简介：BPandRBFneuralnetworktopredictforeststockvolumewerestudied,butthestudyinevaluatingbothnetworks’applicationeffectswasnotconducted.Inordertofindahigherforecastprecision,morestrongapplicativemethod,thecomprehensiveanalysisandevaluationonthetwomethodswerecarriedoutinthepracticalapplication.Bythecorrelationanalysis,crowndensity,shady-slopeandsunny-slope,TM1,TM2,TM3,TM5,TM7,NDVI,TM,(4-3),TM4/3wereselectedasinputvariables,andtheforestvolumeofMiyunCountyasoutputvariables,RBFandBPneuralnetworkmodelsforforecastingtheforestvolumewereestablished.Andtheneuralnetworktrainingsteplength,trainingtime,predictionaccuracyandtheapplicabilitymodelofthetwomethodswerecomprehensivelyanalyzed.TheresultsshowthattheRBFneuralnetworkmodelissuperiortotheBPneuralnetworkmodel.

简介：Background:LeafAreaIndex(LAI)isanimportantparameterusedinmonitoringandmodelingofforestecosystems.Theaimofthisstudywastoevaluateperformanceoftheartificialneuralnetwork(ANN)modelstopredicttheLAIbycomparingtheregressionanalysismodelsastheclassicalmethodinthesepureandeven-agedCrimeanpineforeststands.Methods:OnehundredeighttemporarysampleplotswerecollectedfromCrimeanpineforeststandstoestimatestandparameters.EachsampleplotwasimagedwithhemisphericalphotographstodetecttheLAI.ThepartialcorrelationanalysiswasusedtoassesstherelationshipsbetweenthestandLAIvaluesandstandparameters,andthemultivariatelinearregressionanalysiswasusedtopredicttheLAIfromstandparameters.DifferentartificialneuralnetworkmodelscomprisingdifferentnumberofneuronandtransferfunctionsweretrainedandusedtopredicttheLAIofforeststands.Results:ThecorrelationcoefficientsbetweenLAIandstandparameters(standnumberoftrees,basalarea,thequadraticmeandiameter,standdensityandstandage)weresignificantatthelevelof0.01.Thestandage,numberoftrees,siteindex,andbasalareawereindependentparametersinthemostsuccessfulregressionmodelpredictedLAIvaluesusingstandparameters(/?;adj=0.5431).AscorrespondingmethodtopredicttheinteractionsbetweenthestandLAIvaluesandstandparameters,theneuralnetworkarchitecturebasedontheRBF4-19-1withGaussianactivationfunctioninhiddenlayerandtheidentityactivationfunctioninoutputlayerperformedbetterinpredictingLAI(SSE(12.1040),MSE(0.1223),RM5E(0.3497),AIC(0.1040),BIC(-777310)andR2(0.6392))comparedtotheotherstudiedtechniques.Conclusion:TheANNoutperformedthemultivariateregressiontechniquesinpredictingLAIfromstandparameters.TheANNmodels,developedinthisstudy,mayaidinmakingforestmanagementplanninginstudyforeststands.

简介：Basedonthecurrentstatusofnature,economyandsociety,andinthelightofinterconnectedpatternsofmaterial,energyandinformationflows,theForestEco-NetworkSysteminChina(CFENS)istobeestablishedtoharmonizesthedevelopmentofhuman,natureandsocietyinthiscountry,whichisofintegrity,multi-function,highefficiencyandoperability,andviewsthewholemainlandasanecosystemwithdifferentbigparchesconsistingofdifferenttypesofforests,grasslands,flelds,barrenhill...

简介：ChineseForestEcosystemResearchNetwork,estabfishedinlate1950'sanddirectlyconstructedandadministeredbytheScienceandTechnologyDepartmentofStateForestryAdministrationofChina,isalargeecologyresearchnetworkfocusesonlong-termecosystemfixed-observation.Itembodies15sitesthatrepresentdiverseecosystemsandresearchpriorities,including6state-levelsites.CFERNOfficecoordinatescommunications,networkpublications,andresearch-planningactivities.CFERNusestheadvancedgroundandspatialobservationtechnologiessuchasRS,GPS,GIStostudythestructure,functionallawsandfeedbackmechanismofChineseforestecosystem,aswellasitseffectsonChina'ssocialandeconomicdevelopment.ThemaintaskscarriedoutbyCFERNare:(1)constructionofthedatabaseonthestructureandfunctionsofChineseforestecosystemanditsecologicalenvironmentalfactors;(2)thedatabaseconstructionofforestresources,ecologicalenvironment,waterresourcesandrelatedsocialeconomyinbothregionalandnationalscales;(3)theestablishmentofanevaluationsystemofforestecologicaleffectsinChina'smaindrainageareas;(4)theestabfishmentofaforestenvironmentmonitoringnetworkandadynamicpredictionandalarmsystem.

简介：ＦＯＲＵＭＯＮ“ＷＯＭＥＮＡＮＤＳＯＣＩＡＬＦＯＲＥＳＴＲＹ”ＨＥＬＤＢＹＴＨＥＦＯＲＥＳＴＲＹＡＮＤＳＯＣＩＥＴＹＮＥＴＷＯＲＫ￥ＢｙＬｉＷｅｉｃｈａｎｇＡｆｏｒｕｍｏｎ＂ＷｏｍｅｎａｎｄＳｏｃｉａｌＦｏｒｅｓｔｒｙ＂ｗａｓｈｅｌｄａｔｔｈｅＩｎｓ...

简介：Urbanforestisanimportantcompositionandthewindowandsoulofmoderncities,whichhasacloserelationshipwithecologicalenvironmentandinvestingenvironment.SourbanforesthasbeenconstructedinChina.HuainingCountycouldholdofthehistoricalopportunityandcomeupwiththegreatblueprintofforestecologicalnetworksystemconstructionforthenewtown.Thispapermainlyintroducestheguidingideas,principles,goalsandoveralllayoutsoftheconstructioninthenewtown,andhopethatitwillbeamodelforothercounty-levelforestecologicalnetworksystemconstructioninChina.

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