Chapter 2 EMR

1
Thermal Infrared Remote Sensing
John R. Jensen Department of Geography University
of South Carolina Columbia, South Carolina 29208
2
Selected Applications of Thermal Infrared Remote
Sensing
3
Nighttime Thermal Infrared Imagery of an Airport
4
Thermal Infrared Remote Sensing
Thermal infrared energy is emitted from all
objects that have a temperature greater than
absolute zero. Therefore, all the features we
encounter in the landscape on a typical day (Sun,
vegetation, soil, rocks, water, and even people)
emit thermal infrared electromagnetic radiation.
Humans sense thermal energy primarily through the
sense of touch. Our eyes cannot detect
differences in thermal infrared energy because
they are primarily sensitive to short wavelength
visible light from 0.4 ?m to 0.7 ?m. Our eyes are
not sensitive to the reflective infrared (0.7 -
3.0 ?m) or thermal infrared energy (3.0 - 14 ?m).
Fortunately, engineers have developed detectors
that are sensitive to thermal infrared radiation.
These thermal infrared sensors allow humans to
sense a previously invisible world of information
as they monitor the thermal characteristics of
the landscape.
5
Atmospheric Windows in the Electromagnetic
Spectrum
6
Fundamental Properties of Electromagnetic
Radiation
The three basic ways in which energy can be
transferred Conduction occurs when one body
(molecule or atom) transfers its kinetic energy
to another by colliding with it. This is how a
pan is heated on a stove. In convection, the
kinetic energy of bodies is transferred from one
place to another by physically moving the bodies.
An example is the convectional heating of air in
the atmosphere in the early afternoon. The
transfer of energy by electromagnetic radiation
is of primary interest to remote sensing because
it is the only form of energy transfer that can
take place in a vacuum such as the region between
the Sun and the Earth.
7
Methods of Heat Transfer
8
History of Thermal Infrared Remote Sensing
The astronomer Sir Frederick William Herschel
(1738-1822) discovered the infrared portion of
the electromagnetic spectrum in 1800 described in
his famous paper Investigations of the Powers of
the Prismatic Colours to Heat and Illuminate
Objects with Remarks. In 1879, S. P. Langley
began a research program to find a superior
radiation detector. One year later he invented
the bolometer that was able to obtain measurable
temperature variations of 1/10,000 C. In
World War I, S. O. Hoffman could detect men at
120 m and aircraft. In the 1930s, Germany
developed the Kiel system for discriminating
between bombers and night fighters.
9
History of Thermal Infrared Remote Sensing
The single most important development in
infrared technology was the development of the
detector element by nations at war during World
War II. Early infrared detectors were lead salt
photodetectors. Now we have very fast
detectors consisting of mercury-doped germanium
(GeHg), indium antimonide (InSb) and other
substances that are very responsive to infrared
radiation. We also have computers to rapidly
process and display the thermal radiometric
measurements. In 1968, the government
declassified thermal infrared remote sensing
systems that did not exceed a certain spatial
resolution and temperature sensitivity.
10
History of Thermal Infrared Remote Sensing
The first declassified satellite remote sensor
data were collected by the U. S. Television IR
Operational Satellite (TIROS) launched in 1960.
The coarse resolution thermal infrared data were
ideal for monitoring regional cloud patterns and
frontal movement. NASA launched the Heat
Capacity Mapping Mission (HCCM) on April 26, 1978
that obtained 600 x 600 m spatial resolution
thermal infrared data (10.5 - 12.6 ?m) both day
(130 pm) and night (230 am). This was one of
the first scientifically oriented (geology)
thermal infrared systems. NASAs Nimbus 7
launched on October 23, 1978 had a Coastal Zone
Color Scanner (CZCS) that included a thermal
infrared sensor for monitoring sea-surface
temperature.
11
History of Thermal Infrared Remote Sensing
In 1980, NASA and the Jet Propulsion Laboratory
developed the thermal infrared multispectral
scanner (TIMS) that acquires thermal infrared
energy in six bands at wavelength intervals of
lt1.0 ?m. Landsat Thematic Mapper 4 and 5
sensors were launched on July 16, 1982 and March
1, 1984, respectively, and collected 120 x 120 m
thermal infrared data (10.4 - 12.5 ?m) along with
two bands of middle infrared data. Today, the
NOAA Geostationary Operational Environmental
Satellite (GOES) collects thermal infrared data
at a spatial resolution of 8 x 8 km for weather
prediction. Full-disk images of the earth are
obtained every 30 minutes both day and night by
the thermal infrared sensor.
12
History of Thermal Infrared Remote Sensing
The NOAA Advanced Very High Resolution
Radiometer (AVHRR) collects thermal infrared
local area coverage (LAC) data at 1.1 x 1.1 km
and global area coverage (GAC) at 4 x 4 km. The
routine collection of thermal infrared data are a
part of each persons daily life as we watch the
nightly weather report.
13
Thermal Infrared Radiation Principles
An analyst cannot interpret a thermal infrared
image as if it were an aerial photograph or a
normal image produced by a multispectral scanner
or charge-coupled device. Rather, the image
analyst must think thermally. The analyst
must understand how energy from the Sun or from
the Earth interacts with the various terrain
components and how the detectors function as they
record the terrains emitted thermal infrared
electromagnetic radiation. Finally, the analyst
must understand how both the sensor system itself
and the terrain can introduce noise into the
thermal infrared image that might make the data
less useful or lead to incorrect image
interpretation.
14
Characteristics of a Thermal Infrared Airborne
Across-track Scanner
15
Pre-dawn Thermal Infrared Image of Effluent
Entering the Savannah River Swamp System
Savannah River
Savannah River
2x reduction
March 31, 1981 428 am 3 x 3 m
16
Pre-dawn Thermal Infrared Image of a Residential
Subdivision in Forth Worth, Texas
250 m AGL 1 mrad IFOV 645 am Jan 10, 1980 0.25 x
0.25 m
17
Kinetic Heat, Temperature, Radiant Energy and
Radiant Flux
The energy of particles of matter in random
motion is called kinetic heat (also referred to
as internal, real, or true heat). All objects
having a temperature above absolute zero (0 K
-273.16 C and -459.69 F) exhibit this random
motion. When these particles collide they change
their energy state and emit electromagnetic
radiation as previously discussed. The amount
of heat can be measured in calories (the amount
of heat required to raise the temperature of 1 g
of water 1 C). We can measure the true kinetic
temperature (Tkin) or concentration of this heat
using a thermometer. We perform this in situ (in
place) temperature measurement when we are ill.
We can also measure the true kinetic internal
temperature of soil or water by physically
touching them with a thermometer.
18
Kinetic Heat, Temperature, Radiant Energy and
Radiant Flux
Fortunately for us, an objects internal
kinetic heat is also converted to radiant energy
(often called external or apparent energy). The
electromagnetic radiation exiting an object is
called radiant flux (?) and is measured in watts.
The concentration of the amount of radiant flux
exiting (emitted from) an object is its radiant
temperature (Trad). There is usually a high
positive correlation between the true kinetic
temperature of an object (Tkin) and the amount of
radiant flux radiated from the object (Trad).
Therefore, we can utilize radiometers placed some
distance from the object to measure its radiant
temperature which hopefully correlates well with
the objects true kinetic temperature. This is
the basis of thermal infrared remote sensing.
19
Kinetic Heat, Temperature, Radiant Energy and
Radiant Flux
Unfortunately, the relationship is not perfect,
with the remote measurement of the radiant
temperature always being slightly less than the
true kinetic temperature of the object. This is
due to a thermal property called emissivity.
20
Thermal Infrared Atmospheric Windows
Beyond the visible region of the
electromagnetic spectrum, we encounter the
reflective infrared region from 0.7 - 3.0 ?m and
the thermal infrared region from 3 - 14 ?m.
The only reason we can use remote sensing devices
to detect infrared energy in these regions is
because the atmosphere allows a portion of the
infrared energy to be transmitted from the
terrain to the detectors. Regions that pass
energy are called atmospheric windows. Regions
that absorb most of the infrared energy are
called absorption bands. Water vapor (H2O),
carbon dioxide (CO2), and ozone (O3) are
responsible for most of the absorption. For
example, atmospheric water vapor (H2O) absorbs
most of the energy exiting the terrain in the
region from 5 to 7 ?m making it almost useless
for remote sensing.
21
Atmospheric Windows in the Electromagnetic
Spectrum
22
Reflective Infrared Detectors
Remote sensors can be engineered to be
sensitive to the infrared energy present within
the reflective infrared atmospheric windows.
Film emulsions can be made sensitive to reflected
infrared energy in the window from 0.7 -.09 ?m.
For example, Kodaks 2443 color infrared film
works within this photographic infrared region
and is ideal for monitoring vegetation and water.
Electro-optical detectors on Landsat Thematic
Mapper 4 and 5 are sensitive to the reflective
infrared windows from 1.55 - 1.75 ?m (TM band 5)
and 2.08 - 2.35 ?m (TM band 7).
23
Thermal Infrared Detectors
Electronic detectors can also be made sensitive
to photons of thermal infrared radiant energy
exiting the terrain in the two primary thermal
infrared windows 3 - 5 ?m and 8 - 14 ?m.
Sub-orbital thermal infrared remote sensing
systems utilize these spectral bands. The
Earths ozone (O3) layer absorbs much of the
thermal energy exiting the terrain in an
absorption band from approximately 9 - 10 ?m.
Therefore, satellite thermal infrared remote
sensing systems usually only record data in the
region from 10.5 - 12.5 ?m to avoid the
absorption band.
24
Daytime Optical and Nighttime Thermal Infrared
Imagery of the University of South Carolina Campus
April 26, 1981 456 am 1 x 1 m
2x reduction
25
Thermal Radiation Laws
A blackbody is a theoretical construct that
absorbs all the radiant energy striking it and
radiates energy at the maximum possible rate per
unit area at each wavelength for any given
temperature. No objects in nature are true
blackbodies, however, we may think of the Sun as
approximating a 6,000 K blackbody and the Earth
as a 300 K blackbody. If we pointed a sensor at
a blackbody we would be able to record
quantitative information about the total amount
of radiant energy in specific wavelengths exiting
the object and the dominant wavelength of the
object. In order to do this, we utilize two
important physical laws the Stefan-Boltzmann law
and Weins displacement law.
26
Stephen Boltzmann Law
The total spectral radiant flux exitance (Fb)
measured in watts m2 leaving a blackbody is
proportional to the fourth power of its
temperature (T). This is the Stefan-Boltzmann law
and is expressed as Fb kT4 where k is the
Stefan-Boltzmann constant equaling 2898 mm K,
and T is temperature in degrees Kelvin. The total
radiant exitance is the integration of all the
area under the blackbody radiation curve. The
Sun produces more spectral radiant exitance (Fb)
at 6,000 K than the Earth at 300 K. As the
temperature increases, the total amount of
radiant energy measured in watts per m2 (the area
under the curve) increases and the radiant energy
peak shifts to shorter wavelengths.
27
Blackbody Radiation Curves for Several Objects
including the Sun and Earth
28
Weins Displacement Law
The relationship between the true temperature of
a blackbody (T) in degrees Kelvin and its peak
spectral exitance or dominant wavelength (?max)
is described by Weins displacement law ?max
k 2898 ?m K T
T where k is a constant equaling 2898 ?m
K.
29
Weins Displacement Law
For example, the average temperature of the Earth
is 300 K (80 F). We compute the Earths
dominant wavelength as ?max 2898 ?m
K T ?max 2898 ?m K 9.67
?m 300 K
30
Weins Displacement Law
The dominant wavelength provides valuable
information about which part of the thermal
spectrum we might want to sense in. For example,
if we are looking for 800 K forest fires that
have a dominant wavelength of approximately 3.62
?m then the most appropriate remote sensing
system might be a 3-5 ?m thermal infrared
detector. If we are interested in soil,
water, and rock with ambient temperatures on the
earths surface of 300 K and a dominant
wavelength of 9.66 ?m, then a thermal infrared
detector operating in the 8 - 14 ?m region might
be most appropriate.
31
Emissivity
The world is not composed of radiating
blackbodies. Rather it is composed of selectively
radiating bodies such as rocks, soil, and water
that emit only a fraction of the energy emitted
from a blackbody at the same temperature.
Emissivity, ?, is the ratio between the radiant
flux exiting a real-world selective radiating
body (Fr) and a blackbody at the same temperature
(Fb) Fr ? ______ Fb
32
Emissivity
All selectively radiating bodies have
emissivities ranging from 0 to lt1 that fluctuate
depending upon the wavelengths of energy being
considered. A graybody outputs a constant
emissivity that is less than one at all
wavelengths. Some materials like distilled
water have emissivities close to one (0.99) over
the wavelength interval from 8 - 14 ?m. Others
such as polished aluminum (0.08) and stainless
steel (0.16) have very low emissivities.
33
Spectral emissivity of a blackbody, a graybody,
and a hypothetical selective radiator
Spectral Emissivity, e
Spectral radiant exitance distribution of the
blackbody, graybody, and hypothetical selective
radiator
Spectral Radiant Exitance W m-2 um-1
2x reduction
34
Emissivity
Two rocks lying next to one another on the ground
could have the same true kinetic temperature but
have different apparent temperatures when sensed
by a thermal radiometer simply because their
emissivities are different. The emissivity of an
object may be influenced by a number factors,
including color -- darker colored objects are
usually better absorbers and emitters (i.e. they
have a higher emissivity) than lighter colored
objects which tend to reflect more of the
incident energy. surface roughness -- the
greater the surface roughness of an object
relative to the size of the incident wavelength,
the greater the surface area of the object and
potential for absorption and re-emission of
energy.
35
Emissivity
moisture content -- the more moisture an object
contains, the greater its ability to absorb
energy and become a good emitter. Wet soil
particles have a high emissivity similar to
water. compaction -- the degree of soil
compaction can effect emissivity. field-of-view
-- the emissivity of a single leaf measured with
a very high resolution thermal radiometer will
have a different emissivity than an entire tree
crown viewed using a coarse spatial resolution
radiometer. wavelength -- the emissivity of an
object is generally considered to be wavelength
dependent. For example, while the emissivity of
an object is often considered to be constant
throughout the 8 - 14 mm region, its emissivity
in the 3 -5 mm region may be different.
36
Emissivity
viewing angle - the emissivity of an object can
vary with sensor viewing angle. We must take into
account an objects emissivity when we use our
remote radiant temperature measurement to measure
the objects true kinetic temperature. This is
done by applying Kirchoffs radiation law.
37
Kirchoffs Radiation Law
Remember that the terrain intercepts incident
(incoming) radiant flux (?i). This incident
energy interacts with terrain materials. The
amount of radiant flux reflected from the surface
(?r), the amount of radiant flux absorbed by the
surface (?a), and the amount of radiant flux
transmitted through the surface (?t) can be
carefully measured as we apply the principle of
conservation of energy and attempt to keep track
of what happens to all the incident energy. The
general equation for the interaction of spectral
(?) radiant flux with the terrain is 1 ?i?
?r? ??? ???
38
Kirchoffs Radiation Law
Dividing each of the variables by the original
incident radiant flux ?i? / ?i? (?r? / ?i?)
( ??? / ?i?) ( ??? / ?i?) allows us to rewrite
the initial equation as ????????????????????????
? r?? ?? ?? where r? is spectral
hemispherical reflectance by the terrain, ?? is
spectral hemispherical absorptance, and ?? is
spectral hemispherical transmittance.
39
Kirchoffs Radiation Law
The Russian physicist Kirchhoff found that in
the infrared portion of the spectrum the spectral
emissivity of an object generally equals its
spectral absorptance, i.e. ?? ??. This is often
phrased as good absorbers
are good emitters and
good reflectors are poor emitters. Also, most
real-world materials are usually opaque to
thermal radiation meaning that no radiant flux
exits from the other side of the terrain element.
Therefore, we may assume transmittance, ?? 0.
Substituting emissivity for absorptance and
removing transmittance from the equation
yields ? r?? ??
40
Kirchoffs Radiation Law
This simple relationship describes why objects
appear as they do on thermal infrared imagery.
Because the terrain does not lose any incident
energy to transmittance, all of the energy
leaving the object must be accounted for by the
inverse relationship between reflectance (r?) and
emissivity (??). If reflectivity increases then
emissivity must decrease. If emissivity increases
then reflectivity must decrease. For example,
water absorbs almost all incident energy and
reflects very little. Therefore, water is a very
good emitter and has a high emissivity close to
1. Conversely, a sheet metal roof reflects most
of the incident energy, absorbs very little,
yielding an emissivity much less than 1.
Therefore, metal objects such as cars, aircraft,
and metal roofs almost always look very cold
(dark) on thermal infrared imagery.
41
Kirchoffs Radiation Law
The goal of thermal infrared remote sensing is
to be able to point a radiometer at an object and
have the apparent radiant temperature recorded
(Trad) equal the true kinetic temperature of the
object (Tkin). Unfortunately, the radiant flux
from a real-world object at a given temperature
is not the same as the radiant flux from a
blackbody at the same temperature largely due to
the effects of emissivity. Knowing the emissivity
characteristics of an object makes it possible to
modify the Stefan-Boltzmann law (originally
applicable to blackbodies) so that it pertains to
the total spectral radiant flux of real-world
materials (Fr) Fr ??k Tkin 4 It takes into
account the temperature of the object and its
emissivity to create a more accurate estimate of
the radiant flux exiting an object.
42
Kirchoffs Radiation Law
Thermal infrared remote sensing systems
generally record the apparent radiant
temperature, Trad of the terrain rather than the
true kinetic temperature, Tkin. If we assume that
the incorporation of emissivity in the previous
equation has improved our measurement to the
point that Fr ??k Tkin 4 and we
assume that Fb k Trad4 and Fr
Fb then, k Trad4 ??k Tkin
4 Therefore, the radiant temperature of an object
recorded by a remote sensor is related to its
true kinetic temperature and emissivity by the
following relationship Trad ??1/4Tkin
43
Thermal Properties of Terrain
Water, rocks, soil, vegetation, the atmosphere,
and human tissue all have the ability to conduct
heat directly through them (thermal conductivity)
onto another surface and to store heat (thermal
capacity). Some materials respond to changes in
temperature more rapidly or slowly than others
(thermal inertia).
44
Thermal Properties of Terrain
Thermal capacity (c) is the ability of a
material to store heat. It is measured as the
number of calories required to raise a gram of
material (e.g. water) 1 C (cal g-1 C-1). Water
has the highest thermal capacity (1.00). It
stores heat very well relative to all the other
materials. Thermal conductivity (K) is the rate
that heat will pass through a material and is
measured as the number of calories that will pass
through a 1-cm cube of material in 1 second when
two opposite faces are maintained at 1 C
difference in temperature (cal cm-1 sec-1 C).
The conductivity of a material is variable due to
soil moisture and particle size. Many rocks and
soils are extremely poor conductors of heat.
45
Thermal Inertia
Thermal inertia (P) is a measurement of the
thermal response of a material to temperature
changes and is measured in calories per square
centimeter per second square root per degree
Celsius (cal cm-2 sec -1/2 C-1). Thermal inertia
is computed using the equation P (K x p x
c)1/2 where K is thermal conductivity, p is
density (g cm-3), and c is thermal capacity.
Density is the most important property in this
equation because thermal inertia generally
increases linearly with increasing material
density.
46
Apparent Thermal Inertia
It would be wonderful if we could remotely
sense each of the aforementioned variables and
then simply compute thermal inertia.
Unfortunately, this is not the case because
conductivity, density, and thermal capacity must
all be measured in situ. Nevertheless, it is
possible to remotely sense and compute an
apparent thermal inertia measurement per pixel in
the following manner. A thermal infrared image is
acquired over the identical terrain in the
nighttime and in the early afternoon. The two
images are geometrically and radiometrically
registered to one another and the change in
temperature, ?T for a specific pixel is
determined by subtracting the nighttime apparent
temperature from the daytime apparent
temperature. The apparent thermal inertia (ATI)
per pixel is ATI 1 - A
?T with A being the albedo (reflectance)
measured in a visible band of the spectrum for
the pixel of interest.
47
Thermal Infrared Data Collection
Thermal infrared remote sensor data may be
collected by across-track thermal scanners,
and push-broom linear and area array
charge-coupled device (CCD)
detectors.
48
Thermal Infrared Multispectral Scanners
Daedalus DS-1260, DS-1268, and Airborne
Multispectral Scanner These scanners provide
most of the useful high spatial and spectral
resolution thermal infrared data for monitoring
the environment. The DS-1260 records data in 10
bands including a thermal-infrared channel (8.5
to 13.5 µm). The DS-1268 incorporates the
thematic mapper middle-infrared bands (1.55 -
1.75 µm and 2.08 - 2.35 µm). The AMS contains a
hot-target, thermal-infrared detector (3.0 to 5.5
µm) in addition to the standard thermal-infrared
detector (8.5 to 12.5 µm).
49
Thermal Infrared Multispectral Scanners
The diameter of the circular ground area viewed
by the sensor, D, is a function of the
instantaneous-field-of-view, ?, of the scanner
measured in milliradians (mrad) and the altitude
of the scanner above ground level, H, where
D H x ? For example, if the IFOV of the
scanner is 2.5 mrad, the ground size of the pixel
in meters is a product of the IFOV (0.0025) and
the altitude above ground level (AGL) in meters.
IFOVs range from 0.5 to 5 milliradians
50
Characteristics of a Thermal Infrared Airborne
Across-track Scanner
51
Ground Resolution Cell Size Along a Single
Across-Track Scan
52
Thermal Infrared Detectors
Thermal infrared detectors are usually composed
of InSb (indium antimonide) with a peak
sensitivity near 5µm GdHg (mercury-doped
germanium) with a peak sensitivity near 10 µm,
or HgCdTe (mercury-cadmium-telluride)
sensitive over the range from 8 - 14 µm. The
detectors are cooled to low temperatures (-196
C -243 C 73 K) using liquid helium or liquid
nitrogen. Cooling the detectors insures that the
radiant energy (photons) recorded by the
detectors comes from the terrain and not from the
ambient temperature of objects within the scanner
itself.
53
Peak Sensitivity of Indium-Antimonide and
Mercury-doped Germanium Thermal InfraredDetectors
54
Thermal Infrared Remote Sensing
There is an inverse relationship between having
high spatial resolution and high radiometric
resolution when collecting thermal infrared data.
The larger the radiometer instantaneous-field-o
f-view, ?, the longer the dwell time that an
individual detector can view the terrain within
the IFOV during a single sweep of the mirror. A
larger IFOV provides good radiometric resolution
which is the ability to discriminate between very
small differences in radiant energy exiting the
terrain element. In fact, the radiant energy
signal measured may well be much stronger than
any noise introduced from the sensor system
components. When this takes place we say that we
have a good signal to noise ratio. Of course, the
larger the IFOV, the poorer the ability to
resolve fine spatial detail. Selecting a smaller
IFOV will increase the spatial resolution. But,
the sensor will dwell a shorter time on each
terrain element during a sweep of the mirror,
resulting in poorer radiometric resolution and
perhaps a poorer signal to noise ratio.
55
Inverse-Square Law
Halving the distance of a remote sensing detector
from a point source quadruples the infrared
energy received by that detector. The
inverse-square law states that the intensity
of radiation emitted from a point source varies
as the inverse square of the distance between
source and receiver. Thus, we can obtain a
more intense, strong thermal infrared signal if
we can get the remote sensor detector as close to
the ground as practical.
56
The intensity of thermal radiation emitted from a
point source, S, varies as the inverse square of
the distance, d, between the source and remote
detector receiver, D1 or D2
57
Consideration
Most thermal infrared remote sensing
investigations try to maintain good radiometric
and spatial resolution by selecting a fairly
large IFOV such as 2.5 mrad, and flying at a
relatively low altitude to obtain smaller pixel
sizes. Unfortunately, at lower altitudes, the
high spatial resolution may be outweighed by the
fact that more flight lines are required to cover
the area compared to more efficient coverage at
higher altitudes with larger pixels. The pixel
size and the geographic size of the survey are
considered, objectives are weighed, and a
compromise is reached. Multiple flight lines of
aircraft MSS data are difficult to mosaic.
58
Geometric Correction of Across-Track Thermal
Infrared Scanner Data
Thermal infrared scanning systems (actually all
scanning systems) introduce numerous types of
geometric error that must be understood because
they impact a) the quality of the imagery for
visual or digital image processing and analysis,
and b) the creation of planimetric maps from the
thermal infrared data. The most important
considerations are ground swath width
spatial resolution cell size tangential
scale distortion, and one-dimensional relief
displacement.
59
Perspective Geometry of a Vertical Aerial
Photograph and Across-track One-dimensional
Relief Displacement and Tangential Scale
Distortion
60
Daytime Optical and Nighttime Thermal Infrared
Imagery of New York City
Thermal Infrared
Aerial Photograph
61
Daytime Optical and Nighttime Thermal Infrared
Imagery of the University of South Carolina Campus
April 26, 1981 456 am 1 x 1 m
2x reduction
62
Radiometric Calibration of Thermal Scanner Data
To use the thermal infrared remote sensor data
for practical purposes such as temperature
mapping, it is necessary to calibrate the
brightness values stored on the digital tape to
temperature values. This radiometric calibration
may be performed using internal blackbody
source referencing, or external empirical
referencing based on in situ data collection.
63
External Empirical Referencing of Thermal
Infrared Imagery
64
Push-broom Linear and Area Array Charge-coupled
device (CCD) Detectors
It is possible to make both linear and area
arrays that are sensitive to mid- and thermal
infrared radiation. Linear and area arrays allow
improved thermal infrared remote sensing to take
place because the solid-state microelectronic
detectors are smaller in size (e.g. 20 x 20 mm)
and weight, require less power to operate, have
fewer moving parts, and are more reliable
each detector in the array can view the ground
resolution element for a longer time (i.e. it is
as longer dwell time), allowing more photons of
energy from within the IFOV to be recorded by the
individual detector resulting in improved
radiometric resolution (the ability to resolve
smaller temperature differences) each
detector element in the linear or area array is
fixed relative to all other elements therefore
the geometry of the thermal infrared image is
much improved relative to that produced by an
across-track scanning system and some linear
and area thermal detectors do not even require
the cooling apparatus.
65
Forward-Looking Infrared (FLIR) Systems
For decades, the military organizations
throughout the world have funded the development
of FLIR type systems that look obliquely ahead of
the aircraft and acquire high-quality thermal
infrared imagery, especially at night. FLIR
systems collect the infrared energy based on the
same principles as an across-track scanner
previously discussed, except that the mirror
points forward about 45 and projects terrain
energy during a single sweep of the mirror onto a
linear array of thermal infrared detectors.
66
Forward Looking Infrared (FLIR) Examples
67
Diurnal Temperature Cycle of Typical Materials
The diurnal cycle encompasses 24 hours.
Beginning at sunrise, the earth begins
intercepting mainly short wavelength energy (0.4
- 0.7 ?m) from the Sun. From about 600 am to
800 pm, the terrain intercepts the incoming
short wavelength energy and reflects much of it
back into the atmosphere where we can use optical
remote sensors to measure the reflected energy.
However, some of the incident short wavelength
energy is absorbed by the terrain and then
re-radiated back into the atmosphere as thermal
infrared long wavelength radiation (3 - 14 ?m).
The outgoing longwave radiation reaches its
highest value during the day when the surface
temperature is highest. This peak usually lags
two to four hours after the midday peak of
incoming shortwave radiation, owing to the time
taken to heat the soil. The contribution of
reflected short wavelength energy and emitted
long wavelength energy causes an energy surplus
to take place during the day. Both incoming and
outgoing shortwave radiation become zero after
sunset (except for light from the moon and
stars), but outgoing longwave radiation continues
all night.
68
Peak Period of Daily Outgoing Longwave Radiation
and the Diurnal Radiant Temperature of Soils and
Rocks, Vegetation, Water, Moist Soil and Metal
Objects
69
Diurnal Temperature Cycle of Typical Materials
If all the curves for soils and rocks, water,
vegetation, moist soil, and metal objects lie
exactly on top of one another, then remote
sensing in the thermal infrared portion of the
spectrum would be of no value because all the
phenomena would have the same apparent radiant
temperature. There would be no contrast in the
imagery between the different phenomena.
Fortunately, there are only two times during the
day (after sunrise and near sunset) when some
materials like soils and rocks and water have
exactly the same radiant temperature. During this
crossover time period it is not wise to acquire
thermal infrared remotely sensed data.
Fortunately, some materials store heat more
efficiently that others, i.e. they have a higher
thermal capacity. For example, water has a much
higher thermal capacity than soils and rocks).
Its diurnal temperature range fluctuates very
little when compared with the dramatic
temperature fluctuation of soils and rocks during
a 24-hr period.
70
Solomon Blatt Fieldhouse on the University of
South Carolina Campus
March 10, 1983 430 am 0.5 x 0.5 m
71
Blackbody Radiation Curves for Several Objects
including the Sun and the Earth
Relative Radiated Intensity