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| Remote Sensing |
Showing posts with label Hyperspectral Remote Sensing. Show all posts
Showing posts with label Hyperspectral Remote Sensing. Show all posts
Tuesday, 29 April 2014
Monday, 9 December 2013
Hyperspectral Remote Sensing
The
advances
in
remote
sensing
and
geographic
information
that
made
the
way
for
the
development
of
Hyperspectral
remote
Sensors.
Imagery
Spectroscopy
is
also
known
as
Hyperspectral
Remote
Sensing
and
it
is
a
new
technology
that
is
presently
being
investigated
by
scientists
and
researchers
and
it
would
deal
with
the
detection
and
identification
of
minerals,
vegetation,
man-made
materials
and
backgrounds.
It
combines
imaging
and
spectroscopy
in
one
system
and
it
often
includes
large
data
sets
and
require
new
processing
methods.
Like
other
spectral
imaging,
Hyper
Spectral
imaging
collects
and
processes
information
from
across
the
electromagnetic
spectrum.
Unlike
the
human
eye
that
can
see
the
visible
light
in
three
bands(red,
blue
&
green),
spectral
imaging
divides
the
spectrum
into
more
bands.
The
technique
of
diving
images
into
bands
that
can
be
extended
beyond
the
visible
region.
Hyperspectral
Remote
Sensing
makes
use
of
Hyperspectral
Sensors.
The
sensors
collect
information
as
a
set
of
images,
where
each
image
represents
a
range
of
electromagnetic
spectrum
and
is
also
called
spectral
band.
All
of
these
images
are
further
collected
and
integrated
to
form
a
three-dimensional
hyperspectral
cube
for
the
purpose
of
processing
and
analysis.
The
precision
of
these
sensors
is
typically
measured
in
spectral
resolution,
which
is
the
width
of
each
band
of
the
spectrum
that
has
been
captured.
It
is
possible
that
the
senors
might
detect
a
large
number
of
fairy
narrow
frequency
bands
giving
the
possibility
to
identify
objects
even
if
they
are
captured
in
a
handful
of
pixels.
Spatial
Resolution
is
a
factor
in
addition
to
Spectral
Resolution.
If
the
pixels
are
sufficiently
large
then
multiple
objects
are
captured
in
the
same
pixel
and
it
becomes
difficult
to
identify
each
of
them.
Also
if
the
pixels
are
too
small,
then
the
energy
that
is
captured
in
each
sensor
cell
is
quite
low
and
the
decreased
signal-to-noise
ratio
reduces
the
reliability
of
measured
features.
The
acquisition
and
refining
of
hyperspectral
images
is
also
referred
to
as
imaging
spectroscopy.
Applications:
There
are
a
few
scenarios
that
make
use
of
Hyperspectral
Remote
Sensing.
- Biomass burning: subpixel temperatures, smoke
- Atmosphere: cloud properties, water vapor, aerosols
- Snow/Ice: snow cover fraction, melting
- Geology: minerals and soil type
- Commercial: agriculture, forest production and mineral exploration
Thursday, 21 November 2013
Passive Remote sensing
So far, we have
read various definitions and descriptions of Remote Sensing. But only
an appropriate definition would make the very concept of Remote
Sensing clear. Remote Sensing is the acquisition of information about
an object or phenomenon relating to the object without making any
kind of physical contact with the object.
Passive remote
sensing is a class of Remote Sensing that make use of Passive Remote
Sensors. The sensors are used to detect natural radiations that are
emitted by the object or by its surrounding areas. The most common
source of energy that is measured by Passive Remote Sensors is
“Reflected Sunlight”.
The sensors that
are used for Passive Remote Sensing can only be used when there is
some naturally occurring energy available. Thus, for all reflected
energy, Passive Remote Sensing can only take place when the sun is
illuminating the surface of the earth. No reflected is available from
the sun at night.
Passive Remote
Sensors obtain measurements from naturally occurring radiations. The
sensors have several characteristics and they are often called its
advantages :
- Multiple wavelength information
- Comparatively low electrical power requirements
- Small size possible
The Passive Remote
Sensing systems are pretty much similar to what the eyes see. They
are more or less similar to photographs. Passive Sensing radiates
visible light. Some of the very common examples of Passive Remote
Sensing are :
- Charge-Coupled Devices
- Infrared
- Film Photography
- Radiometers
The energy that is
radiated naturally can be detected day or night, as long as the
amount of energy is large enough to be recorded.
Friday, 15 November 2013
Remote Sensing
Remote Sensing is the technique that is used for obtaining information about objects by analyzing the data that is collected by special instruments that do not have any physical contact with the object/s under investigation.
Alternatively, it can be termed as acquiring the salient information of an object or aspect without the need to physically touch it. The technique generally makes use of aerial sensor technologies that detect or classify the objects on earth by means of electromagnetic radiations that are emitted by aircraft or satellites. The two main components of remote Sensing are “Data Capture” and “Data Analysis”.
Alternatively, it can be termed as acquiring the salient information of an object or aspect without the need to physically touch it. The technique generally makes use of aerial sensor technologies that detect or classify the objects on earth by means of electromagnetic radiations that are emitted by aircraft or satellites. The two main components of remote Sensing are “Data Capture” and “Data Analysis”.
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| Remote Sensing |
Remote Sensing is broadly categorized into two main types:
Active Remote Sensing
Passive Remote Sensing
In Passive Remote Sensing passive sensors are able to detect the natural radiations that are emitted by objects and their surrounding areas. They respond to external stimuli. Reflected sunlight is the most common source of radiation that is measured by passive sensors. Charge-coupled devices, infrared and radiometers are some examples of passive sensors.
As the name also suggests in Active Remote Sensing Active sensors are used to measure the radiations that are reflected back from the target bodies. They respond to internal stimuli. RADAR is a common example of active remote sensing technique. A RADAR measures the time delay between the emission and return of a radiation, based on which it calculates the location, speed and the direction of an object.
Following are the application areas for Remote Sensing technology:
Ocean Applications: The technique of remote Sensing can also be used to monitor ocean circulation and current system. It is also used to measure ocean temperature and the wave heights. Remote sensing can also be used to track sea ice or in cases where you want to get a better understanding of the oceans and manage ocean resources.
Hazard Assessment: It has its importance when there is a need to track hurricanes, earthquakes, erosion, and floods and other natural disasters. The data that is given can be used to assess the effects of natural disasters. Based on the data that is obtained by Remote Sensors some strategies can be made that can be used before and after the disaster.
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| Hazard Assessment |
Coastal Applications: Remote Sensing is used to monitor the changes that occur on the shoreline or even in the case of tracking sediment transport etc. The data that is obtained by Remote Sensing can also be used for coastal mapping and for preventing erosion.
The complete remote sensing process can be summarized as follows:
The data is captured by the Remote Sensors, such information is recorded and then analyzed by some interpretive and measurement techniques. This is done in order to provide useful information about the objects that are under investigation. The techniques are diverse and vary from the traditional methods of visual interpretation to the methods using computer processing.
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