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简介：Itisasharedopinionthatsustainabledevelopmentrequiresasystemdiscontinuity,meaningthatradicalchangesinthewayweproduceandconsumeareneeded.Withinthisframeworkthereisanemergingunderstandingthatanimportantcontributiontothischangecanbedirectlylinkedtodecisionstakeninthedesignphaseofproducts,servicesandsystems.DesignschoolshavethereforetobeabletoprovidedesignstudentswithabroadknowledgeandeffectiveDesignforSustainabilitytools,inordertoenableanewgenerationofdesignersinplayinganactiveroleinre-orientingourconsumptionandproductionpatterns.ThispaperpresentstheintermediateresultsoftheLeNSChina,theLearningNetworkonSustainabilityofChinesedesignHigherEducationInstitutionsaimingatcurriculadevelopmentonDesignforSustainability.TheprojectisaregenerationoftheLeNSAsian-Europeanmulti-polarnetworkprojectfinancedbytheEuropeanCommission.LeNSChinaistakinginconsiderationthelocalneeds,interestsandopportunitiescouldrepresentasignificantenablingplatformcapabletosensitise,supportandempoweranewgenerationofChinesedesigneducators,designersandentrepreneurstoreachdesignpracticethroughoutanopencollaborativelearningapproach.ThepaperwillfirstlyintroducetheLeNSprojectanditsethos,andthentheLeNSChinanetworkwillbedescribedintermsofthestateoftheartofdesignforsustainabilityanditseducationinChina,thescopeandtheobjective,theresultsachievedsofarandthenextsteps.

简介：IntegratedwithGISandremotesensing(RS)technology,asystematicanalysisanditsmethodologyforhuman-settlementssocialenvironmenthasbeenintroduced.Thismethodologyhasbeencalledspatialtrendfieldmodel(STFM).STFM'sapplicationhistoryinthefieldofhuman-settlementssocialenvironmenthasbeendiscussedatfirst.Then,someindexdatamodelshavebeencreatedthroughSTFM,whichincludepopulationdensitytrendfield,humanactivitystrengthtrendfield,city-townspatialdensitytrendfield,urbanizationratiotrendfield,roaddensitytrendfield,GDPspatialdensitytrendfieldandPER-GDPspatialdensitytrendfield.Withallabove-mentionedindexesasinputdata,throughIterativeSelf-OrganizingDataAnalysisTechniquesAlgorithm(ISODATA),thispapermakesaverificationstudyofChongqingmunicipality.TheresultofthecasestudyconfirmsthatSTFMmethodologyiscredibleandhashighefficiencyforregionalhuman-settlementsstudy.

简介：DevelopmentofcoastalecotourismhasbeenafocusofShandonggovernment,andthesuitabilityevaluationofregionalcoastalecotourismiscrucialforthereasonableplanandsustainabledevelopmentofShandongcoastalecotourism.ByusingMATLABlanguagetoestablishaSOMneuralnetworkmodel,thispaperevaluatesthecoastalecotourismsuitabilityoffourregions,Qingdao,Yantai,WeihaiandRizhaoofShandongProvinceanddivides33subordinateregionsofthosefourcitiesintofourcategories,i.e.regionspoorlysuitableforecotourismresources,regionshighlysuitableforcoastalecotourism,regionssecondlysuitableforcoastalecotourism,regionsordinarilysuitableforcoastalecotourism.Relatedsuggestionsondevelopmentofregionalcoastalecotourismhavebeengiveninthefinalconclusions.