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GEOGRAPHIC INFORMATION SYSTEM (GIS) AND REMOTE SENSING

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REMOTE SENSING Lecture 4 Zakaria ... the most distinctive characteristic is the energy ... spectral responses measured by the remote sensors are what permit us to ... – PowerPoint PPT presentation

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Title: GEOGRAPHIC INFORMATION SYSTEM (GIS) AND REMOTE SENSING


1
GEOGRAPHIC INFORMATION SYSTEM (GIS) AND
REMOTE SENSING
  • Lecture 4

Zakaria Khamis
2
  • From the spectral reflectance values of an
    object, the spectral reflectance curve can be
    drawn. This curve is very important, for it
    portrays the spectral characteristics of a given
    feature.
  • Spectral reflectance curve helps to select the
    band width (wavelength range) which will be used
    in remote sensing to acquire data for a given
    feature.
  • The spectral reflectance curve is drawn not
    using single values which produce single line,
    rather it is drawn as a ribbon (envelope), for
    the spectral reflectance values vary somewhat
    within a given material class (i.e. there is a
    range of values for a spectral reflectance of a
    given feature).
  • For example, the spectral reflectance of one
    orange species and another will not be identical
    as well as, the spectral reflectance of the same
    tree specie will never be exactly the same.
  • It is difficult to differentiate Coniferous
    trees from Deciduous trees in the forest in the
    visible band however, in the IR band, Deciduous
    trees appears BRIGHT in tone whereas, Coniferous
    trees appear DARKER in tone.

3
Note the range of spectral values
4
Infrared (IR) Photograph for Trees in a Forest
5
Spectral Reflectance of Vegetation, Soil, and
Water
  • Through remote sensing, these features can be
    distinctly identified.
  • The spectral reflectance curve of these features
    can help to identify the bandwidth in which the
    sensor can sense.
  • Note the graphs represent the average values for
    spectral reflectance of these 3 features.
  • Healthy green vegetation, dry bare soil
    (gray-brown loam) and clear lake water are 3
    basic features on the earths surface.

6
  • Chlorophyll highly absorbs EME in the wavelength
    bands of about 0.45µm and 0.67µm (often called
    chlorophyll absorption bands).
  • Thus we see the healthier vegetations green in
    color, for the plant leaves highly absorb the
    blue and red waves whereas, highly reflecting
    the green wave.
  • When the plant is under stress, the chlorophyll
    production decreases. This increases the red wave
    reflection on the leaves. Due to the combination
    of red and green, we see the plant leaves YELLOW.
  • The reflectance of healthy vegetation increases
    sharply at NIR (0.7µm to 1.3µm).
  • The plant leaf typically reflects 40 to 50 of
    the NIR energy incident on it.

7
  • Most of the remaining energy is transmitted
    since absorption in this spectral band (IR) is
    minimum less than 5.
  • The plant spectral reflectance in IR range (0.7µm
    to 1.3µm) is primarily the result of the internal
    structure of the leaves. Because this structure
    is highly variable between plant species,
    reflectance measurements in this range often
    permit us to discriminate between species, even
    if they look the same in visible band.
  • Beyond 1.3µm, the incident energy is essentially
    absorbed, with little to no transmission

Dips in the reflectance curve of healthy
vegetation occur at 1.4µm, 1.9µm and 2.7µm.
Because water in the leaves absorb strongly at
this bands. These spectral regions are known as
Water Absorption Bands. Beyond 1.3µm, leaf
reflectance is the function of total water
presents in the leaf. The two are inversely
related
8
  • Soil spectral reflectance curve shows less peaks
    and valleys variation.
  • Factors that affect the soil reflectance include
    soil moisture, soil texture (proportion of
    sand, silt and clay), surface roughness, iron
    oxide, and organic matter among others.
  • Presence of soil moisture decreases the soil
    reflectance at variable bands especially, in the
    water absorption bands (1.4µm, 1.9µm and 2.7µm).
  • Clay soil also has Hydroxyl absorption bands
    1.4µm and 2.2µm

Soil moisture content is strongly related to the
soil texture. Coarse sandy soil is usually well
drained hence low moisture content high
reflectance. In the absence of water, dry soil
itself exhibit the reverse tendency. Coarse
texture soil will appears darker than fine
texture soil.
9
  • The location and delineation of water bodies in
    remote sensing are easily done in NIR band,
    because of this absorption property.
  • The reflectance of water bodies is not only the
    function of water, but also the suspended
    materials within the water.
  • Clear water absorbs relatively little energy
    having the wavelength less than about 0.6µm.
  • As turbidity of water changes, due to the
    presence of suspended materials (organic and
    inorganic), the reflectance property change.
  • For the case of water, the most distinctive
    characteristic is the energy absorption at NIR
    and beyond.

10
  • For example, water containing large quantity of
    suspended sediments resulting from soil erosion
    normally have much higher visible band
    reflectance than clear water.
  • Moreover, the chlorophyll concentration in the
    water changes the reflectance property of the
    water.
  • Increasing in chlorophyll concentration tend to
    decrease water reflectance in blue and increase
    the reflectance in green wavelength.

The characteristics of the presence of
chlorophyll in water has been used to monitor the
concentration of ALGAE via remote sensing
11
Spectral Response Patterns
  • In remote sensing, spectral responses measured by
    the remote sensors are what permit us to
    differentiate types of features and their
    conditions.
  • The spectral responses of a given feature are
    referred as SPECTRAL SIGNATURES of that feature.
  • Earths features manifest very distinctive
    spectral reflectance characteristics (see the
    previous spectral reflectance curves for
    vegetation, water and soil), these
    characteristics result to SPECTRAL RESPONSE
    PATTERN.
  • In remote sensing, the term spectral response
    pattern is preferred over spectral signature,
    because spectral signature tend to imply a
    pattern which is absolute and unique. Whereas,
    the spectral response is not a unique pattern, it
    may change based on spatial, temporal and
    atmospheric factors.

12
An Ideal Remote Sensing System
  • There are elements necessary to conceptualize the
    remote sensing system. These elements are -
  • A uniform Energy Source this source would
    provide energy over all wavelengths, at a
    constant, known, high level of output,
    irrespective of time and place.
  • A non-interfering Atmosphere This would be an
    atmosphere that would not alter the energy from
    the source in any manner, weather that energy is
    in its way to the earths surface or coming from
    it (irrespective of wavelength, place, time and
    sensing altitude involved).
  • A series of unique energy-matter interactions at
    the earths surface these interactions will
    generate reflected signals that are selective
    with respect to wavelength, known, invariant and
    unique to each and every earths feature type and
    subtype.

13
  • A super-sensor this would be highly sensitive
    sensor to all wavelengths, yielding spatially
    detailed data on the absolute brightness
    throughout the spectrum. This sensor would be
    simple and reliable, requires virtually no power
    or space, and be accurate and economical to
    operate.
  • A real-time data processing and supply system
    in this system, the instant the
    radiance-versus-wavelength response over a
    terrain element was generated, it would be
    transmitted to ground, geometrically and
    radiometric ally corrected as necessary and
    processed into readily interpretable format.
  • Multiple data Users these people would have
    knowledge of great depth, both of their
    respective disciplines and remote sensing data
    acquisition and analysis techniques.
  • Unfortunately, and ideal remote sensing system
    as described above doesnt exist.
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