IoE 184 - The Basics of Satellite Oceanography. 3. Remote Sensing of the Sea

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Lecture 3 Remote Sensing of the Sea
IoE 184 - The Basics of Satellite Oceanography.
3. Remote Sensing of the Sea
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Remote sensing of the sea includes
1. Sensor calibration
2. Atmospheric correction
3. Positional registration
4. Oceanographic sampling for "sea truth"
5. Image processing
6. Oceanographic applications of satellite remote
sensing
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3. Remote Sensing of the Sea
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Compare satellite remote sensing and the
traditional sources of oceanographic information

• Remote sensing is better than traditional
  methods
• Synoptic view, because satellites collect huge
  amount of information much exceeding the data
  collected by contact oceanographic observations
• Satellite observations cover wide areas of the
  World Ocean hardly accessible for field
  observations.
• Problems of remote sensing
• The parameters measured by the satellites cannot
  be directly attributed to traditionally measured
  oceanographic characteristics
• Some satellite observations (ocean color and
  infrared) are more sensitive to unfavorable
  meteorological conditions than traditional
  oceanographic methods.

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1. Sensor calibration
Each oceanographic equipment should be calibrated
both before and after deployment. In the case of
satellites we need to take into account the
following

• The stress of launch
• High vacuum of outer space
• 3. The power limitations on board the satellite,
  often resulting in gradual deterioration in the
  power supply on the satellite
• 4. No opportunity of retrieving the instrument
  for periodic recalibration in the laboratory.

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1. Sensor calibration
On some scanners, part of the scan views a
reference target, a lamp of known brightness for
the visible wavelength scanners, or a black body
of measured temperature for thermal IR sensors.
In this way gradual drift of the sensor can be
detected and corrections made in the data
analysis.
Some sensors use the moon as a natural object
with constant optical characteristics.
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2. Atmospheric correction
The sensors look at the ocean surface through
another medium, the atmosphere. The atmosphere is
opaque to electromagnetic radiation at many
wavelengths, and there are only certain
wavelengths through which radiation may be fully
or partly transmitted.
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2. Atmospheric correction

• The following compounds of the atmosphere change
  its transmittance
• Gas molecules themselves
• Water vapor
• Aerosols
• Suspended particles of dust
• Water droplets in the form of clouds

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2. Atmospheric correction
40 of sunlight is reflected by clouds 20 of
sunlight is absorbed by the atmosphere 40 of
sunlight is absorbed by Earths surface
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2. Atmospheric correction
Ray 1 - the useful signal Ray 2 - the radiation
leaving the sea which is absorbed by the
atmosphere Ray 3 - the radiation, which is
scattered by the atmosphere out of the sensor
field of vision. Ray 4 - the energy emitted by
the constituents of the atmosphere Ray 5 - the
energy reflected by scattering into the field of
vision of the sensor Ray 6 - the energy which
previously left the sea surface but from outside
the field of view.
Atmospheric pathways of electromagnetic radiation
between the sea and the satellite sensor.
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2. Atmospheric correction
The ocean area within the IFOV emits rays
123 Rays 4, 5, and 6 reach the sensor without
having left the sea surface in the field of view,
and therefore constitute extraneous "noise" on
top of the signal. The sensor receives rays
1456 The complete atmospheric correction
should result in the sum of rays 123.  
Atmospheric pathways of electromagnetic radiation
between the sea and the satellite sensor.
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2. Atmospheric correction
In the case of optical sensors Ray 2 is absent.
On the contrast, in thermal IR sensors Ray 2 is
important the cool atmosphere absorbs radiation
(Ray 2) and re-emits it with lower temperature
characteristics (Ray 4).
Atmospheric pathways of electromagnetic radiation
between the sea and the satellite sensor.
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2. Atmospheric correction
Increased atmospheric pathlength resulting from
oblique viewing. The oblique view results in
looking through longer path length of atmosphere
than for nadir viewing. This feature is used in
atmospheric correction. By viewing the same piece
of sea twice, through different lengths of
atmosphere, an objective estimate of atmospheric
effect can be made.
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2. Atmospheric correction

• The main strategies of atmospheric correction
•  
• No separate attempt of atmospheric correction,
  instead we calibrate each scene with ground data.
• A universal atmospheric correction based on an
  average model of atmospheric effects.
•  
• Using different wavelengths, assuming that
  certain channels are unlikely to have any
  upwelling radiation from the sea. In this way we
  process each pixel of the image.
•  
• An atmospheric (microwave) sounding sensor can be
  mounted on the same satellite as an oceanographic
  sensor.

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2. Atmospheric correction
Without atmospheric correction, each scene can be
calibrated with ground data, but the slope of
correlation for each scene is unique.
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2. Atmospheric correction
- Cloud detection
Cloud cover is a main obstacle for satellite
imagery in visible and infrared spectral bands.
Clouds are transient atmospheric features that
consist of small ice and liquid water particles
with dimensions from under a micrometer to a few
millimeters, resulting from water condensation
and freezing.
Cloud properties vary with height. In the visible
and infrared part of spectrum, the liquid water
and ice crystals contained in the clouds scatter
and absorb radiation, so that thick clouds make
it impossible to view the surface. At any time,
clouds cover almost two-thirds of the globe.
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2. Atmospheric correction
- Cloud detection
In both ocean color and SST, the first step of
the procedure of atmospheric correction is to
determine if every oceanic pixel in the image
under investigation is cloud-free.
The SeaWiFS (8 optical channels) cloud detection
is most primitive. It is assumed, that the
water-leaving radiance of near-infrared
wavelength is near zero. As such, the pixels with
a reflectance greater than a preset threshold are
classified as clouds.
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2. Atmospheric correction
- Cloud detection
In AVHRR and MODIS the cloud detection is based
on two factors

• the clouds are colder and more reflective than
  the ocean surface
• for spatial scales of order 100 km, the ocean
  surface, in contrast to clouds, is nearly uniform
  in temperature and reflectance.
• Three kinds of tests are used
• Threshold tests eliminate pixels that are more
  reflective or colder than the ocean surface.
• 2) Uniformity tests examine the variance of
  temperature or reflectance in a rectangular array
  of pixels.
• 3) The retrieved SSTs are compared with
  climatology and with SSTs retrieved using
  alternative algorithms e.g., according to the
  unreasonableness test, SST must be within the
  range from -2ºC to 35ºC.

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3. Positional registration
Positional registration means the identification
on a map of the place to which a remote-sensed
measurement refers. The problem of knowing where
the satellite was when a measurement was made
depends on type of sensor, first of all its
spatial resolution.
An approximate estimation of the satellite
position can be obtained from the time of
observation. However, the precision of this
estimation is within few kilometers.
AVHRR radiometer on NOAA satellite
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3. Positional registration
Positional registration means the identification
on a map of the place to which a remote-sensed
measurement refers. The problem of knowing where
the satellite was when a measurement was made
depends on type of sensor, first of all its
spatial resolution.
An approximate estimation of the satellite
position can be obtained from the time of
observation. However, the precision of this
estimation is within few kilometers.
AVHRR radiometer on NOAA satellite
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3. Positional registration
Often the "ground control points" are used.
However, the ground control points can be used
mostly in the coastal zones. The problem of
distortion of the image results from oblique
viewing of the spherical earth surface. During
processing each pixel of the image should be
attributed to geographical coordinates.
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3. Positional registration
In recent satellites more precise estimation of
the position is obtained using the signals of
GPS (Global Positioning System) satellites.
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3. Positional registration
Most sophisticated method of position
registration is used in TOPEX/Poseidon
radar-altimeter. It is based on Doppler effect.
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3. Positional registration
DORIS system determines the position of
TOPEX/Poseidon satellite orbit to within a few
centimetres.
The technique used (known as orbit
determination), consists of locating a satellite
in relation to about fifty ground control points
on the Earth's surface.
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4. Oceanographic sampling for "sea truth"
The main problem is that in general the
remote-sensed characteristics of the sea change
on a much shorter time scale than those of the
land. Using for this purpose the overpasses of
the satellite should be done carefully. In some
cases it is impossible (e. g., altimeter
measuring swell waves). In other case (SST or
water color measured few hours one after another)
we can compare overpasses of the satellites.
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4. Oceanographic sampling for "sea truth"
The strategy of collecting of samples is very
important. The samples must span as wide range of
data values as possible. Typically, transects
across the gradients are used.
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4. Oceanographic sampling for "sea truth"
Spatial resolution of the sensor is important as
compared with spatial variability of the measured
parameter, because the value measured within a
point may not be representative of the average
parameter within the whole pixel measured by the
satellite.
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4. Oceanographic sampling for "sea truth"
Comparing satellite observations and sea truth
data we should keep in mind that the data
collected by contact methods can be not more
precise than remotely-sensed data. In practice,
the satellite data and sea truth data are
nothing but two data arrays collected by
different methods.
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5. Image processing
Level of data processing
Level 0 - Level 1 - Level 2 - Level 3
- Level 4 -
Raw data received from satellite, in standard
binary form Image data in sensor coordinates,
containing individual calibrated
channels Derived oceanic variable,
atmospherically corrected and geolocated, but
presented in sensor coordinates Composite
images of derived ocean variable resampled onto
standard map base and averaged over a certain
time period (may contain gaps) Image
representing an ocean variable averaged within
each grid cell as a result of data analysis,
e.g., modeling.
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5. Image processing
The raw information measured by the sensor
onboard the satellite (raw radiance counts from
all bands as well as spacecraft and instrument
telemetry) is transmitted by radio-signal and
received by the ground station. These data are
called Level 0 data.
Level-1 Data Products Level-1 products contain
all the Level-0 data, appended calibration and
navigation data, and instrument and selected
spacecraft telemetry that are reformatted and
also appended.
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5. Image processing
The radiances are measured at different
wavebands, called channels. Different channels
provides information on different properties of
the Earth surface. One method of analysis is
when the images observed at different wavebands
can be combined to result in a true color
image.
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5. Image processing
The radiances are measured at different
wavebands, called channels. Different channels
provides information on different properties of
the Earth surface. One method of analysis is
when the images observed at different wavebands
can be combined to result in a true color
image.
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5. Image processing
At this MODIS image of the Mississippi River
delta you can see clouds, coastline, river, the
zones of phytoplankton bloom and pollution in the
coastal ocean, etc.
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5. Image processing
True color images are an important source of
information about natural disasters like these
wildfires in California in autumn 2003.
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5. Image processing
Level-2 Data Products Each pixel of Level-2 data
contains geophysical values (e.g., sea surface
temperature, surface chlorophyll concentration,
etc.) estimated from the radiances measured by
the satellite Each Level-2 product is generated
from a corresponding Level-1 product. Level-2
data are derived from the Level-1 raw radiance
counts by applying the sensor calibration,
atmospheric corrections, and the algorithms
specific for each kind of geophysical value
(e.g., bio-optical algorithms for water color
data, etc.).
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5. Image processing
Example of Level 2 data MODIS Sea Surface
Temperature, 2000 December 6, 1705
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5. Image processing
Example of Level 2 data MODIS Surface
Chlorophyll Concentration, 2000 December 6, 1705
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5. Image processing
Example of Level 2 data MODIS Total Suspended
Solids , 2000 December 6, 1705
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5. Image processing

• Level-3 Data Products
• Level-3 means geophysical parameters observed
  during a certain period and interpolated on a
  global grid. For The SeaWiFS the periods of Level
  3 data are
• one day,
• 8 days,
• a calendar month, or
• a calendar year.
• For other satellites these periods can be
  different.
• The spatial resolution of the global grid can be
• 1 degree (360 x 180 grid)
• 18 km (2048 x 1024 grid) - MC SST
• 9 km (4096 x 2048 grid) - SeaWiFS, Pathfinder SST
  v.1-4
• 4.5 km (8192 x 4086 grid) - MODIS, Pathfinder SST
  v.5.

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5. Image processing
SeaWiFS Level 3 chlorophyll image, 1997 December
8 (daily)
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5. Image processing
SeaWiFS Level 3 chlorophyll image, 1997 December
11 18 (8-day)
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5. Image processing
SeaWiFS Level 3 chlorophyll image, 1997 December
1 31 (monthly)
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5. Image processing
The satellite data are disseminated via
internet. Users select the images in online
databases and either download or order data
files. Typical satellite images are very big
(e.g., one MODIS image is about 250-300 Mb). To
enable the users to have a brief look at each
image before selecting it low-resolution browse
images are often produced. If the area of
interest is free from clouds, the user orders the
data file, downloads it, and works with it using
appropriate software.
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5. Image processing
Data format. Many types of satellite information
are stores in Hierarchical Data Format
(HDF). HDF is a cross-platform file format for
storing a wide variety of scientific data. This
public-domain open standard was created by the
National Center for Supercomputing Applications
at the University of Illinois Urbana-Champaign
(NCSA). A typical HDF file might contain a
dataset, data table, descriptions of data, images
produced from the data and other related
information. It can be processed using special
software, such as Noesys, MATLAB, IDL, etc.
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5. Image processing
All good software packages are commercial. To
understand the basic features of HDF files you
can use free program HDFExplorer from the
Internet site http//www.space-research.org/ 1.
Select ltltDownloadgtgt 2. Fill out the form with
your name, etc. 3. Click ltltSubmitgtgt 4. Store
the HDFExplorerSetup.exe file on the hard drive
of your computer 5. Double-click
HDFExplorerSetup.exe to install HDFExplorer.
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5. Image processing
Download from the site www.obee.ucla.edu/test/fa
culty/nezlin From the section Lecture 3 Remote
Sensing of the Sea two example
files MO36MWN2.sst4.zip and C1978341012416.L2_B
RS.hdf.zip Uncompress these files using WinZip
and open them in HDFExplorer. On the left you see
the content of the file. Clicking expand the
structures.
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5. Image processing
MO36MWN2.sst4.zip contains data on sea surface
temperature (SST4) collected by MODIS Terra
satellite.
The dataset sst4_mean contains the data array.
Double-click it to see the content. Let us
analyze the content of the dataset at the example
of one grid node (x1 y150). The grid node
with column 1 and row 150 contains the value
31706. To understand its meaning double-click on
the records Scale_type, Slope and Intercept.
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5. Image processing
You see the following Scale_type YSlope x
Intercept Slope 0.01 Intercept -300
31706 0.01 300 17.06 Double-click Units
and Name. Now you see that it is the
temperature of the ocean surface measured in
Degrees C.
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5. Image processing
Double-click Start Year, Start Day, End Year, End
Day. You see that the data were collected from
2000, Julian Day 336 (December 1) to 2000 Julian
Day 344 (December 9). Double-click Northernmost
Latitude Southernmost Latitude Westernmost
Longitude Easternmost Longitude.
You can see that the data array covers the entire
Earth surface from 90S (i.e., -90) to 90N and
from 180W (i.e., -180) to 180E. Number of
Columns and Number of Lines indicate the grid
size 1024 x 512.
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5. Image processing
HDFExplorer cannot transform 2-byte arrays into
images, but other software can help you to make a
graphical representation of the HDF file content.
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5. Image processing
Open the file C1978341012416.L2_BRS.hdf and
expand the structures clicking .
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5. Image processing
This file contains CZCS chlorophyll image the
snapshot was obtained in the western Pacific.
8-bit Raster Image 1 contains the image of
surface chlorophyll concentration. 8-bit Raster
Image 2 indicates the snapshot location.
Point the mouse cursor at the Raster Image 1,
right-click and select View. You see the values
from 0 to 255, i.e. bytes. Point the mouse
cursor at the Raster Image 1, right-click and
select Image View. You see the graphic
representation of the data array made using the
Image Palette.
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5. Image processing
The records Start Year, Start Day, End Year, End
Day indicate that the image was obtained in 1978,
Julian Day 341 (December 7). Northernmost
Latitude, Southernmost Latitude, Westernmost
Longitude and Easternmost Longitude indicate the
approximate location of the image.
Latitude and Longitude structures indicate the
exact geographic locations of selected pixels of
the image. These arrays can be used by the
software like MATLAB Mapping Toolbox to produce
the image in any geographical projection you
wish.
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5. Image processing
Double-click the records Scaling
Equation, Base, Slope, and Intercept. You
see Base 10 Slope 0.012 Intercept -1.4
Scaling Equation Base((Slopebrs_data)
Intercept) chlorophyll a We can check some
values within the range 0-255 and see that the
brs_data 100 results in 0.630957, the
brs_data 200 results in 10.00000, etc.
Double-click Parameter and Units. You see the
description of the data chlorophyll a
concentration and mgm-3.
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Oceanographic applications of satellite remote
sensing include
1. Visible wavelength "ocean color" sensors
2. Sea surface temperature from infrared scanning
radiometers
3. Passive microwave radiometers
4. Satellite altimetry of sea surface topography
5. Active microwave sensing of sea-surface
roughness
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1. Visible wavelength "ocean color" sensors
These sensors operate in the visible part of the
electromagnetic spectrum, measuring
electromagnetic radiation emitted by the sun and
reflected by land and ocean surface.
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1. Visible wavelength "ocean color" sensors
The color of the Earth surface, especially the
color of the ocean, results primarily from
biological processes. Measuring the absorption
and backscattering characteristics of ocean
surface, we can estimate the concentrations of
different kinds of matter suspended in seawater,
including phytoplankton cells.
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2. Sea surface temperature from infrared
radiometers
Infrared sensors measure electromagnetic
radiation within the band 1-30 µm, emitted by the
ocean surface and resulting from the temperature
of the upper sea layer.
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2. Sea surface temperature from infrared
radiometers
The near-infrared and infrared radiation is
processed to sea surface temperature (SST). The
most important SST sensors are Advanced Very High
Resolution Radiometer (AVHRR) on NOAA satellites,
MODIS, GOES geostationary satellites, and some
others.
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3. Passive microwave radiometers
Passive microwave radiometers operate at
electromagnetic wavelengths 1.5300 mm (i. e.,
the frequency 1200 GHz). Their advantage is
the comparatively long wavelength, which is not
sensitive to scattering by the atmosphere or
aerosols, haze, dust, or small water particles in
clouds. So, the microwave sensors are all-weather
devices. This principle advantage is countered by
the fact that thermal emission is very weak at
these longer wavelengths. To overcome noise
levels a large field of view must be received
that results in low spatial resolution (25150
km). So, these observations are used for studies
of heat balance of the ocean. The emissivity of
the sea at microwave frequencies varies with the
dielectric properties of sea water (including
salinity) and the surface roughness. Hence, the
development of this technique in future can
enable the measurements of surface salinity.
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4. Satellite altimetry of sea surface topography
Satellite altimeters are radars, which transmit
short pulses toward the earth beneath them. The
return time of the pulse after reflection at the
earth's surface is measured, and this yields the
height of the satellite. The most important are
ERS-1, ERS-2, TOPEX/Poseidon, and Jason-1
satellites.
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5. Active microwave sensing of sea-surface
roughness
Synthetic Aperture Radar (SAR)
Synthetic aperture radar (SAR) is based on the
comprehensive analysis of contribution from
individual points to the signal received when the
sensor is at a particular point. The result is
very high resolution.
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5. Active microwave sensing of sea-surface
roughness
Synthetic Aperture Radar (SAR)
SAR images enable the analysis of small-scale and
mesoscale eddies, river plumes, oil slicks, ice
packs, etc.
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IoE 184 - The Basics of Satellite Oceanography.
3. Remote Sensing of the Sea