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Fundamentos de teledeccion para la web acuatica

El tratamiento digital de las imágenes agiliza el proceso de interpretación, permite generar modelos cuantitativos e integrar los resultados con otro tipo de información geográfica. Contribuye además a resolver problemas vinculados con la entrada y actualización de datos en la implementación de SIG (también conocido con los acrónimos SIG en español o GIS en inglés), por la capacidad de obtener documentos temáticos, a bajo costo y en un período de tiempo bastante cercano a la obtención de la imagen utilizada, ofreciendo mayor accesibilidad temporal frente a otras técnicas convencionales.

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Fundamentos de teledeccion para la web acuatica

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  1. National Aeronauticsand SpaceAdministration ARSET AppliedRemoteSensingTraining http://arset.gsfc.nasa.gov NASAARSET @ Fundamentals of Aquatic Remote Sensing Sherry L. Palacios, Ph.D. www.nasa.gov

  2. Course Objective • Provide an overview ofaquatic optics,the remote sensing ofwatertargets,and NASA Earth observation resources available for aquatic applications. Credit:NASA/USGS Landsat; GeoscienceAustralis National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 2

  3. Agenda • • • Lightand Water Fundamentals ofRemote Sensing Aquatic Remote Sensing Data Products TheirUses Accessing NASASatellite Imagery and • • NASASatellite Data Processing Tools PhytoplanktonBloom intheArabianSea Credit:N. Kuring,http://earthobservatory.nasa.gov/IOTD/view.php?id=85718 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 3

  4. Why Do We Observe from Space? To Understand Earth’s Processes on a Global Scale SeaWiFSChlorophyll Credit: OBPG,NASA Goddard National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 4

  5. Advantages of Remote Sensing ofAquatic Environments • • • Synoptic coverage Temporal frequency needed to capture dynamic aquatic processes Observations of remote ocean locations, infrequently accessed by sea-based platforms National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 5

  6. Light and Water

  7. Agenda • Lightand Water –How lightpropagates through the atmosphere and watercolumn,and back to sensor –Constituents ofthe watercolumn and their inherentoptical properties Fundamentals ofRemoteSensing • • Aquatic Remote Sensing Data Products TheirUses Accessing NASASatellite Imagery NASASatellite Data ProcessingTools and • • PhytoplanktonBloom intheArabianSea Credit:N. Kuring, http://earthobservatory.nasa.gov/IOTD/view.php?id=85718 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 7

  8. First, anAquatic Optics Primer… The Electromagnetic Spectrum National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 8

  9. How Light Interacts with Water Defining Remote Sensing Reflectance (Rrs) – or ‘Ocean Color’ InherentOptical Properties a = absorption by… phytoplankton (ph) non-algal particles (nap) colored dissolved organic water(w) matter(CDOM) aph aw aCDOM a b = scattering in forward (f)and backward (b) directions nap bb bf Fluorescence National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 9

  10. How Light Interacts with Water Defining Remote Sensing Reflectance (Rrs) – or ‘Ocean Color’ InherentOptical Properties a =absorption b =scattering Rrs Ed Lw Lu Apparent Optical Properties Lw=waterleaving radiance Lu=upwelling radiance aph aw aCDOM a nap bb E =downwellingirradiance =remote sensing (rs)reflectance d Rrs bf Fluorescence National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 10

  11. Inherent Optical Properties (IOPs) and the ‘Color’ of Water Lightabsorption (a)by photoplankton (ph), non-algal particles (nap),water(w),and colored dissolved organic matter(CDOM) a= aph+anap +aCDOM +aw Lightscattering (b)by particles in forward and backward (bb)direction b=bf+bb (bf) National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 11

  12. Inherent Optical Properties (IOPs) and the ‘Color’ of Water chlorophyll water CDOM nap/ sediments National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 12

  13. Inherent Optical Properties (IOPs) and the ‘Color’of Water Visible Near IR chlorophyll 0.025 sediments 0.02 water 0.015 Rrs (sr-1) CDOM 0.01 CDOM water 0.005 chlorophyll nap/ sediments 0 400 500 600 Wavelength 700 (nm) 800 900 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 13

  14. Inherent Optical Properties (IOPs) and the ‘Color’ of Water Visible Near IR • The typical human eye has color- detecting receptors that at: sense light chlorophyll 0.025 – – – 420-440 534-555 564-580 nm nm nm ‘blue’ ‘green’ ‘red’ 0.02 0.015 Rrs (sr-1) • Waterwith high chlorophyll content looks green because itreflects 0.01 strongly in the green part spectrum of the 0.005 0 400 500 600 Wavelength 700 (nm) 800 900 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 14

  15. Fundamentals of Remote Sensing

  16. Agenda • • Lightand Water Fundamentals ofRemote Sensing – – Spatial,Temporal,Spectral Resolution NASASatellites and Sensors forAquatic Applications Image “Correction” Satellite Data Processing Levels – – • Aquatic Remote Sensing Data Products TheirUses Accessing NASASatellite Imagery NASASatellite Data ProcessingTools and • • PhytoplanktonBloom intheArabianSea Credit:N. Kuring, http://earthobservatory.nasa.gov/IOTD/view.php?id=85718 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 16

  17. Types of Resolution SpatialResolution TemporalResolution SpectralResolution • • Decided by its pixel Pixel:smallestunit size • How frequently a satellite • Ability ofa sensorto define fine wavelength intervals Finerspectral channels enable observes the same area of the Earth measured by a sensor • remote sensing ofdifferent ofthe atmosphere *Credit:Natural Resources Canada parts Satellite (Sensor) SpatialResolution TemporalResolution SpectralBands Landsat8 (OLI) 15 m,30 m 16 day revisit 9 bands (blue-green, green,red,nearIR, shortwave and thermal IR) Terra,Aqua (MODIS) 250 m– 1 km 2 timesperday 36 bands (red,blue, IR,NIR,MIR) National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 17

  18. How Do Overview We Observe From Space? ofActive & Passive Remote Sensing • Satellites measure: carry instruments and sensors to – – reflected solarradiation emitted infrared and microwave radiation National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 18

  19. Data Collection by Satellites Atmosphere • • • Clouds Aerosols Gases Earth’s Surface • • • Snow/Ice Land (land Water use, vegetation) National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 19

  20. Remote Sensing of Water Bodies Reflected SolarRadiation(~colorofwater) • • Measured by satellite sensors Used to derive the properties of optically- active water constituents CoccolithophoreBloom,Norway •Suspended Sediments •Algae •Colored Dissolved Organic Matter •Detrital Organic Matter •Submerged orfloating vegetation •Oil •Contaminants •Pathogens National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 20

  21. Remote Sensing of Water Bodies Emitted ThermalRadiation • Used to derive the surface temperature of water bodies 8-dayaverageSST MARACOOS, ORB Lab,courtesy M. Oliver AppliedRemoteSensingTrainingProgram National AeronauticsandSpaceAdministration 21

  22. NASASatellites and Sensors forAquaticApplications

  23. Overview of NASASatellites & Sensors for Water Quality Monitoring • Currently several satellites observe water surface properties in: – – – A the open ocean coastal oceans and estuaries many inland lakes numberofwaterquality parameters are • operationally available fromthese satellites – e.g. temperature, chlorophyll-a National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 23

  24. NASA Satellites & Sensors for Ocean and Coastal Systems Satellite Sensor Parameter Landsat Series (7/1972 - present) •Thematic Mapper (TM) •EnhancedThematic Mapper (ETM+) •Operational Land Imager (OLI) •Spectral Reflectance Terra (12/1999 - present) Moderate Resolution Imaging Spectroradiometer (MODIS) •Spectral Reflectance •Temperature (CDOM) •Turbidity •Euphotic Depth • Chlorophyll-a Concentration • Colored Dissolved Organic Matter Aqua (5/2002 - present) Terra (12/1999 – present) Advanced SpaceborneThermal Emission and Reflection Radiometer (ASTER) •Spectral Reflectance • Temperature National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 24

  25. NASA Satellites & Sensors for Ocean and Coastal Systems Satellite Sensor Parameter National Polar Partnership (NPP) (11/2011-present) Visible Infrared Imaging RadiometerSuite (VIIRS) •Spectral Reflectance • Chlorophyll Concentration International Space Station Hyperspectral Imagerforthe Coastal Ocean (HICO)(2009 – 2014) •Spectral Radiance Reflectance • Spectral Remote Sensing Plankton,Aerosols, Clouds,ocean Ecosystems (PACE) (proposed for2022 or 2023) Ocean ColorInstrument •Spectral Reflectance •Optional Polarimeter being considered National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 25

  26. Landsat Satellites and Sensors http://landsat.gsfc.nasa.gov/ • • • • • • Near-polarorbit 10 a.m.equatorcrossing Global coverage July 1972 – present time 16 day revisit Sensors: time – – – – – MSS TM ETM+ OLI TIRS National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 26

  27. Landsat-7 EnhancedThematic Mapper http://geo.arc.nasa.gov/sge/landsat/l7.html (ETM+) • Flying on-board Landsat7 polarorbiting satellites Spatial Coverage and Resolution: –Global,swath 185 km –Spatial Resolution:15 m,30 m,60 m Temporal Coverage and Resolution –April 15,1999 – present –16 day revisittime Spectral Bands –8 bands (majorbands include:blue-green, green,red,reflected and thermal IR,and panchromatic) • • • • Spectral Bands – – – Bands 1-5, 7: m m 30 m Band Band 6: 8: 60 15 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 27

  28. Landsat-8 Operational Land Imager (OLI) http://landsat.usgs.gov/landsat8.php; http://landsat.gsfc.nasa.gov/?p=5779 •Spectral Bands –Bands 1-7,9:30m –Band 8:15m Visible Near- Short-wavelength Thermal-wavelength Infrared infrared infrared • Flying on-board Landsat8 (LandsatData Continuity Mission – LDCM)polarorbiting satellite Spatial Coverage & Resolution: –Global,Swath 185 km –Spatial Resolution:15 m,30 m Temporal Coverage & Resolution: –February 11,2013 – present –16 day revisittime Spectral Bands –9 bands (majorbands include blue-green, red,nearIR,shortwave and thermal IR, panchromatic) • • • National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 28

  29. Terra andAqua http://terra.nasa.gov/; http://aqua.nasa.gov/ Terra Aqua • • • • • Polarorbit,10:30 a.m.equator Global Coverage December18,1999 – present 1-2 observations perday Sensors: crossing time • • • • • Polarorbit,1:30 p.m.equatorcrossing time Global Coverage May 4,2002 – present 1-2 observations perday Sensors: – ASTER, CERES, MISR, MODIS, MOPITT – AIRS,AMSU, CERES, MODIS,AMSR-E National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 29

  30. MODerate Resolution Imaging Spectroradiometer (MODIS) http://modis.gsfc.nasa.gov • • On boardTerra andAqua Designed forland,atmosphere, cryosphere observations SpectralBands ocean, and • 36 bands (red,blue, IR, NIR, MIR) – – – Bands Bands Bands 1-2:250 m 3-7:500 m • Spatial Coverage and Resolution: –Global,Swath:2,330 km –Spatial Resolution Varies:250 m, 1 km 8-16: 1000 m 500 m, • Temporal Coverage –2000 – present –2 times perday and Resolution: ImageCredit: http://cimss.ssec.wisc.edu/ National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 30

  31. National Polar Partnership (NPP) http://www.nasa.gov/mission_pages/NPP • • • • • • Polarorbit 1:30 p.m.equatorcrossing time Global coverage November21,2011 – present 1-2 observations Sensors: per day – – – – – VIIRS ATMS CrlS OMPS CERCES NASA/NOAA National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 31

  32. Visible Infrared Imaging Radiometer http://npp.gsfc.nasa.gov/viirs.html Suite (VIIRS) • • Flying on-board NPP,polar-orbiting satellite Designed to collectmeasurements ofclouds, aerosols,ocean color,surface temperature, fires,and albedo Spatial Coverage and Resolution: –Global,swath width:3,040 km • • Spectral Bands –Spatial resolution:375 m Temporal Coverage –October2011 – present –2 times perday – 750 m – 15 bands (major bands include visible,red, • blue,green,short,middle,and long-wave IR) Ocean ColorBands 1-7:0.402-0.682 μm Sea SurfaceTemperature Bands 12-13: 3.660 -4.128 μm – – National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 32

  33. Hyperspectral Imager for the Coastal Ocean (HICO) http://hico.coas.oregonstate.edu/; http://oceancolor.gsfc.nasa.gov/cms/data/hico • Partnership with U.S.Naval Research Lab,Office ofNaval Research, and NASA Oregon State University, • • • • Active 2009 – 2014 aboard the International Space Station (ISS) 380 nmto 960 nmat5.7 nm spectral resolution m2 90 spatial resolution Targeted data collection Davis,C. O.(n.d.).TheHyperspectral Imager for theCoastal Ocean(HICO): Sensor andDataProcessing Overview [PDF]. International Ocean Colour CoordinatingGroup. National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 33

  34. Plankton,Aerosol, Clouds, http://pace.gsfc.nasa.gov/ Ocean Ecosystem (PACE) • • • • Polarorbiting,2-day revisit High spectral resolution 1 kmground sample distance Optional polarimeterbeing considered for cloud and aerosol study and atmospheric correction Anticipated launch 2022 to aid in • National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 34

  35. Image “Correction”

  36. National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 36 Remote Sensing of Water Bodies 0.025 0.02 NearIR Rrs(sr-1) 0.015 0.01 0.005 0 400 800 90 Matter 500 600 700 0 Colored Dissolved Wavelength (nm) Organic Phytoplankton Suspended sediments Detrital particles

  37. National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 37 Atmospheric Correction <10% >90% 9 8 7 6 5 4 Water 3 2 1 0 Wavelength(nm) L(λ) t L(λ) r L(λ) a t(λ,θ).L (λ) w t(λ,θ).L (λ) wc T(λ,θ)(λ).L(λ) g Top-ofatmosphere Radiance (µW.cm−2.sr−1.nm−1) 400 500 600 700 800 900

  38. National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 38 Water-leaving radiance Downwelling Irradiance Lw(l) Ed(l,0+) Field spectroradiometer

  39. National Aeronauticsand SpaceAdministration ARSET AppliedRemoteSensingTraining http://arset.gsfc.nasa.gov NASAARSET www.nasa.gov Atmospheric Correction @ <10% >90% Water Top-ofatmosphere Atmospheric correction

  40. Satellite Data Processing Levels

  41. Levels of Data Processing http://oceancolor.gsfc.nasa.gov/cms/products • Level 0:unprocessed instrumentdata atfull resolution,rawestformat available Level 1A:reconstructed and unprocessed instrumentdata atfull resolution • • • • Level Level Level 1B:L1Adata with instrument/radiometric calibrations applied 2:Derived geophysical variables atsame resolution as L1 data 3:L2 projected onto a well defined spatial grid overa well-defined time period Level 4:model outputorresults fromanalyses oflowerlevel data –e.g.,Primary Productivity • National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 41

  42. Data Processing Levels L0:Raw instrumentdata Harder to Use L Geolocate and calibrated 1: d L2:Products derived fromL1B L3:Gridded and quality controlled L4:Model output:derived variables Easier to Use National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 42

  43. Aquatic Remote Sensing Data Products andTheir Uses

  44. Agenda • • • Lightand Water Fundamentals ofRemote Sensing Aquatic Remote Sensing Data Products TheirUses Accessing NASASatellite Imagery and • • NASASatellite Data Processing Tools PhytoplanktonBloom intheArabianSea Credit:N. Kuring, http://earthobservatory.nasa.gov/IOTD/view.php?id=85718 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 44

  45. What Can We Observe from Space? Ocean Properties Derived from Remote Sensing Imagery Observation Application Chlorophyll-a Phytoplankton biomass,primary productivity, biogeochemical cycling WaterTurbidity Waterquality,human and ecosystemhealth Colored Dissolved Organic Matter(CDOM) Waterquality,biogeochemical cycling,human and ecosystemhealth Sea SurfaceTemperature (SST) Currents,primary productivity,climate studies, biogeochemistry,temperature flux Surface winds Currents,mixing,air-sea flux ofgases Salinity Mixing,air-sea flux ofgases,geostrophic currents, saltflux National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 45

  46. Chlorophyll-a from Remote Sensing Reflectance (Rrs) Surface Remote Sensing Reflectance National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 46

  47. Rrs at Different Chlorophyll-a Concentrations Surface Remote Sensing Reflectance 1 2 3 4 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 47

  48. Chlorophyll-a Estimates Estimations are a function of the ratios of Rrs values Surface Remote Sensing Reflectance Example: Ratio 10.0 of Rrs value at 486 nm and 550 nm 1.0 VIIRS Chl a 0.1 0.1 1.0 In situ Chl a (mg 10.0 m-3) Algorithm description:http://oceancolor.gsfc.nasa.gov/cms/atbd/chlor_a National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 48

  49. Chlorophyll-a from Space MODIS chlorophyll-a Northern Hemisphere Spring 2014 National AeronauticsandSpaceAdministration AppliedRemoteSensingTrainingProgram 49

  50. Accessing NASASatellite Imagery

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