Remote Sensing

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REMOTE SENSING
By JWAN M ALDOSKI Geospatial Information
Science Research Center (GISRC), Faculty of
Engineering, Universiti Putra Malaysia, 43400
UPM Serdang, Selangor Darul Ehsan. Malaysia.
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Preprocessing

• Digital Image Processing of satellite images can
  be divided into
• Pre-processing
• Enhancement and Transformations
• Classification and Feature extraction
• Preprocessing consists of radiometric correction
  and geometric correction

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Preprocessing

• Radiometric Correction removal of sensor or
  atmospheric 'noise', to more accurately represent
  ground conditions - improve imagefidelity
• correct data loss
• remove haze
• enable mosaicking and comparison
• Geometric correction conversion of data to
  ground coordinates by removal of distortions from
  sensor geometry
• enable mapping relative to data layers
• enable mosaicking and comparison

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Radiometric correction modification of DNs
Errors
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Radiometric correction

• Radiometric correction is used to modify DN
  values to account for noise, i.e.  contributions
  to the DN that are a result of
• the intervening atmosphere
• b. the sun-sensor geometry
• c. the sensor itself errors and gaps

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Radiometric correction

• We may need to correct for the following reasons
• Variations within an image (speckle or striping)
• b. between adjacent / overlapping images (for
  mosaicing)
• c. between bands (for some multispectral
  techniques)
• d. between image dates (temporal data) and sensors

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Errors Sensor Failure Calibration
Sensor problems show as striping or missing lines
of data Missing data due to sensor failure
results in a line of DN values - every 16th line
for TM data .. As there are 16 sensors for each
band, scanning 16 lines at a time (or 6th
line  for MSS).
MSS 6 line banding raw scan
TM data 16 line banding
MSS 6 line banding - georectified
Sample DNs shaded DNs are higher
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Landsat ETM scan line corrector (SLC) failed
May 31 2003http//landsat.usgs.gov/products_slc_o
ff_data_information.php
SLC compensates for forward motion of the scanner
during scan
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Atmospheric Interference - haze
Lower wavelengths are subject to haze, which
falsely increases the DN value. The simplest
method is known as dark object subtraction which
assumes there is a pixel with a DN of 0 (if there
were no haze), e.g. deep water in near infra-red.
An integer value is subtracted from all DNs so
that this pixel becomes 0.
http//geology.wlu.edu/harbor/geol260/lecture_note
s/Notes_rs_haze.html
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Atmospheric Interference clouds
clouds affect all visible and IR bands, hiding
features twice once with the cloud, once with
its shadow. We CANNOT eliminate clouds, although
we might be able to assemble cloud-free parts of
several overlapping scenes (if illumination is
similar), and correct for cloud shadows 
(advanced). Only in the microwave, can
energy penetrate through clouds.
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Advanced slide Reflectance to Radiance
Conversion
DN reflectance values can be converted to
absolute radiance values. This is useful when
comparing the actual reflectance from different
sensors e.g. TM and SPOT, or TM versus ETM
(Landsat 5 versus 7) DN aL b       where a
gain and b n offset The radiance value (L) can
be calculated as L Lmax - LminDN/255
Lmin where Lmax and Lmin are known from the
sensor calibration. This will create 32 bit
(decimal) values.
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Geometric Correction Corrected image scene
orientation map
Uncorrected data path
Pixels and rows
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Why is rectification needed

• Raw remote sensing data contain distortions
  preventing overlay with map layers, comparison
  between image scenes, and with no geographic
  coordinates
• To provide georeferencing
• To compare/overlay multiple images
• To merge with map layers
• To mosaic images
• e.g. google maps / google earth
• Much imagery now comes already rectified
  YEAH !!

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Image distortions
In air photos, errors include topographic
and radial displacement airplane tip, tilt
and swing (roll, pitch and yaw). These are less
in satellite data due to altitude and stability.
The main source of geometric error in satellite
data is satellite path orientation (non-polar)
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Sources of geometric error (main ones in bold)

• Systematic distortions
• Scan skew ground swath is not normal to the
  polar axis along with the forward motion of the
  platform during mirror sweep
• Mirror-scan Velocity and panoramic distortion
  along-scan distortion (pixels at edge are
  slightly larger). This would be greater for
  off-nadir sensors.
• Earth rotation earth rotates during scanning
  (offset of rows).... (122 pixels per Landsat
  scene)
•  
• b. Non-systematic distortions
• Topography requires a DEM, otherwise 6 pixel
  offset in mountains
• Correcting with a DEM involves orthorectification
  
• Altitude and attitude variations in satellite
  these are minor

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Geocorrection
Rectification assigning coordinates to (6)
known locations - GCPs GCP
Ground Control Point Resampling - resetting
the pixels (rows and columns) to match the GCPs

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Rectification

• Data pixels must be related to ground locations,
  e.g. in UTM coordinates
• Two main methods
• Image to image (to a geocorrected image)
• .... to an uncorrected image would be
  'registration' not rectification
• Image to vectors (to a digital file)....
•  
• (black arrows point to known locations
• - coordinates from vectors or images)
• Ortho-rectification this process (since 2000)
  enables the use of a DEM to also take into
  account the topography

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Resampling methods
New DN values are assigned in 3 ways   a.Nearest
Neighbour Pixel in new grid gets the value of
closest pixel from old grid retains original
DNs   b. Bilinear Interpolation New pixel gets a
value from the weighted average of 4 (2 x 2)
nearest pixels smoother but synthetic  c.
Cubic Convolution (smoothest) New pixel DNs are
computed from weighting 16 (4 x 4) surrounding
DNs
http//www.geo-informatie.nl/courses/grs20306/cour
se/Schedule/Geometric-correction-RS-new.pdf
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Resampling pixel
sizePreviously during resampling stage,
pixels were rounded to match UTM grid and
DEMsLandsat MSS 80m raw pixels -gt 50m
corrected pixelsLandsat TM 30 (28.5) m -gt
25mBC TRIM DEM was built to 25m to match
Landsat TM dataNew millenium software can
handle layers with different resolution, so
downloaded TM scenes are mostly 30m pixels
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Resampling
http//www.geo-informatie.nl/courses/grs20306/cour
se/Schedule/Geometric-correction-RS-new.pdf Good
rectification is required for image registration
no movement between images
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Canadian Arctic mosaic
See also google maps, lrdw.ca/imap etc..
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Northern Land Cover of Canada Circa 2000
http//ccrs.nrcan.gc.ca/optical/landcover2000_e.ph
p
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Projections and reprojection

• Global data might be downloaded as geographic
  (lat/long) or UTM zone
• BC data as UTM or BC Albers
• GIS and DIP software can display different
  projections on the fly
• but require reprojection for analysis and data
  overlay
• Reprojecting vectors simply reassigns
  coordinates to points
• Reprojecting rasters involves resampling every
  pixel
• (using nearest neighbour,
  bilinear or cubic convolution)

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Release of new ASTER Global DEM (GDEM v2) 3 Oct
2011
Available in Geographic (Lat/Long) or UTM zone
http//www.nasa.gov/topics/earth/features/aster201
11017.html
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Ellipsoids and Datums

• Data will also have a datum
• NAD27 North American datum 1927
• NAD83 North American Datum 1983
• There is a 100-200 metre difference between NAD27
  and NAD83
• NADCON83 NAD for continental USA
• NAD83 Canada based on Canadian landmass
• WGS84 World Geodetic System 1984
• There is very little difference between WGS84
  and NAD83(flavours)
• But .. AIEEEEEEEEEE !

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Reprojection error stripes
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Reprojection geographic (WGS84) to UTM / Albers
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Striping from projecting SRTM data, from Lat/long
to UTM Chile
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Now for something completely different perfect
registration needed.
100 Marilyn Monroe -gt 100 Margaret
Thatcher
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• Thank you