多尺度土地资源配置研究(6)
发布时间:2021-06-07
发布时间:2021-06-07
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WiththerapideconomicdevelopmentinChina,Urbanizationhasbecome
useallirreversibletrendofsocialdevelopment.Inthisprocess,people’Srequirementofland
growing,theincreasinglyintensifiedcontradiction
economicandenvironmentalspaceandlandproductsisalsobetweenpeopleandorlandledtomanysocial,issues,and
asmayresultinthedisappearancefragmentationofhabitat,thereductioninbiodiversity
theseecologicalproblems
awellastheweakeningofecosystemservices.Howtorespondtointegratethemintoandpolicy,planningandprojectdecision-makingprocesshasbecome
allocationofhotspotofresearch.Therefore,thispaperdealtwithmulti-scaleoptimalunderconsiderationofinfluencingfactorswithvariousscalelandresourceslandusepattern,takingrepresentativeblocksofYubeidistrict,LongxingtownandHeyanvillageetc.forexample.Thisstudywouldenrichandimprovelandqualityassessmentsystembyanatomizingsimilaritiesanddifferencesofmulti—scalelandqualityinhilly-landregions.Theresearchwill
development.improvethesystemofland
1.Landuseoptimizationinthecontextofruralandurbanresourcesdispositionatcountyscale
ThisresearchmakesthetownshipofYubeidistrictinChongqmgasbasiczoningunitstoestablishCO-ordinatedevelopinglandusemainfunctionzoning.Firstofall,weconstructtheindexsystemaccordingtocertainprinciples,andtheindexdataderivefrom“ChongqingStatisticalYearbook”,“YubeiStatistical
wehandleYearbook'’and“ChongqingStatisticalYearbookofLandandResources”.Then,useandselecttheindicatorbyprincipalcomponentanalysis.FinallyweclusteranalysisforlandusemainfunctionzoninginYubeidistrict.
(1)TheprincipalcomponentanalysisCanscientificallyandreasonablyrefinezoningindex.Thisstudyselected15primaryindicatorsfromeconomicdevelopment,socialprogressandenvironmental
analysis,So
aProtectionwhichistodealwithdimension reductiontreatmentbyprincipalcomponentWeCangetlesscomprehensiveindextoreplacetheoriginalvariableindicatorwhichisfewmore.
Therefore,wechose9indicatorssuchas‘'theFinancialrevenue”.‘'theperunitareayieldofgrain’’and“forest
countyarea'’toconstitutethecomprehensiveevaluationsystemofmainfunctionzoningatscale.Theseindicatorsnotonlyreflecttherepresentativenessandaccuracyofthelanduseoriginalinformation,butalsoeffectivelyreducetheworkloadandimprovethezoningprecision.
wellasthe(2)ThecomparisonofresultsfromK—meansclusterandhierarchicalclusteras
verificationofSinglefactorANOVAanalysis
moreanddiscriminantanalysismakethezoningresultsuseaccurate.Weconstitute19x19fuzzysimilarmatrixbased9selectedindicatorstoK.meansclusterandhierarchicalclusterbydifferentcriterion.WefoundthezoningresultsfromeachmethodweresimilarexcepttheMuertown.Intheone-tailedANOVAanalysistableonlytheindex“ruralperV