Introduction To Satellite Remote Sensing
Introduction to SatelliteRemote SensingWilliam EmeryUniversity of Colorado at Boulder,Colorado, United StatesAdrianoCampsUniversitat Politecnica de Catalunya,Barcelona, SpainELSEVIER
ContentsCHAPTER 1The1.1History of Satellite Remote SensingThe Definition of Remote1.2.31.3CHAPTER 2The Future of1SensingLightDevelopmentEarth-Orbiting SatellitesThe Nature of1.2.2 The Birth of1Sensing1.2 The History of Satellite Remote1.2.11and thePolar-Orbitingof AerialPhotography16Satellites201.2.4 Other Historical Satellite Programs25Study Questions42Basic Electromagnetic Concepts and s432.2 The Basics ofElectromagneticRadiation432.3 The Remote Sensing Process442.4 The Character of Electromagnetic Waves462.4.146Definition of Radiometric Terms502.4.2 Polarization and the Stokes Vector2.4.3 Reflection and Refraction2.5atthe Interface of Two Flat MediaBrewster's Angle522.4.5Critical542.4.6Albedo Versus ReflectanceAngleElectromagnetic Spectrum:2.5.1Distribution of Radiant5555EnergiesGamma, X-Ray, and Ultraviolet Portions of the al Infrared60Visible2.5.4 MicrowaveSpectrum60Spectrum622.6 Atmospheric Transmission652.6.1 Spectral Windows2.6.2 Atmospheric2.7Sensors2.8Incoming SolartoEffects66Measure Parameters of the Earth's Surface69Radiation712.9 Infrared Emissions722.10 Surface Reflectance: Land Targets2.10.12.11522.4.47780Land Surface MixturesStudy Questions 81vii
viiiCONTENTSCHAPTER 33.1Optical Imaging Systems85PhysicalPrinciplesOptical Systems853.2.1 Prisms863.2.2 Filter-Wheel Radiometers873.2.392Measurement3.2 Basic86Grating Spectrometer3.2.4 Interferometer953.3Spectral Resolving 73.5 Vignetting1003.6 Scan Geometries1023.7 Field of View1083.8 Optical Sensor 93.8.2 Polarization Filters3.9LightDetection and3.9.1Physics113Ranging115of the Measurement1153.9.2 Optical and Technological Considerations1173.9.3118Applicationsof LIDARSystems3.9.4 Wind LIDAR1193.10 Study QuestionsCHAPTER 4125Microwave Radiometry4.1 Basic 131131Brightness Temperatureandfor theEmissivityEmissivity1354.1.4 Power CollectedbyanAntenna SurroundedbyaBlackbody4.1.5byanAntenna SurroundedbyaGray body:Power CollectedApparent Temperatureand AntennaTemperature4.2 The Radiative Transfer Equation4.2.1TheComplete4.2.2 UsualPolarimetric Radiative osphere145150Land Emission1564.3.4 Ocean Emission4.4138Ionosphere4.3.2 The4.3.3137140Equationto the Radiative Transfer4.3 Emission Behavior of Natural Surfaces134UnderstandingMicrowave169Radiometry Imagery1814.5 Applications of Microwave Radiometry1874.6 Sensors197
CONTENTS4.6.1Historical Review of Microwave Radiometers andFrequencyBands Used1974.6.2 Microwave Radiometers: Basic Performance1974.6.3Real2204.6.4Synthetic Aperture4.6.5Future Trends in Microwave RadiometersApertureRadiometersRadiometers2572864.7 Study QuestionsCHAPTER 55.1ix288RadarA291Compact Introduction5.1.15.1.25.2 Radar5.2.1toRadar Theory293RangingDoppler ds2985.2.2 Normalizations of the RadarReflectivity2995.2.3 Point Versus Distributed Scatterers5.2.4Speckle, ons: Double Bounce,TripleBounce, andUrban Areas5.2.8Backscattering311of Surfaces3145.2.9 Periodic Scattering: The Bragg rization318of VolumesSummary321of Radar Backscatter325of Radar Waves3255.3 Radar iver for330aSingleEcho: The Matched Filter5.3.3 Matched Filter Versus Inverse Filter5.3.4OptimalReceiver forThe BackprojectionRange-Doppler333334Radar Echoes:Operator3365.3.5 Radar Waveforms5.3.6 A304307Equation5.2.6 Radar Waves at5.2.7302and Radiometric Resolution337Paradigmatic Example: Linear FrequencyModulated Pulses(Chirps)5.3.7 Geometrical Dialectics of Remote5.3.8 Profiler arsRadarsSide-Looking340341Radars5.3.10 Distortions of the Radar Side-Looking Geometry3423445.3.11 Flat Earth Versus Curved Surface3475.3.12 Ground349Velocity
CONTENTS5.3.13 Local Versus Global Coordinate350Systems3525.3.14 The Radar Coordinates5.3.15352Geocoding5.3.17The Radar353Synthetic Aperture5.3.16 Real Versusas a355Communications System3755.4 Synthetic Aperture Radar5.4.1ACompactIntroduction to5.4.2Synthetic Aperture5.4.3Fundamentals ofRadarSynthetic ApertureRadarTheorySystemsand MissionsSynthetic ApertureRadar391Processing5.5 Synthetic Aperture Radar Interferometry5.5.1377391401Geometrical Models4035.5.2 Coherence, Effective Number of Looks, and Decorrelation408Sources5.5.3 Interferometric413Processing4175.5.4 Differential Synthetic Aperture Radar Interferometry5.5.5Synthetic ApertureRadar422Tomography4275.6 Future Synthetic Aperture Radar Systems5.6.1High-Orbit (Medium Earth/Geosynchronous) SyntheticAperture5.6.3Onboard428Radar5.6.2 MultichannelSynthetic ApertureProcessingSynthetic ApertureRadar429Systemsfor Data Reduction in Earth andPlanetary431Radar Missions5.6.4 Bistatic and Multistatic Synthetic ApertureRadar ConstellationsGeometrical Models5.7.2Illuminated Area and EchoSignal439Power5.7.3 Radar Altimetry Over the Ocean4405.7.4 Error Correction and Calibration4445.8.1ScatterometryBriefHistoryfor Ocean Wind Vector Observationsof5.8.3 SeaWindsa445446Scatterometry5.8.2 Scatterometer AntennaCHAPTER 64375.7.15.8 Radar5.94324355.7 Radar 4 Scatterometer Limitations4495.8.5449Examplesof Scatterometer Measurements452Study QuestionsSensing Using Global NavigationSystem Signals of OpportunityRemoteSatellite4556.1 Brief Historical Review4556.2 Fundamentals of Global Navigation Satellite System Signals4596.3 Global Navigation Satellite System—Radio Occultations466
CONTENTS6.3.1BasicPrinciplesxi4666.3.2 GNSS-RO Instruments4726.3.3 GNSS-RO Applications4736.4 Global6.4.1Navigation Satellite System-ReflectrometryBasic Principles: GNSS-R as a Multistatic Radar6.4.2 GNSS-R Particularities6.4.3 Thermal Noise,476478485Speckle,and Coherence Time4896.4.4 GNSS-R Instruments4986.4.5525Applications6.5 Future Trends in GNSS-R5626.6 Study Questions564CHAPTER 77.1Orbital Mechanics, Image Navigation, and CartographicProjections565History5657.2 Kepler's Laws of Planetary Motion7.2.17.2.27.2.3566Kepler'sFirst Law567Kepler'sSecond Law567Kepler'sThird Law5687.2.4 TheTwo-BodyProblem5687.2.5 Low Earth Orbits5707.2.65747.2.7GeostationaryHighly EllipticalOrbitsOrbits7.3 Map Projections, Image575Navigation,7.3.1Mathematical7.3.2Image Georeferencing7.3.3AdvancedModelingand Georectificationof the Earth's SurfaceVery High-ResolutionAutogeoregistration Using Image577579Radiometer AccurateCalculated Attitude Parameters7.4Map Projections7.5 Study QuestionsCHAPTER 88.1577584592595Atmosphere Applications597Cloud Remote5978.1.1CloudSensingTop Temperature5978.1.2 Cloud Shape and Cloud Type8.1.3 RemoteSensingof Clouds and Cloud600Properties6048.2 Atmospheric Aerosols and Optical Thickness8.2.1AerosolOptical606Thickness8.2.2 Ground Validation of Satellite Observed607Optical8.3 Atmospheric Profiling8.3.1Radiosondes, Rawinsondes, and DropsondesThickness609614614
xiiCONTENTS8.3.2 Satellite Remote617Sensing Atmospheric Profiling8.4 Rain Rate, Atmospheric Liquid Water, and Cloud Liquid Water8.4.1RainEstimationRate631Using Microwave Radiometry8.4.2 Rain Rate EstimationUsing632Radar6338.5 Study QuestionsCHAPTER 99.1OceanApplicationsSea Surface9.1.1635637637TemperatureSensing ofInfraredSea Surface9.1.3 AdvancedVery HighSea SurfaceMerging638Resolution Radiometer Pathfinder642Temperature9.1.4 Passive Microwave Sea Surface9.1.5638TemperatureHigh Resolution Radiometer9.1.2 The Advanced Very648TemperatureInfrared and Passive Microwave Sea Surface652Temperatures9.2 Sea SurfaceHeightand Satellite660Altimetry9.2.1Radar ter Error Corrections6649.2.5Altimeter Waveforms and Backscatter664of Satellite Altimetersof661662Operation9.2.6 Altimeter Data667Merging9.2.7Synthetic ApertureRadar9.2.8Altimetry Applications667Altimetry6689.3 Synthetic Aperture Radar Ocean an Winds FromSynthetic680Radar9.3.2 Directional Wave NumberSpectraFromSynthetic ApertureRadar683Imagery9.4 Ocean Wind Scatterometry9.4.1Mapping686the Ocean Wind VectorSalinity9.4.3and Benthic Habitats9.4.4BathymetrySargassum Saga: Spotting6866899.4.2 Sea SurfaceMappingSeaweed Fromin Shallow WatersSpace6936979.5 Conclusions6989.6 Study Questions699CHAPTER 1010.1LandApplicationsHistorical Development10.2 1701706706
CONTENTS10.2.2Mapping10.2.3 Carbon10.2.4Floods and FloodPlains711Storage713Drought Monitoringand ItsImpactin Forest Decline and FiresOccurrence10.2.5Analyzing713Landsat toMitigateBird/Aircraft Collisions10.2.6 Landsat Adds Tremendous Value10.3 Land Cover10.4 Commercialxiiito DecisionMakingMappingHigh-Resolution Optical Imagery71571771872010.4.1Satellite Pour l'Observation de la Terre72010.4.2DigitalGlobe724Inc10.5 Forest Fire Detection and Mapping10.5.1730MODIS Fire Products73110.5.2 MODIS Active Fire Detection73110.5.3 MODIS Fire Validation73410.5.4 The Hay man Wildfire in Colorado73610.6 Measuring and Monitoring Vegetation From Space10.6.1 The AVHRR NDVI 8-km Dataset10.6.2UsingNDVItoIdentify742and Monitor Corn Growthin Western Mexico10.6.3Microwave Remote740744SensingofVegetationand Soil Moisture74510.7 The European Copernicus Program76210.8 Study Questions766CHAPTER 1111.1Cryosphere Applications767Introduction76711.2 Polar Observations76711.2.1Satellite LaserAltimetry77011.2.2 Satellite RadarAltimetry77211.3 Sea Ice77211.4 Ice Sheets77311.5 CryoSat Instruments11.5.111.5.211.6 erometry to ComputeSea Ice Concentration and Drift77811.7 Thin Ice Thickness Estimation78111.8 Multiyear Arctic Sea Ice Classification Using OSCAT and QuikSCAT78311.8.1Greenland Ice Sheet11.8.2 Sea Ice Concentration and Ice Motion78679011.9 Arctic Sea Ice Drift Estimation by Merging Radiometer andScatterometer Data792
xivCONTENTS11.10 Merging the Sea Ice Drift Products79211.11795CHAPTER 12Study QuestionsRemoteSensing With Small Satellites12.1 Introduction12.2 Earth Observation797797UsingConstellations of Small Satellites12.3 Future Trends in Small Satellites801809References811Index843
CONTENTS xi 6.3.1 Basic Principles 466 6.3.2 GNSS-ROInstruments 472 6.3.3 GNSS-ROApplications 473 6.4 Global Navigation Satellite System-Reflectrometry 476 6.4.1 BasicPrinciples: GNSS-Ras aMultistatic Radar 478 6.4.2 GNSS-RParticularities 485 6.4.3 Thermal Noise, Speckle, and CoherenceTime 489 6.4.4 GNSS-RInstrume
PRINCIPLES OF REMOTE SENSING Shefali Aggarwal Photogrammetry and Remote Sensing Division Indian Institute of Remote Sensing, Dehra Dun Abstract : Remote sensing is a technique to observe the earth surface or the atmosphere from out of space using satellites (space borne) or from the air using aircrafts (airborne). Remote sensing uses a part or several parts of the electromagnetic spectrum. It .
Scope of remote sensing Remote sensing: science or art? The remote sensing process Applications of remote sensing Information flow in remote sensing The EMRreflected, emitted, or back-scattered from an object or geographic area is used as a surrogatefor the actual property under investigation.
Jul 28, 2014 · imagery analysis are forms of remote sensing. Remote sensing, a term which refers to the remote viewing of the surrounding world, including all forms of photography, video and other forms of visualization (Parcak 2012) can be used to view live societies. Satellite remote sensing allows
Proximity Sensor Sensing object Reset distance Sensing distance Hysteresis OFF ON Output Proximity Sensor Sensing object Within range Outside of range ON t 1 t 2 OFF Proximity Sensor Sensing object Sensing area Output (Sensing distance) Standard sensing object 1 2 f 1 Non-metal M M 2M t 1 t 2 t 3 Proximity Sensor Output t 1 t 2 Sensing .
Abstract Satellite remote sensing data has significant potential use in analysis of natural hazards such as landslides. Relying on the recent advances in satellite remote sensing and geographic information system (GIS) techniques, this paper aims to map landslide susceptibility over most of the globe using a GIS-based weighted linear
An advantage of airborne remote sensing, compared to satellite remote sensing, is the capability of offering very high spatial resolution images (20 cm or less). The disadvantages are low coverage area and high cost per unit area of ground coverage. It is not cost-effective to map a large area using an airborne remote sensing system.
Chapter 3 Introduction to Remote Sensing and Image Processing 17 Introduction to Remote Sensing and Image Processing Of all the various data sources used in GIS, one of the most important is undoubtedly that provided by remote sensing. Through the use of satellites, we now have a continuing program of data acquisition for the entire world with time frames ranging from a couple of weeks to a .
One upscaling approach is to use satellite remote sensing observations and climate data (Turner et al., 2003). Repetitive and systematic satellite remote sensing observations of vegetation dynamics and ecosystems allow us to characterize vegetation structure, and estimate GPP and NPP (Potter et al., 1993; Ruimy et al., 1994).
