Remote sensing technique
in coastal studies
Elena Mauri
OGS, Istituto Nazionale di Oceanografia e
Geofisica Sperimentale, Trieste, Italy
Lecture 19
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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.)
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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
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Electromagnetic spectrum
Visible (400 nm - 1000 nm, VIS)
Infrared (~ 10,000 nm, IR)
Microwave (MW)
active (3-30 GHz)
Links:
http://www.biogeorecon.com/remote.htm
http://www.eeb.ucla.edu/test/faculty/nezlin/SatellitesAndSensors.htm
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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.
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Passive remote sensing
Sun emission
Earth emission
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Passive remote sensing
Effects of Atmosphere on the
electromagnetic spectrum
Links:
http://www.gisdevelopment.net/tutorials/tuman008.htm
http://www.crisp.nus.edu.sg/~research/tutorial/atmoseff.htm
http://earthobservatory.nasa.gov/Library/RemoteSensingAtmosphere/
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Satellite orbits
Geostationary
Near-Polar orbiting
Sun-synchronous
Links:
http://www.rap.ucar.edu/~djohnson/satellite/coverage.html
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Satellite orbits
Polar-orbiting and geostationary Satellites
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Passive and Active
Satellite Remote Sensing
Passive (VIS, IR, MW)
Active (MW)
Links:
http://www.csc.noaa.gov/products/nchaz/htm/ccap5.htm
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Satellite sensors
Scanning
Pushbroom
Instantaneous Field of View (IFOV)
Satellite Sampling
Links:
http://ccrs.nrcan.gc.ca/resource/tutor/fundam/chapter2/08_e.php
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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:
http://www.fas.org/irp/imint/docs/rst/Front/tofc.html
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Sunlight propagation, refection and
absorption by atmosphere and ocean
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Passive remote sensing: VISIBLE
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.
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Passive remote sensing: VISIBLE
Remote sensing reflectance
(Rrs)
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).
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Passive remote sensing: VISIBLE
Remote Sensing Reflectance
and inherent optical properties
Rrs(λ)=const
bb(λ)
bb(λ) + a(λ)
Where:
a(λ)=aw(λ)+aph(λ)+ad(λ)+acdom(λ)
bb(λ)=bbw (λ)+bbp (λ)
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.
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Passive remote sensing: VISIBLE
Absorption
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
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components.
Passive remote sensing: VISIBLE
Back-scattering
blue green red
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
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maximum in red (C).
Passive remote sensing: VISIBLE
Empirical Chlorophyll algorithms
Reference
Algorithms for <Chl> calculation
Ratio R
<chl> = 10^(a(1) + a(2)*R + a(3)*R2 + …
SeaWiFS
<chl> = 10^(a(1) 3+ a(2)*R + a(3)*R2 + 4 R = log10(Rrs490/Rrs555)
… a(4)*R
a(4)*R
+ a(5)*R )
3) +a(5))
OC2v2
*R4 )
O’Reilley
(2000)
a = [0.2974, -2.2429, 0.8358, -0.0077, 0.0929]
SeaWiFS
OC4v4
<chl> = 10^(a(1) + a(2)*R + a(3)*R2 +
a(4)*R3) +a(5) *R4 )
CZCS GPs
Gordon et al.
(1983)
C13 = 10^(0.053+1.71* R1)
R1 = log10(Lwn550/Lwn443)
Rrs555R2 = log10(Lwn550/Lwn520)
C23 = 10^(0.522+2.44* R2)
<chl> + P = C13; if C13 > 1.5 mg m-3 then P = phaeopigments
<chl> + P = C23
(<chl> + P ) = 1.3404*<chl> 0.983
where
R = log10 Rrs490
(
OCTS-C
<chl> = -2.2429,
10^(a(1) + a(2)*R)
a = [0.2974,
0.8358,
OCTS-C
a = [-0.55006, 3.497]
0.0929]
(1996)
Morel (1988)
MODIS
R = log10(Rrs443>Rrs490>Rrs510/Rrs555)
1/e
empirical
coefficients
<chl> = ((Kd490-K
w490)/X)
)
R = log10((Lwn520
-0.0077,
- + Lwn565)/Lwn 490)
Kd490 = 0.02+0.1*(R)-1.29966
R = Rrs443/ Rrs555
Kw490 = 0.0217
X=0.069, e=0.702
<chl> = 10^(a(1) + a(2)*R + a(3)*R2 +
a(4)*R3) +a(5) *R4 )
R = log10(Rrs443>Rrs488/Rrs551)
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Passive remote sensing: VISIBLE
MODIS
Moderate-resolution Imaging Spectroradiometer
•is on board of two satellite: Terra (EOS AM) satellite (1999),
Orbit
705 km, 10:30 a.m. descending node (Terra) or 1:30 p.m. ascending node (Aqua), sunAQUA (EOS PM) satellite (2002).
synchronous, near-polar, circular
Specifications
Scan Rate
20.3 rpm, cross track
Swath are 36 spectral
2330 km (cross bands
track) by 10 km
(along track at in
nadir)wavelength from 0.4 μm
• there
ranging
to 14.4Dimensions
µm and at varying spatial resolutions (2 bands at 250 m,
Telescope
17.78 cm diam. off-axis, afocal (collimated), with intermediate field stop
5 bands
at 500 m
and 29 bands at 1 km).
Size
1.0 x 1.6 x 1.0 m
Weight
228.7 kg
Design Life
6 years
•together
the instruments
image the entire Earth every 1 to 2
Data Rate
10.6 Mbit/s (peak daytime); 6.1 Mbit/s (orbital average)
days.
Spatial Resolution
250 m (bands 1-2) 500 m (bands 3-7) 1000 m (bands 8-36)
•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.
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MODIS spectral bands and athmospheric
effects
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Passive remote sensing: VISIBLE
Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
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Passive remote sensing: VISIBLE
Ocean Color
Phytoplankton pigment (chlorophyll-a) concentration.
The global biosphere!
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Passive remote sensing: VISIBLE
MODIS chlorophyll concentration
around Tanzania
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Ocean Color
Passive remote sensing: VISIBLE
Spatial and seasonal (monsoon) variability of the
chlorophyll-a concentration in NW Atlantic and Indian Oceans
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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 37
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.
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Passive remote sensing: VISIBLE
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.
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Passive remote sensing: VISIBLE
Passive remote sensing: VISIBLE
Landsat 7
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Passive remote sensing: VISIBLE
Landsat 7
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MODIS True color (250 m resolution)
Phytoplankton bloom South
Atlantic Ocean (off
Argentina coast)
Coccolotophorids bloom in
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Bering Sea
True color satellite images of Italian Seas
(non-dusty and dusty cases)
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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 4meter 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
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days off-nadir and 144 days for true-nadir
Passive remote sensing: VISIBLE
Bahamas
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Passive remote sensing: VISIBLE
Bora Bora
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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: http://www.eeb.ucla.edu/test/faculty/nezlin/SST.htm
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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
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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 49
logarithmic scale.
Passive remote sensing: INFRARED
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Passive remote sensing: INFRARED
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Passive remote sensing: INFRARED
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Passive remote sensing: INFRARED
Sea Surface Temperature (SST)
Gulf Stream
Composite SST images of NW Atlantic SST constructed from AVHRR53data
Active remote sensing: MICROWAVE
Altimetry
Jason
Links:
http://sealevel.jpl.nasa.gov
http://www.aviso.oceanobs.com/
http://ibis.grdl.noaa.gov/SAT/SAT.html
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Altimetry
Active remote sensing: MICROWAVE
World’s Ocean bathymetry (geoid)
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Active remote sensing: MICROWAVE
Altimetry
Satellite altimetry can be used to measure marine geostrophic currents
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Active remote sensing: MICROWAVE
Altimetry
Satellite altimetry to measure marine geostrophic currents
Links:
http://oceanworld.tamu.edu/resources/ocng_textbook/chapter10/chapter10_03.htm
http://www.eeb.ucla.edu/test/faculty/nezlin/Altimetry.htm
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Sea Surface Height (SSH) in the
Caribbian Sea
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cm
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.
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Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
Strait of Gibraltar : Surface signature of internal waves
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Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
French Riviera : Oil Slick
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Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
Gulf of Naples, Italy: Circulation structures
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Active remote sensing: MICROWAVE
Synthetic Aperture Radar (SAR)
Ship and its wake
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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
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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
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Mooring and Tripods
Remote Sensing
In-situ Non-stationary Platforms
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Thanks for your
attention
and for your very
warm hospitality
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