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1、ThispageintentionallyleftblankMACHINELEARNINGMETHODSINTHEENVIRONMENTALSCIENCESNeuralNetworksandKernelsWilliamW.HsiehMachinelearningmethods,havingoriginatedfromcomputationalintelligence(i.e.artiÞcialintelligence),arenowubiquitousintheenvironmentalsciences.ThisistheÞ
2、rstsingle-authoredtextbooktogiveauniÞedtreatmentofmachinelearningmethodsandtheirapplicationsintheenvironmentalsciences.MachinelearningmethodsbegantoinÞltratetheenvironmentalsciencesinthe1990s.Today,thankstotheirpowerfulnonlinearmodellingcapability,theyarenolongeran
3、exoticfringespecies,astheyareheavilyusedinsatellitedataprocessing,ingeneralcirculationmodels(GCM),inweatherandclimateprediction,airqual-ityforecasting,analysisandmodellingofenvironmentaldata,oceanographicandhydrologicalforecasting,ecologicalmodelling,andinthemonito
4、ringofsnow,iceandforests,etc.End-of-chapterreviewquestionsareincluded,allowingreaderstodeveloptheirproblem-solvingskillsandmonitortheirunderstandingofthemate-rialpresented.Anappendixlistswebsitesavailablefordownloadingcomputercodeanddatasources.Aresourceswebsiteisa
5、vailablecontainingdatasetsforexercises,andadditionalmaterialtokeepthebookcompletelyup-to-date.Thisbookpresentsmachinelearningmethodsandtheirapplicationsintheenvironmentalsciences(includingsatelliteremotesensing,atmosphericscience,climatescience,oceanography,hydrolo
6、gyandecology),writtenatalevelsuitableforbeginninggraduatestudentsandadvancedundergraduates.Itisalsovaluableforresearchersandpractitionersinenvironmentalsciencesinterestedinapplyingthesenewmethodstotheirownwork.WILLIAMW.HSIEHisaProfessorintheDepartmentofEarthandOcea
7、nSci-encesandintheDepartmentofPhysicsandAstronomy,aswellasChairoftheAtmosphericScienceProgramme,attheUniversityofBritishColumbia.Heisinternationallyknownforhispioneeringworkindevelopingandapply-ingmachinelearningmethodsintheenvironmentalsciences.Hehaspublishedover8
8、0peer-reviewedjournalpublicationscoveringareasofclimatevariability,machinelearning,oceanography,atmosphericscienceandhydrology.MACHINELEARNINGMET
