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1 Elena Mauri Lecture 19 OGS, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Trieste, Italy Remote sensing technique in coastal studies.

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Presentation on theme: "1 Elena Mauri Lecture 19 OGS, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Trieste, Italy Remote sensing technique in coastal studies."— Presentation transcript:

1 1 Elena Mauri Lecture 19 OGS, Istituto Nazionale di Oceanografia e Geofisica Sperimentale, Trieste, Italy Remote sensing technique in coastal studies

2 2 OUTLINE  Electromagnetic spectrum and black body emission  Satellite orbits and sampling  PASSIVE REMOTE SENSING: in the visible bands (Ocean Color), principles, atmospheric contamination, algorithms to retrieve chlorophyll concentration pan-spectral, multi-spectral and hyper-spectral sensors and applications (MODIS, Landsat7) in the thermal infrared bands (Sea Surface Temperature) principles, atmospheric effects, algorithms to retrieve SST applications (AVHRR and MODIS)  ACTIVE REMOTE SENSING: in the microwave bands (Satellite Altimetry and Synthetic Aperture Radar) principles applications (geostrophic surface circulation oil spill detection, etc.)

3 3 is the science and art of obtaining information about an object, area, or phenomenon through the analysis of data acquired by a device that is not in contact with the object, area, or phenomenon under investigation. Satellite Remote Sensing uses electromagnetic radiation to measure near-surface ocean properties Remote Sensing

4 4 Links: http://www.biogeorecon.com/remote.htm http://www.eeb.ucla.edu/test/faculty/nezlin/SatellitesAndSensors.htm Microwave (MW) active (3-30 GHz) Visible (400 nm - 1000 nm, VIS) Infrared (~ 10,000 nm, IR) Electromagnetic spectrum

5 5 Plank’s Law & Blackbody Emission Planck's law describes the spectral radiance of electromagnetic radiation at all wavelength from a black body at temperature T. As the temperature decreases, the peak of the black-body radiation curve moves to lower intensities and longer wavelengths. Black body when is cold no light is reflected or transmitted, the object appears black. When is hot, it will on average emit exactly as much as it absorbs, at every wavelength. Passive remote sensing

6 6 Sun emission Earth emission Passive remote sensing

7 7 Links: http://www.gisdevelopment.net/tutorials/tuman008.htm http://www.crisp.nus.edu.sg/~research/tutorial/atmoseff.htm http://earthobservatory.nasa.gov/Library/RemoteSensingAtmosphere/ Effects of Atmosphere on the electromagnetic spectrum

8 8 Links: http://www.rap.ucar.edu/~djohnson/satellite/coverage.html Geostationary Near-Polar orbiting Sun-synchronous Satellite orbits

9 9 Polar-orbiting and geostationary Satellites

10 10 Links: http://www.csc.noaa.gov/products/nchaz/htm/ccap5.htm Passive (VIS, IR, MW)Active (MW) Passive and Active Satellite Remote Sensing

11 11 Satellite Sampling Links: http://ccrs.nrcan.gc.ca/resource/tutor/fundam/chapter2/08_e.php ScanningPushbroom Satellite sensors Instantaneous Field of View (IFOV)

12 12 Sensor Calibrations and Ground Truth In-situ measurements are needed for ground truthing or validation of remotely sensed data Links: http://www.fas.org/irp/imint/docs/rst/Front/tofc.html Surface drifter (SST) Oceanographic Platform (Ocean color)

13 13 Sunlight propagation, refection and absorption by atmosphere and ocean Passive remote sensing: VISIBLE

14 14 Remote sensing in the VISIBLE OCEAN COLOR Ocean color is not the color we normally see, blue/gray due to the reflection of the sky. BUT Ocean color is the color that would be observed freed from the surface reflection, for instance the color measured beneath the surface of the water. Passive remote sensing: VISIBLE

15 15 Remote sensing reflectance (Rrs) E u (λ) E d (λ) Is the ratio between the irradiance upwelling just under the surface of the water E u (λ), to the downwelling irradiance just penetreting the surface E d (λ). Rrs= Passive remote sensing: VISIBLE

16 16 Remote Sensing Reflectance and inherent optical properties b b (λ) b b (λ) + a(λ) Where: a(λ)=a w (λ)+a ph (λ)+a d (λ)+a cdom (λ) b b (λ)=b bw (λ)+b bp (λ) Passive remote sensing: VISIBLE Absorption is the process by which the enery of a photons is taken up by another entity, for example, by an atom whose valence electrons make transition between two electronic energy levels. The photon is destroyed in the process. Scattering is a general physical process whereby radiation are forced to deviate from a straight trajectory. Rrs( λ)=const

17 17 Total absorption spectrum of an idealized, productive ( = 1 mg m-3) oceanic water together with spectra of the individual absorbing components. Relative contribution of absorption by phytoplankton, a ph (), and by organic detritus, a det () or a d (), to the total particulate absorption, a p (), from Sargasso Sea waters at 20 m depth Passive remote sensing: VISIBLE Absorption

18 18 Clean ocean water (A) has maximum backscatter in short (blue) wavelength and almost zero in yellow and red. Higher is phytoplankton (i.e., chlorophyll and other plant pigments) concentration, more is contribution of green color (B). In coastal zones with high concentration of dead organic and inorganic matter light spectrum has maximum in red (C). bluegreenred Passive remote sensing: VISIBLE Back-scattering

19 19 Empirical Chlorophyll algorithms Reference Algorithms for calculation Ratio R SeaWiFS OC2v2 O’Reilley (2000) = 10^(a(1) + a(2)*R + a(3)*R 2 + a(4)*R 3 ) +a(5) *R 4 ) a = [0.2974, -2.2429, 0.8358, -0.0077, - 0.0929] R = log 10 (R rs490 /R rs555 ) SeaWiFS OC4v4 = 10^(a(1) + a(2)*R + a(3)*R 2 + a(4)*R 3 ) +a(5) *R 4 ) R = log 10 (R rs443> R rs490> R rs510 /R rs555 ) CZCS GPs Gordon et al. (1983) C 13 = 10^(0.053+1.71* R1) C 23 = 10^(0.522+2.44* R2) + P = C 13 ; if C 13 > 1.5 mg m -3 then + P = C 23 R 1 = log 10 (L wn550 /L wn443 ) R 2 = log 10 (L wn550 /L wn520 ) P = phaeopigments ( + P ) = 1.3404* 0.983 OCTS-C OCTS-C (1996) = 10^(a(1) + a(2)*R) a = [-0.55006, 3.497] R = log 10 ((L wn520 + L wn565 )/L wn 490 ) Morel (1988) = ((K d490 -K w490 )/X) 1/e K d490 = 0.02+0.1*(R) -1.29966 R = R rs443 / R rs555 K w490 = 0.0217 X=0.069, e=0.702 MODIS = 10^(a(1) + a(2)*R + a(3)*R 2 + a(4)*R 3 ) +a(5) *R 4 ) R = log 10 (R rs443> R rs488 /R rs551 ) Passive remote sensing: VISIBLE = 10^(a(1) + a(2)*R + a(3)*R 2 + … … a(4)*R 3 ) + a(5)*R 4 ) where R = log 10 Rrs490 Rrs555 a = [0.2974, -2.2429, 0.8358, -0.0077, - 0.0929] empirical coefficients ()

20 20 Specifications Orbit705 km, 10:30 a.m. descending node (Terra) or 1:30 p.m. ascending node (Aqua), sun- synchronous, near-polar, circular Scan Rate20.3 rpm, cross track Swath2330 km (cross track) by 10 km (along track at nadir) Dimensions Telescope17.78 cm diam. off-axis, afocal (collimated), with intermediate field stop Size1.0 x 1.6 x 1.0 m Weight228.7 kg Data Rate10.6 Mbit/s (peak daytime); 6.1 Mbit/s (orbital average) Spatial Resolution250 m (bands 1-2) 500 m (bands 3-7) 1000 m (bands 8-36) Design Life6 years MODIS Passive remote sensing: VISIBLE Moderate-resolution Imaging Spectroradiometer is on board of two satellite: Terra (EOS AM) satellite (1999), AQUA (EOS PM) satellite (2002). there are 36 spectral bands ranging in wavelength from 0.4 μm to 14.4 µm and at varying spatial resolutions (2 bands at 250 m, 5 bands at 500 m and 29 bands at 1 km). together the instruments image the entire Earth every 1 to 2 days. designed to provide measurements in large-scale global dynamics including changes in Earth's cloud cover, radiation budget and processes occurring in the oceans, on land, and in the lower atmosphere.

21 21 Passive remote sensing: VISIBLE MODIS spectral bands and athmospheric effects

22 22 Passive remote sensing: VISIBLE

23 23 Passive remote sensing: VISIBLE

24 24 Passive remote sensing: VISIBLE

25 25 Passive remote sensing: VISIBLE

26 26 Passive remote sensing: VISIBLE

27 27 Passive remote sensing: VISIBLE

28 28 Passive remote sensing: VISIBLE

29 29 Passive remote sensing: VISIBLE

30 30 Passive remote sensing: VISIBLE

31 31 Passive remote sensing: VISIBLE

32 32 Passive remote sensing: VISIBLE

33 33 Passive remote sensing: VISIBLE

34 34 Ocean Color Phytoplankton pigment (chlorophyll-a) concentration. The global biosphere! Passive remote sensing: VISIBLE

35 35 Passive remote sensing: VISIBLE MODIS chlorophyll concentration around Tanzania

36 36 Spatial and seasonal (monsoon) variability of the chlorophyll-a concentration in NW Atlantic and Indian Oceans Ocean Color Passive remote sensing: VISIBLE

37 37 Remote sensing in the VISIBLE Truecolor is a method of representing image (especially in computer processing) in an RGB color space. MODIS res. 250 m Multispectral is a type of sensor with sensitive to a few specific wavelength and hyperspectral sensitive to many (can reach 200 bands) specific bands Panchromatic sensor is a type of sensor that is sensitive to all wavelength of visible light. This imagery is of a much higher resolution than the multispetral imagery. For example, the QuickBird satellite produces panchromatic imagery having a pixel equivalent to an area 0.6m x 0.6m, while the multispectral pixels represent an area of 2.4m x 2.4m. QuickBird and IKONOS Pansharpening is a process of merging high resolution panchromatic and lower resolution multispectral imagery to create a single high resolution color image Passive remote sensing: VISIBLE

38 38 The Earth Observing System (EOS) is a program of NASA comprising a series of artificial satellite missions and scientific instruments in Earth orbit designed for long-term global observations of the land surface, biosphere, athmosfere, and oceans of the Earth. The first satellite component of the program was launched in 1997. Passive remote sensing: VISIBLE

39 39 Landsat 7, launched on April 15, 1999, is the latest satellite of the Landstat program. Landsat 7's primary goal is to refresh the global archive of satellite photos, providing up-to-date and cloud free images. Although the Landsat Program is managed by NASA, data from Landsat 7 is collected and distributed by the USGS. The NASA World Wind project allows 3D images from Landsat 7 and other sources to be freely navigated and viewed from any angle. Landsat 7 data has eight spectral bands with spatial resolutions ranging from 15 to 60 meters. Landsat 7 Passive remote sensing: VISIBLE

40 40 Passive remote sensing: VISIBLE Landsat 7

41 41 Passive remote sensing: VISIBLE Landsat 7

42 42 Phytoplankton bloom South Atlantic Ocean (off Argentina coast) Coccolotophorids bloom in Bering Sea MODIS True color (250 m resolution)

43 43 True color satellite images of Italian Seas (non-dusty and dusty cases)

44 44 is a commercial earth observation satellite and was the first to collect publicly available high-resolution imagery at 1- and 4- meter resolution. It offers multispectral(MS) and panchromatic (PAN) imagery. Spatial resolution 0.8 m panchromatic (1-m PAN Panchromatic) 4-meter multispectral (4-m MS Multispectral) 1-meter pan-sharpened (1-m PS Pansharpening) Spectral Resolution: Band1-m PAN4-m MS & 1-m PS1 (Blue)0.45-0.90 µm0.445-0.516 µm2 (Green)*0.506-0.595 µm3 (Red)*0.632-0.698 µm4 (Near IR)*0.757-0.853 µm Temporal resolution: the revisit rate for IKONOS is 3 to 5 days off-nadir and 144 days for true-nadir Passive remote sensing: VISIBLE IKONOS

45 45 Passive remote sensing: VISIBLE Bahamas

46 46 Passive remote sensing: VISIBLE Bora

47 47 NOAA (National Oceanic and Atmospheric Administration) satellites Advanced Very High Resolution Radiometer (AVHRR) data : 5 channels in VIS & IR Sea Surface Temperature (SST) Link: http://www.eeb.ucla.edu/test/faculty/nezlin/SST.htm MCSST algorithm to estimate SST Cloud masking The AVHRR instrument also flies on the METOP series of satellites. The three planned METOP satellites are part of the Eumetsat Polar System (EPS) run by Eumetsat. Passive remote sensing: INFRARED

48 48 Sea Surface Temperature (SST) algorithm Example of an algorthm SST=A*T4+B*(T4-T5)+C*(T4-T5)*(sec(θ)-1)+D A, B, C, D = empirical coefficients specific for each satellite Passive remote sensing: INFRARED

49 49 Deviation of the temperature from deep undisturbed water during daylight warming. Notice logarithmic scale. Deviation of the temperature from deep undisturbed water during night. Notice logarithmic scale. Passive remote sensing: INFRARED Sea surface temperature (SST) - is the temperature of a very thin layer of about 10 micrometres thick or skin of the ocean which leads to the phrase skin temperature (because infared radiation is emitted from this layer).

50 50 Passive remote sensing: INFRARED

51 51 Passive remote sensing: INFRARED

52 52 Passive remote sensing: INFRARED

53 53 Sea Surface Temperature (SST) Composite SST images of NW Atlantic SST constructed from AVHRR data Gulf Stream Passive remote sensing: INFRARED

54 54 Links: http://sealevel.jpl.nasa.gov http://www.aviso.oceanobs.com/ http://ibis.grdl.noaa.gov/SAT/SAT.html Altimetry Active remote sensing: MICROWAVE Jason

55 55 World’s Ocean bathymetry (geoid) Altimetry Active remote sensing: MICROWAVE

56 56 Satellite altimetry can be used to measure marine geostrophic currents Altimetry Active remote sensing: MICROWAVE

57 57 Links: http://oceanworld.tamu.edu/resources/ocng_textbook/chapter10/chapter10_03.htm http://www.eeb.ucla.edu/test/faculty/nezlin/Altimetry.htm Satellite altimetry to measure marine geostrophic currents Altimetry Active remote sensing: MICROWAVE

58 58 Sea Surface Height (SSH) in the Caribbian Sea cm

59 59 SAR imaging (MW through clouds) Synthetic Aperture Radar (SAR) Active remote sensing: MICROWAVE Small gravity and capillary waves (also referred as Bragg waves) at the ocean surface reflect the radar signal. The generation of these waves is damped by thin oily layers. Imaging radars are useful for detecting oil spills or leaks from abandoned oil wells.

60 60 Strait of Gibraltar : Surface signature of internal waves Synthetic Aperture Radar (SAR) Active remote sensing: MICROWAVE

61 61 French Riviera : Oil Slick Synthetic Aperture Radar (SAR) Active remote sensing: MICROWAVE

62 62 Synthetic Aperture Radar (SAR) Gulf of Naples, Italy: Circulation structures Active remote sensing: MICROWAVE

63 63 Synthetic Aperture Radar (SAR) Ship and its wake Active remote sensing: MICROWAVE

64 64 What do we sense from space that is useful for modeling Chlorophyll per unit of volume within the upper layer Clear sky irradiation at the sea surface, corrected for the absorption by ozone, scattering and absorption by the aerosols, effect of clouds. Sea surface temperature from which a vertical profile is derived of a reasonable estimate of a mean value in the euphotic zone. In global application also radar altimetry is used for sea surface height, heat storage in upper ocean and nutrient storage

65 65 Satellite versus in situ measurement: advantages and disadvantages SATELLITE near synoptic observations measurement above to the upper optical depth sampling time interval is large once a day for the polar-orbiting, more frequent for geostationary cloud coverage interfere with measurement not all parameters can be measured lower accuracy and precision IN SITU not synoptic observations measurement along the water column time interval can be shorter clouds do not interfere with measurement all parameters higher accuracy and precision

66 66 Remote Sensing Mooring and Tripods In-situ Non-stationary Platforms

67 67 Thanks for your attention and for your very warm hospitality


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