GEOGRAPHIC INFORMATION
SYSTEM (GIS)
AND
REMOTE SENSING
Zakaria Khamis
Lecture 4
• 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.
Note the range of
spectral values
Infrared (IR) Photograph for Trees in a Forest
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.
• Healthy green vegetation, dry bare
soil (gray-brown loam) and clear lake
water are 3 basic features on the
earth’s surface.
• Note: the graphs represent the
average values for spectral
reflectance of these 3 features.
• Chlorophyll highly absorbs EME • The reflectance of healthy vegetation
in the wavelength bands of about increases sharply at NIR (0.7μm to
0.45μm and 0.67μm (often called 1.3μm).
chlorophyll absorption bands).
• The plant leaf typically reflects 40%
to 50% of the NIR energy incident on
• Thus we see the healthier
vegetations green in color, for the it.
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.
• Most of the remaining energy is
transmitted; since absorption in this
spectral band (IR) is minimum – less
than 5%.
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
• 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
• 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.
• 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.
• For the case of water, the most
distinctive characteristic is the
energy absorption at NIR and
beyond.
• 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 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
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.
• Earth’s 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.
An Ideal Remote Sensing System
• There are elements necessary to conceptualize the remote sensing system.
These elements are: 1. 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.
2. 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 earth’s surface or coming from it (irrespective of
wavelength, place, time and sensing altitude involved).
3. A series of unique energy-matter interactions at the earth’s surface –
these interactions will generate reflected signals that are selective with
respect to wavelength, known, invariant and unique to each and every
earth’s feature type and subtype.
4. 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.
5. 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.
6. 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 doesn’t
exist.