外文翻译--以gis为基础的煤矿开采沉陷危机分析

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1、翻译部分英文原文SensitivityanalysisfortheGIS-basedmappingofthegroundsubsidencehazardnearabandonedundergroundcoalminesAbstractGroundsubsidencearoundabandonedunder-groundcoalminescancausemuchlossoflifeandprop-erty.WeanalyzefactorsthatcanaffectgroundsubsidencearoundabandonedminesinJeongahminKangwon-

2、dobysensitivityanalysisingeographicinformationsystem(GIS).Spatialdataforthesubsidencearea,topographyandgeologyandvariousgroundengineeringdatawerecol-lectedandusedtomakeafactorrasterdatabaseforagroundsubsidencehazardmap.Todeterminetheimpor-tanceofextractedsubsidence-relatedfactors,frequenc

3、yratiomodelandsensitivityanalysiswereemployed.Sen-sitivityanalysisisamethodforcomparingthecombinedeffectsofallfactorsexceptone.Sensitivityanalysisanditsverificationshowedthatusingallfactorsprovided91.61%accuracy.Thebestaccuracywasachievedbynotconsid-eringthegroundwaterdepth(92.77%)andthew

4、orstbynotconsideringthelineament(85.42%).Theresultsshowthatthedistancefromthelineamentandthedistancefromthedrifthighlyaffectedtheoccurrenceofgroundsubsidence,andthegroundwaterdepth,landuseandrockmassratinghadtheleasteffects.Thus,wedeterminedcausesofgroundsubsidenceinthestudyareaandthisinf

5、ormationcouldhelpinthepredictionofgroundsubsidenceinotherareas.KeywordsGISAbandonedundergroundcoalmineGroundsubsidenceFrequencyratioSensitivityanalysisKoreaIntroductionCoalindustryhasplayedamajorroleinthedevelopmentoftheKoreaneconomysincethe1960s.However,thecoalindustrybegantodeclinefromt

6、heendofthe1980sbecausetheoilpricefellglobally.Therewere173coalminesin1988inJeongseon,Kangwon-do,thelargestcoalminingregioninKorea.However,valuelesscoalmineswereabandonedaftertheimplementationofcoalindustryrationalizationactionbyKoreangovernment.Today,nocoalminesareinoperation.Intheabandon

7、edcoalminesinJeongseon,environmentalpollution,havingneverbeenconsideredafutureproblematthetimetheminesceasedoperating,isontheincrease.Heavymetalsinwastewaterfromcoalminesandmuckreachingriversandsoilisaseriousproblem.Inparticular,mostabandonedcoalminesareinmountainra