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Showing posts with label Thermal Remote Sensing. Show all posts
Showing posts with label Thermal 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
Saturday, 30 November 2013
Thermal Remote Sensing
Thermal
Remote
Sensing
is
described
as
the
acquisition
of
image
data
in
the
infrared
part
of
the
electromagnetic
spectrum.
It
uses
the
radiations
that
are
emitted
by
the
surface itself.
Thermal
infrared
is
emitted
energy
that
is
sensed
digitally.
Thermal
remote
sensing
is
used
on
areas
to
assess
the
heat
island,
to
perform
land
cover
classifications
and
as
an
input
for
models
of
urban
surface
atmosphere
exchange.
Thermal
Remote
Sensing
is
a
special
case
of
reserving
land
surface
temperature
which
varies
in
accordance
to
the
surface
energy
balance.
Thermal data are usually acquired in sequences, where the first image is taken at night and the second is taken during the day. The image that is taken at night is used to monitor the raw emission of the surface and the second image that is taken during the day is used to see what part of incident shortware solar radiation is transformed to thermal radiation and then emitted to the surface.
This
principle
is
used
quite
often
in
geological
applications
and
we
can
study
the
presence
of
different
rocks
based
on
their
thermal
capacity.
Whereas
the
domain
of
visible
and
near
infrared
(VNIR)
radiation
is
suitable
for
monitoring
the
presence
of
metallic
minerals
such
as
hematite,
the
shortwave
infrared
domain
(SWIR)
is
used
for
the
detection
of
minerals
containing
OH-
functional
group.
But
none
of
these
domains
is
suitable
for
observing
the
major
constituents
of
igneous
rocks,
silica
and
feldspar.
In
addition
to
the
geological
applications,
Thermal
Remote
Sensing
image
data
can
be
used
for
:
- Studying the transformation of shortware solar radiation into longware thermal radiation and and evapo transpiration in the case of vegetation.
- Detection of heat loss in buildings
- Detection of the damages of steam pipelines and caliduct
- Detection of the subsurface fires
More Knowledge Contact
:- Spatial
IT Solutions
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