Remote Sensing:

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Remote Sensing

• Creating GIS data from
• digital imagery

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• Remote Sensing Defined
• A means of acquiring information using airborne
  equipment and techniques to determine the
  characteristics of an area. Aerial photographs
  from aircraft and satellite are the most common
  form of remote sensing.
• "Remote sensing is the science of deriving
  information about the earth's land and water
  areas from images acquired at a distance. It
  usually relies upon measurement of
  electromagnetic energy reflected or emitted from
  the features of interest (Campbell 1987)."

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• Types of GIS data created from remotely sensed
  imagery
• Land Cover Maps (physical material on earths
  surface)
• Agricultural Maps (Type of Land Cover)
• Digital Elevation Models
• -Delineate Watersheds, Streams Rivers, Flood
  Plains
• -Create Slope and Shaded Relief Maps
• Stream/Water Body Temperature

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Multi-Spectral Remote Sensing

• Sensors, typically on Satellites or Airplanes,
  record the intensity of EMR from the sun as it is
  reflected and emitted from the earths surface.
• These sensors record EMR (continuous data) into
  discrete ranges of the Spectrum called channels
  or bands.
• Most Sensors operate in the visible to
  near-infrared portion of the electro magnetic
  spectrum.

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The Electromagnetic Spectrum
Units Micron 10-6m Nanometer 10-9m
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Spectra of earth materials When EMR from the sun
reaches the earth surface, it is transmitted -
transmittance absorbed - absorbance reflected
- reflectance The nature of how the earth
materials transmit, absorb or reflect the solar
EMR is called spectral signature of an object.
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The Solar Spectrum at the Surface
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Spectral Signatures The Principle of Spectral
Remote Sensing
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Spatial Resolution Characteristics
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Mixels
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Resolution and Mixing
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Resolution Comparison Landsat 7 (30m) vs. Ikonos
(1m)
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Landsat Image of Greater Puget Sound
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• Satellite Example Landsat
• Landsat 1 was launched on July 23, 1972.
• Landsat 7 is most current and was launched on
  April 15, 1999.
• Numerous technological improvements occurred with
  each new sensor, including improved spectral and
  spatial resolution. In general, comparable
  temporal data exits as far back as March 1, 1984-
  launch of Landsat 5.
• Landsat 7 has a 16 day between scene interval.

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• Benefits of Landsat
• Regional Coverage (large per scene spatial
  extent)
• Relatively inexpensive
• Seasonal/Temporal Availability
• Multiple bands facilitate accurate
  classifications
• Data Consistency(?)

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Spectral Resolution Characteristics
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• Types of errors and effects in digital images
• geometric distortions
• variations in solar illumination angle
• atmosphere (scattering absorption)
• topographic effect

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• Effects of Noise in multi-temporal imagery
• An objects spectral response as recorded by the
  sensor
• will be different than if recorded at ground
  level.
• Material that has remained unchanged over time
• will have some degree of spectral variability
  from image to
• image.
• Analysts often attempt to correct images so that
  they better represent
• an objects true spectral response at a given sun
  incident angle. A data
• normalization procedure will typically attempt to
  account for all
• four factors mentioned on the previous slide.

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Atmospheric Effects
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Example Topographic Effect
Image data
Shaded relief model
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Image classification Image classification is the
process of creating a meaningful digital
thematic map from a image data set (information
extraction). Supervised classification
classes from known cover types. Unsupervised
classification classes by algorithms that
search the data for similar pixels.
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• Supervised classification
• Training class selection (training
  areas/classes)
• Generating statistical parameters (spectral
  signatures)
• of training classes
• Data classification
• Evaluation and refinement

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Concluding Remarks