptibility map which is a significant and valuable resource for a wide range of stakeholders, including decision-makers, land managers, and local communities. It equips these stakeholders with the information and insights required to adopt proactive strategies in response to the identified landslide susceptibility zones.