1. Atmospheric windows
Certain regions of the EM spectrum are completely
absorbed by the various gases that make up the
atmosphere, so that wavelengths in these regions cannot
be used for remote sensing of the Earth's surface. The
regions of the EM spectrum which are not affected by the
Earth's atmosphere are called 'atmospheric windows'
2. Atmospheric Windows
• Atmospheric windows define wavelength ranges
in which the atmosphere is particularly
transmissive of energy.
• Visible region of the electromagnetic spectrum
resides within an atmospheric window with
wavelengths of about 0.3 to 0.9 µm
• Emitted energy from the earth's surface is sensed
through windows at 3 to 5 µm and 8 to 14 µm.
• Radar and passive microwave systems operate
through a window region of 1 mm to 1 m.
3. Atmospheric Windows
The dominant
windows in the
atmosphere are in
the visible and
radio frequency
regions, while X-
Rays and UV are
very strongly
absorbed and
Gamma Rays and
IR are somewhat
less strongly
absorbed.
4. Atmospheric transmittance
Some wavelength regions of the EM spectrum are absorbed by
atmospheric gases so cannot be used for remote sensing of the
Earth's surface features.
5. Ideal Remote Sensing System
1. A uniform energy source.
2. A non-interfering atmosphere.
3. A series of unique energy/matter
interactions at the earth’s surface.
4. A super sensor.
5. A real-time data handling system.
6. Multiple data users.
6. AN IDEALREMOTESENSING SYSTEM
System Component 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.
7. AN IDEALREMOTESENSING SYSTEM
System Component 2
A non-interfering atmosphere
This would be an atmosphere that would not
modify the energy from the source in any
manner, whether that energy were on its way to
the Earth’s surface or coming from it.
Again, ideally, this would hold irrespective of
wavelength, time, place and sensing altitude
involved.
8. AN IDEALREMOTESENSING SYSTEM
System Component 3
A series of unique energy / matter interactions
at the Earth’s surface
These interactions would generate reflected
and/or emitted signals that not only are selective
with respect to wavelength, but also are known,
invariant, and unique to each and every surface
type and subtype of interest.
9. AN IDEALREMOTESENSING SYSTEM
System Component 4
A super sensor
This would be a sensor, highly sensitive to all
wavelengths, yielding spatially detailed data on the
absolute brightness (or radiance) from a scene as a
function of wavelength, throughout the spectrum.
This super sensor would be simple and reliable,
require virtually no power or space, and be accurate
and economical to operate.
10. AN IDEALREMOTESENSING SYSTEM
System Component 5
A real-time data handling system
In this system, the instant a signal over a terrain element was
generated, it would be processed onto an interpretable format and
recognized as being unique to the particular terrain element from
which it came. This processing would be performed nearly
instantaneously (‘real-time’), providing timely information.
Because of the consistent nature of the energy/matter interactions,
there would be no need for reference data in the analysis
procedure. the derived data would provide insight into the
physical - chemical – biological state of each object of interest.
11. AN IDEALREMOTESENSING SYSTEM
System Component 6
Multiple data users
These people would have knowledge of great depth, both of their
respective disciplines and of remote sensing data acquisition and
analysis techniques. The same set of data would be transformed
into various forms of information for different users. This
information would be available to them faster, at less expense, and
for larger areas than information collected in any other manner.
With this information, the various users would make profound,
wise decisions about how best to manage the earth resource under
scrutiny, and these strategic management decisions would be
implemented
– to everyone’s delight !
12. But…..
An ideal remote sensing system does not
and cannot exist. Real remote sensing
systems fall far short of the ideal at
virtually every point in the sequence
outlined. Let us consider some of the
basic shortcomings.
13. Basic shortcomings common to all real remote sensing systems
The energy source.
All passive remote sensing systems rely on energy that is
either reflected and/or emitted from Earth surface features.
The spectral distribution of reflected sunlight and self-
emitted energy is far from uniform. Solar energy levels
obviously vary with respect to time and location, and
different Earth surface materials emit energy to varying
degrees of efficiency.
The sources of energy used in all real systems are generally
nonuniform with respect to wavelength and their properties
vary with time and location.
14. Basic shortcomings common to all real remote sensing systems
The atmosphere.
The atmosphere normally compounds the problems
introduced by energy source variation. To some extent, the
atmosphere always modifies the strength and spectral
distribution of the energy received by a sensor. It restricts
“where we can look” spectrally – atmospheric windows -
and its effects vary with wavelength, time and place.
The importance of these effects is a function of the
wavelengths involved, the sensor used, and the intended
application. Eliminating, or compensating for, atmospheric
effects via some form of calibration is particularly
important in those applications which involve repetitive
observations of the same geographical area.
15. Basic shortcomings common to all real remote sensing systems
The energy / matter interactions at the
Earth’s surface.
Remote sensing would be simple if every material reflected
and/or emitted energy in a unique, known way. Although
spectral response patterns (signatures) play a central role in
detecting, identifying, and analysing Earth surface materials,
the spectral world is full of ambiguity.
Radically different material types can have great spectral
similarity, making differentiation difficult. Furthermore, our
understanding of the energy/matter interactions for Earth
surface features is at an elementary level for some materials
and virtually non-existent for others.
16. Basic shortcomings common to all real remote sensing systems
The sensor.
An ideal “super sensor” does not exist. No single sensor
is sensitive to all wavelengths and all real sensors have
detectors with fixed limits of spectral sensitivity. They
also have a limit on how small an object on the Earth’s
surface can be and still be “seen” by a sensor as being
separate from its surroundings.
This limit, called the spatial resolution of a sensor, is an
indication of how well a sensor can record spatial detail.
17. Basic shortcomings common to all real remote sensing systems
The choice of a sensor for any given task always
involves tradeoffs.
Photographic systems generally produce images of very
fine spatial resolution, but they lack the broad spectral
sensitivity obtainable with non-photographic systems.
These requirements often dictate the type of platform
from which a sensor can be operated. Platforms can vary
from stepladders to space stations. Depending on the
sensor/platform combination needed for a particular
application, the acquisition of remote sensing data can be a
very expensive endeavour.
18. Basic shortcomings common to all real remote sensing systems
The data-handling system.
The capability of remote sensors to generate data far
exceeds our capacity to handle these data. This is generally
true whether we consider “manual” image interpretation
procedures or computer assisted analyses. Subsequently, the
task of preparing data requires considerable thought,
instrumentation, time, experience, and ground (and
atmospheric) reference data.
While much data handling can be done by computers,
personal intervention in data processing is and will continue
to be essential to the productive application of remote
sensor data.
19. Basic shortcomings common to all real remote sensing systems
The multiple data users.
A thorough understanding of the problem at hand is
paramount to the productive application of any remote
sensing methodology. Also, no single combination of
data acquisition and analysis procedures will satisfy
the needs of all data users.
Whereas the interpretation of aerial photography has
been used as a practical resource management tool for
nearly a century, newer forms of remote sensing have
had relatively few satisfied users until recently.
Increasing numbers of users, however, are becoming
aware of the potentials, as well as the limitations, of
remote sensing techniques.
20. Characteristics of Actual Remote Sensing Systems
fluctuating energy source
atmosphere
ambiguous and similar spectral response patterns
for features
true sensor
time lag
few users
22. Photographic Data Acquisition
Remotely sensed photographic data are produced
by directly recording the radiation from an object
onto photographic film. The range of wavelengths
which may be detected by photographic devices is
limited by the sensitivities of the film and filter(s)
being used in the camera. The spectral sensitivity
of photographic film can range from ultraviolet to
near infrared wavelengths.
23. Photographic data
Multi-band cameras, which simultaneously
record multiple photographic impressions of
an object, may be used to simulate a multi-
spectral image. Such cameras use varying film
and filter combinations to record different
spectral regions in each photograph.
24. Photographic data
Remote sensing devices which record data
photographically require that the film be
recoverable for processing. Such devices can
be carried by aircraft or retrievable spacecraft
(such as the Space Shuttle).
Examples of data collected this way are aerial
photography, the Large Format Space Camera
imagery and Shuttle Imaging Radar scenes
25. Photographic data
Advantages of photographic imagery are the
technical simplicity of its processing and
interpretation. Both these factors tend to mean that
it is available at a lower cost than digitally recorded
data.
However, unlike digital scanners, photographic
devices can only directly detect radiation in the
visible and near infrared range of the
electromagnetic spectrum so such data are affected
by cloud cover.
26. Digital Data Acquisition
Data need to be in digital, or numeric, form to
be processed by a computer. In a digital
image, colours are represented by numbers. A
grid pattern is used to record the colours in
the image, each cell being assigned one or
more colour numbers.
28. digital image
Any picture, photograph or map can be
digitised. Automatic scanning devices, which
operate in a similar manner to the satellite
scanning systems, can be used in a laboratory
to convert coloured or black and white maps,
pictures or photographs, into digital images
for processing by computer.
