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Study on the Identification and Classification of Key Influencing Factors of Debris-Flow-Prone Areas in Liaoning Province Based on Self-organizing Clustering and Sensitivity Analysis
Due to the characteristics of sudden occurrence, fast disaster speed, and severe damage, debris-flow disasters can easily result in the loss of human lives and cause serious damage to property and social infrastructure. In this study, taking the debris-flow events in Liaoning province from 1960 to 2...
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Published in: | Sustainability 2023-01, Vol.15 (1), p.412 |
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description | Due to the characteristics of sudden occurrence, fast disaster speed, and severe damage, debris-flow disasters can easily result in the loss of human lives and cause serious damage to property and social infrastructure. In this study, taking the debris-flow events in Liaoning province from 1960 to 2020 as the study period, the natural geographical characteristics and key influencing factors of the debris-flow-prone areas were explored utilizing the self-organization mapping clustering method and nonlinear global sensitivity analysis. The main conclusions were as follows: (1) The key influencing factors of debris flow are the content of clay, sand, and silt; the first type of debris flow is sensitive to the fluctuation in slope and elevation; the second and third types of debris flows are more significantly affected by changes in land use and geomorphology; the third type of debris flow is weakly sensitive the NDVI value, vegetation type, slope direction, and soil type; (2) The first type of debris flow was widely distributed, mainly located in most of the hills of eastern and the southwest part of Liaoning province; the focus of the second type of debris flow focus was further in Xiuyan County and scattered in the hills of northeast Liaoning province; the third type of debris flow was mainly distributed on the peninsula of Liaodong and the southwest of Liaoning province. (3) When the clay content is 12–27%, sand content is 49–70%, silt content is 18–29%, the elevation is 0–500 m, the slope is 0°–30°, and the land use is at the junction of arable land, medium cover grassland, and forested land, etc., debris flow disasters are very likely to occur. |
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In this study, taking the debris-flow events in Liaoning province from 1960 to 2020 as the study period, the natural geographical characteristics and key influencing factors of the debris-flow-prone areas were explored utilizing the self-organization mapping clustering method and nonlinear global sensitivity analysis. The main conclusions were as follows: (1) The key influencing factors of debris flow are the content of clay, sand, and silt; the first type of debris flow is sensitive to the fluctuation in slope and elevation; the second and third types of debris flows are more significantly affected by changes in land use and geomorphology; the third type of debris flow is weakly sensitive the NDVI value, vegetation type, slope direction, and soil type; (2) The first type of debris flow was widely distributed, mainly located in most of the hills of eastern and the southwest part of Liaoning province; the focus of the second type of debris flow focus was further in Xiuyan County and scattered in the hills of northeast Liaoning province; the third type of debris flow was mainly distributed on the peninsula of Liaodong and the southwest of Liaoning province. (3) When the clay content is 12–27%, sand content is 49–70%, silt content is 18–29%, the elevation is 0–500 m, the slope is 0°–30°, and the land use is at the junction of arable land, medium cover grassland, and forested land, etc., debris flow disasters are very likely to occur.</description><identifier>ISSN: 2071-1050</identifier><identifier>EISSN: 2071-1050</identifier><identifier>DOI: 10.3390/su15010412</identifier><language>eng</language><publisher>Basel: MDPI AG</publisher><subject>Agricultural land ; Analysis ; Arable land ; Clay ; Cluster analysis ; Clustering ; Detritus ; Disasters ; Elevation ; Emergency management ; Flow velocity ; Geological structures ; Geology ; Geomorphology ; Grasslands ; Hills ; Land use ; Methods ; Property damage ; Regression analysis ; Rivers ; Sand ; Sensitivity analysis ; Silt ; Soil research ; Sustainability ; Topography ; Variables ; Vegetation type ; Watersheds</subject><ispartof>Sustainability, 2023-01, Vol.15 (1), p.412</ispartof><rights>COPYRIGHT 2022 MDPI AG</rights><rights>2022 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 (https://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-c368t-44a33e97271e5b50817ced23f847364e168d0501491826cc0b569acfda640ec63</citedby><cites>FETCH-LOGICAL-c368t-44a33e97271e5b50817ced23f847364e168d0501491826cc0b569acfda640ec63</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.proquest.com/docview/2761217463/fulltextPDF?pq-origsite=primo$$EPDF$$P50$$Gproquest$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2761217463?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>314,777,781,25734,27905,27906,36993,44571,74875</link.rule.ids></links><search><creatorcontrib>Wang, Fei</creatorcontrib><creatorcontrib>Cao, Yongqiang</creatorcontrib><creatorcontrib>Fan, Shuaibang</creatorcontrib><creatorcontrib>Zhang, Ruoning</creatorcontrib><title>Study on the Identification and Classification of Key Influencing Factors of Debris-Flow-Prone Areas in Liaoning Province Based on Self-organizing Clustering and Sensitivity Analysis</title><title>Sustainability</title><description>Due to the characteristics of sudden occurrence, fast disaster speed, and severe damage, debris-flow disasters can easily result in the loss of human lives and cause serious damage to property and social infrastructure. In this study, taking the debris-flow events in Liaoning province from 1960 to 2020 as the study period, the natural geographical characteristics and key influencing factors of the debris-flow-prone areas were explored utilizing the self-organization mapping clustering method and nonlinear global sensitivity analysis. The main conclusions were as follows: (1) The key influencing factors of debris flow are the content of clay, sand, and silt; the first type of debris flow is sensitive to the fluctuation in slope and elevation; the second and third types of debris flows are more significantly affected by changes in land use and geomorphology; the third type of debris flow is weakly sensitive the NDVI value, vegetation type, slope direction, and soil type; (2) The first type of debris flow was widely distributed, mainly located in most of the hills of eastern and the southwest part of Liaoning province; the focus of the second type of debris flow focus was further in Xiuyan County and scattered in the hills of northeast Liaoning province; the third type of debris flow was mainly distributed on the peninsula of Liaodong and the southwest of Liaoning province. (3) When the clay content is 12–27%, sand content is 49–70%, silt content is 18–29%, the elevation is 0–500 m, the slope is 0°–30°, and the land use is at the junction of arable land, medium cover grassland, and forested land, etc., debris flow disasters are very likely to occur.</description><subject>Agricultural land</subject><subject>Analysis</subject><subject>Arable land</subject><subject>Clay</subject><subject>Cluster analysis</subject><subject>Clustering</subject><subject>Detritus</subject><subject>Disasters</subject><subject>Elevation</subject><subject>Emergency management</subject><subject>Flow velocity</subject><subject>Geological structures</subject><subject>Geology</subject><subject>Geomorphology</subject><subject>Grasslands</subject><subject>Hills</subject><subject>Land use</subject><subject>Methods</subject><subject>Property damage</subject><subject>Regression analysis</subject><subject>Rivers</subject><subject>Sand</subject><subject>Sensitivity analysis</subject><subject>Silt</subject><subject>Soil research</subject><subject>Sustainability</subject><subject>Topography</subject><subject>Variables</subject><subject>Vegetation type</subject><subject>Watersheds</subject><issn>2071-1050</issn><issn>2071-1050</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><recordid>eNpVkcFu1DAQhiMEElXphSewxAmktJ44sZPjsrB0xUogFs6R1xkvrlK7eJxCeDCeD0eLVGofPPr9_TOjmaJ4CfxSiI5f0QQNB15D9aQ4q7iCEnjDn_4XPy8uiG54PkJAB_Ks-LNP0zCz4Fn6jmw7oE_OOqOTy5L2A1uPmuhBCpZ9xJltvR0n9Mb5I9tok0Kk5esdHqKjcjOGn-XnGDyyVURNzHm2czr4Bc_6vfMG2VtNOCyV9zjaMsSj9u73QqzHiRLGJVw62KMnl9y9SzNbeT3O5OhF8czqkfDi33tefNu8_7q-LnefPmzXq11phGxTWddaCOxUpQCbQ8NbUAaHSti2VkLWCLId8lig7qCtpDH80MhOGztoWXM0UpwXr05572L4MSGl_iZMMTdBfaUkVKBqKTJ1eaKOesTeeRtS1CbfAW-dyWOwLusrVSvoOlCL4fUjQ2YS_kpHPRH12_2Xx-ybE2tiIIpo-7vobnWce-D9svf-Ye_iL-Y_oJs</recordid><startdate>20230101</startdate><enddate>20230101</enddate><creator>Wang, Fei</creator><creator>Cao, Yongqiang</creator><creator>Fan, Shuaibang</creator><creator>Zhang, Ruoning</creator><general>MDPI AG</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>4U-</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope></search><sort><creationdate>20230101</creationdate><title>Study on the Identification and Classification of Key Influencing Factors of Debris-Flow-Prone Areas in Liaoning Province Based on Self-organizing Clustering and Sensitivity Analysis</title><author>Wang, Fei ; Cao, Yongqiang ; Fan, Shuaibang ; Zhang, Ruoning</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c368t-44a33e97271e5b50817ced23f847364e168d0501491826cc0b569acfda640ec63</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Agricultural land</topic><topic>Analysis</topic><topic>Arable land</topic><topic>Clay</topic><topic>Cluster analysis</topic><topic>Clustering</topic><topic>Detritus</topic><topic>Disasters</topic><topic>Elevation</topic><topic>Emergency management</topic><topic>Flow velocity</topic><topic>Geological structures</topic><topic>Geology</topic><topic>Geomorphology</topic><topic>Grasslands</topic><topic>Hills</topic><topic>Land use</topic><topic>Methods</topic><topic>Property damage</topic><topic>Regression analysis</topic><topic>Rivers</topic><topic>Sand</topic><topic>Sensitivity analysis</topic><topic>Silt</topic><topic>Soil research</topic><topic>Sustainability</topic><topic>Topography</topic><topic>Variables</topic><topic>Vegetation type</topic><topic>Watersheds</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wang, Fei</creatorcontrib><creatorcontrib>Cao, Yongqiang</creatorcontrib><creatorcontrib>Fan, Shuaibang</creatorcontrib><creatorcontrib>Zhang, Ruoning</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><collection>University Readers</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>AUTh Library subscriptions: ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><jtitle>Sustainability</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wang, Fei</au><au>Cao, Yongqiang</au><au>Fan, Shuaibang</au><au>Zhang, Ruoning</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Study on the Identification and Classification of Key Influencing Factors of Debris-Flow-Prone Areas in Liaoning Province Based on Self-organizing Clustering and Sensitivity Analysis</atitle><jtitle>Sustainability</jtitle><date>2023-01-01</date><risdate>2023</risdate><volume>15</volume><issue>1</issue><spage>412</spage><pages>412-</pages><issn>2071-1050</issn><eissn>2071-1050</eissn><abstract>Due to the characteristics of sudden occurrence, fast disaster speed, and severe damage, debris-flow disasters can easily result in the loss of human lives and cause serious damage to property and social infrastructure. In this study, taking the debris-flow events in Liaoning province from 1960 to 2020 as the study period, the natural geographical characteristics and key influencing factors of the debris-flow-prone areas were explored utilizing the self-organization mapping clustering method and nonlinear global sensitivity analysis. The main conclusions were as follows: (1) The key influencing factors of debris flow are the content of clay, sand, and silt; the first type of debris flow is sensitive to the fluctuation in slope and elevation; the second and third types of debris flows are more significantly affected by changes in land use and geomorphology; the third type of debris flow is weakly sensitive the NDVI value, vegetation type, slope direction, and soil type; (2) The first type of debris flow was widely distributed, mainly located in most of the hills of eastern and the southwest part of Liaoning province; the focus of the second type of debris flow focus was further in Xiuyan County and scattered in the hills of northeast Liaoning province; the third type of debris flow was mainly distributed on the peninsula of Liaodong and the southwest of Liaoning province. (3) When the clay content is 12–27%, sand content is 49–70%, silt content is 18–29%, the elevation is 0–500 m, the slope is 0°–30°, and the land use is at the junction of arable land, medium cover grassland, and forested land, etc., debris flow disasters are very likely to occur.</abstract><cop>Basel</cop><pub>MDPI AG</pub><doi>10.3390/su15010412</doi><oa>free_for_read</oa></addata></record> |
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subjects | Agricultural land Analysis Arable land Clay Cluster analysis Clustering Detritus Disasters Elevation Emergency management Flow velocity Geological structures Geology Geomorphology Grasslands Hills Land use Methods Property damage Regression analysis Rivers Sand Sensitivity analysis Silt Soil research Sustainability Topography Variables Vegetation type Watersheds |
title | Study on the Identification and Classification of Key Influencing Factors of Debris-Flow-Prone Areas in Liaoning Province Based on Self-organizing Clustering and Sensitivity Analysis |
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