Quantitative Remote Sensing of Land Surfaces

ProcessingthevastamountsofdataontheEarth'slandsurfaceenvironmentgeneratedbyNASA'sandotherinternationalsatelliteprogramsisasignificantchallenge.Fillingagapbetweenthetheoretical,physically-basedmodellingandspecificapplications,thisin-depthstudypresentspracticalquantitativealgorithmsforestimatingvariouslandsurfacevariablesfromremotelysensedobservations.Aconcisereviewofthebasicprinciplesofopticalremotesensingaswellaspracticalalgorithmsforestimatinglandsurfacevariablesquantitativelyfromremotelysensedobservations.EmphasizesboththebasicprinciplesofopticalremotesensingandpracticalalgorithmsforestimatinglandsurfacevariablesquantitativelyfromremotelysensedobservationsPresentsthecurrentphysicalunderstandingofremotesensingasasystemwithafocusonradiativetransfermodellingoftheatmosphere,canopy,soilandsnowGathersthestateoftheartquantitativealgorithmsforsensorcalibration,atmosphericandtopographiccorrection,estimationofavarietyofbiophysicalandgeophysicalvariables,andfour-dimensionaldataassimilation,