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

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. Remote Sensing 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

4. Electromagnetic spectrum
Visible (400 nm nm, VIS)
Infrared (~ 10,000 nm, IR)
Microwave (MW)
active (3-30 GHz)
Links:

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.
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.
As the temperature decreases, the peak of the black-body radiation curve moves to lower intensities and longer wavelengths.
Passive remote sensing

6. Sun emission
Earth emission
Passive remote sensing

7. Effects of Atmosphere on the electromagnetic spectrum
Links:

8. Satellite orbits Geostationary Near-Polar orbiting Sun-synchronous
Links:

9. Satellite orbits
Polar-orbiting and geostationary Satellites

10. Satellite Remote Sensing
Passive and Active
Satellite Remote Sensing
Passive (VIS, IR, MW)
Active (MW)
Links:

11. Satellite sensors Scanning Pushbroom Satellite Sampling
Instantaneous Field of View (IFOV)
Satellite Sampling
Links:

12. Oceanographic Platform
Sensor Calibrations and Ground Truth
In-situ measurements are needed for ground truthing or validation of remotely sensed data
Oceanographic Platform
(Ocean color)
Surface drifter (SST)
Links:

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

14. Remote sensing in the VISIBLE OCEAN COLOR
Passive remote sensing: VISIBLE
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.

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

16. Remote Sensing Reflectance and inherent optical properties
Passive remote sensing: VISIBLE
Remote Sensing Reflectance and inherent optical properties
bb(λ)
bb(λ) + a(λ)
Where: a(λ)=aw(λ)+aph(λ)+ad(λ)+acdom(λ)
bb(λ)=bbw (λ)+bbp (λ)
Rrs(λ)=const
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.

17. Absorption Passive remote sensing: VISIBLE
Relative contribution of absorption by phytoplankton, aph(), and by organic detritus, adet() or ad(), to the total particulate absorption, ap(), from Sargasso Sea waters at 20 m depth
Total absorption spectrum of an idealized, productive (<chl> = 1 mg m-3) oceanic water together with spectra of the individual absorbing components.

18. Back-scattering blue green red Passive remote sensing: VISIBLE
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).

19. Empirical Chlorophyll algorithms
Passive remote sensing: VISIBLE
Empirical Chlorophyll algorithms
Reference  
Algorithms for <Chl> calculation
Ratio R
SeaWiFS OC2v2
O’Reilley (2000)
<chl> = 10^(a(1) + a(2)*R + a(3)*R2 + a(4)*R3) +a(5) *R4 )
a = [0.2974, , , , ]
R = log10(Rrs490/Rrs555)
SeaWiFS OC4v4
R = log10(Rrs443>Rrs490>Rrs510/Rrs555)
CZCS GPs
Gordon et al. (1983)
C13 = 10^( * R1)
C23 = 10^( * R2)
<chl> + P = C13; if C13 > 1.5 mg m-3 then
<chl> + P = C23
R1 = log10(Lwn550/Lwn443)
R2 = log10(Lwn550/Lwn520)
P = phaeopigments
(<chl> + P ) = *<chl> 0.983
OCTS-C
OCTS-C (1996)
<chl> = 10^(a(1) + a(2)*R)
a = [ , ]
R = log10((Lwn520 + Lwn565)/Lwn 490)
Morel (1988)
<chl> = ((Kd490-Kw490)/X)1/e
Kd490 = *(R)
R = Rrs443/ Rrs555
Kw490 =
X=0.069, e=0.702
MODIS
R = log10(Rrs443>Rrs488/Rrs551)
<chl> = 10^(a(1) + a(2)*R + a(3)*R2 + …
… a(4)*R3) + a(5)*R4 )
where
R = log10 Rrs490
Rrs555
a = [0.2974, , , , ]
empirical coefficients ( )

20. MODIS Moderate-resolution Imaging Spectroradiometer
Passive remote sensing: VISIBLE
MODIS
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.
Specifications
Orbit
705 km, 10:30 a.m. descending node (Terra) or 1:30 p.m. ascending node (Aqua), sun-synchronous, near-polar, circular
Scan Rate
20.3 rpm, cross track
Swath
2330 km (cross track) by 10 km (along track at nadir)
Dimensions
Telescope
17.78 cm diam. off-axis, afocal (collimated), with intermediate field stop
Size
1.0 x 1.6 x 1.0 m
Weight
228.7 kg
Data Rate
10.6 Mbit/s (peak daytime); 6.1 Mbit/s (orbital average)
Spatial Resolution
250 m (bands 1-2) 500 m (bands 3-7) 1000 m (bands 8-36)
Design Life
6 years

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

22. Passive remote sensing: VISIBLE

23. Passive remote sensing: VISIBLE

24. Passive remote sensing: VISIBLE

25. Passive remote sensing: VISIBLE

26. Passive remote sensing: VISIBLE

27. Passive remote sensing: VISIBLE

28. Passive remote sensing: VISIBLE

29. Passive remote sensing: VISIBLE

30. Passive remote sensing: VISIBLE

31. Passive remote sensing: VISIBLE

32. Passive remote sensing: VISIBLE

33. Passive remote sensing: VISIBLE

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

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

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

37. Remote sensing in the VISIBLE
Passive remote sensing: VISIBLE
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

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. Landsat 7
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.
Passive remote sensing: VISIBLE

40. Passive remote sensing: VISIBLE
Landsat 7

41. Passive remote sensing: VISIBLE
Landsat 7

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

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

44. IKONOS
Passive remote sensing: VISIBLE
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) µm µm2 (Green)* µm3 (Red)* µm4 (Near IR)* µm
Temporal resolution: the revisit rate for IKONOS is 3 to 5 days off-nadir and 144 days for true-nadir

45. Passive remote sensing: VISIBLE
Bahamas

46. Passive remote sensing: VISIBLE
Bora Bora

47. Advanced Very High Resolution Radiometer (AVHRR) data :
Passive remote sensing: INFRARED
Sea Surface Temperature (SST)
NOAA (National Oceanic and Atmospheric Administration) satellites
Advanced Very High Resolution Radiometer (AVHRR) data :
5 channels in VIS & IR
Cloud masking
MCSST algorithm to estimate SST
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.
Link:

48. Sea Surface Temperature (SST) algorithm
Passive remote sensing: INFRARED
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

49. 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).
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.

50. Passive remote sensing: INFRARED

51. Passive remote sensing: INFRARED

52. Passive remote sensing: INFRARED

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

54. Altimetry Jason Links: http://sealevel.jpl.nasa.gov
Active remote sensing: MICROWAVE
Altimetry
Jason
Links:

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

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

57. Altimetry Satellite altimetry to measure marine geostrophic currents
Active remote sensing: MICROWAVE
Altimetry
Satellite altimetry to measure marine geostrophic currents
Links:

58. Sea Surface Height (SSH) in the Caribbian Seacm

59. Synthetic Aperture Radar (SAR)
Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
SAR imaging (MW through clouds)
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. Synthetic Aperture Radar (SAR)
Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
Strait of Gibraltar : Surface signature of internal waves

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

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

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

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. Satellite versus in situ measurement: advantages and disadvantages
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. Remote Sensing
Mooring and Tripods
In-situ Non-stationary Platforms

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