CHAPTER 8 CHAPTER 8: Thermal Infrared Remote Sensing

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CHAPTER 8CHAPTER 8CHAPTER 8:CHAPTER 8:Thermal InfraredThermal InfraredRemote SensingRemote Sensinggg

REFERENCE: Remote Sensing REFERENCE: Remote Sensing of the Environment of the Environment John R. Jensen (2007)John R. Jensen (2007)Second EditionSecond EditionPearson Prentice HallPearson Prentice Hall

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Thermal Infrared Remote SensingThermal Infrared Remote Sensing

Thermal infrared energy is emitted from all objectsthat have a temperature greater than absolute zero.

Therefore, all the features we encounter in the landscape on atypical day (Sun, vegetation, soil, rocks, water, and evenpeople) emit thermal infrared electromagnetic radiation.

Humans eyes cannot detect differences in thermal infraredenergy because they are primarily sensitive to visible lightenergy because they are primarily sensitive to visible lightfrom 400 to 700 nm. Our eyes are not sensitive to thereflective infrared (700 nm - 3.0 μm) or thermal infraredenergy (3.0 - 14 μm).

• The astronomer Sir Frederick William Herschel (1738-1822) discovered the infrared portion of the electromagnetic spectrum in

History of Thermal Infrared Remote Sensing

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. p

• In World War I, S. O. Hoffman could detect men at 120 m and eventually aircraft.

• In the 1930s, Germany developed the Kiel system for discriminating between bombers and night fighters.

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• 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 (Ge:Hg), 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.

• The first declassified satellite remote sensor data were collected by the U. S. Television IR Operational Satellite (TIROS) launched


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 (HCMM) on April 26, 1978 that obtained 600 x 600 m spatial resolution thermal infrared data (10.5 - 12.6 μm) both day (1:30 pm) and night (2:30 am) This was one of the first scientifically orientednight (2:30 am). This was one of the first scientifically oriented (geology) thermal infrared systems.

• NASA’s 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.

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• In 1980, NASA and the Jet Propulsion Laboratory developed the th l i f d lti t l (TIMS) th t i


thermal infrared multispectral scanner (TIMS) that acquires thermal infrared energy in six bands at wavelength intervals of <1.0 μm.

• Successful studies using TIMS resulted in the development of the 15-channel Airborne Terrestrial Applications Sensor (ATLAS).

• 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 μm) along with two bands of middle infrared data.

• Today, the NOAA Geostationary Operational Environmental Satellite (GOES) collects thermal infrared


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.

• The NOAA Advanced Very High Resolution Radiometer 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 person’s daily life as we watch the nightly weather report.

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Characteristics Characteristics of a Thermal of a Thermal

Infrared Infrared Airborne Airborne

amplifier

high-density magnetic

tape

hot lib i

optional film

recorder focusing mirrors

dewar of liquid

nitrogen

detector

recorder mirror

modulated light

source

motor

scan mirror

AcrossAcross--track track ScannerScanner

H

β β

calibration source cold

source

radiant flux, Φ within the

instantaneous-field-of-view, β

total angular field-of-

view

D

Thermal Infrared Image of Effluent Entering the Savannah River Swamp System

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Kinetic Heat, Temperature, Kinetic Heat, Temperature, Radiant Energy and Radiant FluxRadiant 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) Allkinetic 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.

• The amount of heat can be measured in calories (the amount of h t i d t i th t t f 1 f t 1 ˚C) Wheat 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 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.

• Fortunately for us, an object’s internal kinetic heat is also converted to radiant energy (often called external or apparent


gy ( ppenergy). The electromagnetic radiation exiting an object is called radiant flux (Φ) 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 (Tki ) and the amount of radiantkinetic 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 object’s true kinetic temperature. This is the basis of thermal infrared remote sensing.

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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.p p y y

Methods of Heat TransferMethods of Heat Transfer

Pan

Conduction

in contact with burnera.

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.

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Methods of Heat TransferMethods of Heat Transfer

Convection

Terrain

Pulse of

warm air

b.

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.

Methods of Heat Transfer

λ

Radiation

c.

EarthSun

Electromagnetic wave

The transfer of energy by electromagnetic radiation is of primary interest to remote 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.

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Atmospheric Windows in the Atmospheric Windows in the Electromagnetic SpectrumElectromagnetic Spectrum

Thermal Radiation LawsThermal 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 radiantquantitative 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 Wein’s displacement law.

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The total spectral radiant flux exitance (Mb) measured in watts m2

leaving a blackbody is proportional to the fourth power of its temperature (T).

Stephen Boltzmann LawStephen Boltzmann Law

The Stefan-Boltzmann law is expressed as:

Mb = σT4

where σ is the Stefan-Boltzmann constant equaling 5.6697 x 10-8 W m-2 K-4, and T is temperature in degrees Kelvin. The total radiant exitance is the integration of all the area under the blackbody radiation curveradiation curve.

The Sun produces more spectral radiant exitance (Mb) 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.

The Stefan-Boltzmann Law states that total

Stephen Boltzmann LawStephen Boltzmann Law

Law states that total spectral radiant exitance (Mb) leaving a blackbody is proportional to the fourth power of its temperature (T). p ( )

Mb = σT4

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Th l ti hi b t th t t t f bl kb d

Wein’sWein’s Displacement LawDisplacement Law

The relationship between the true temperature of a blackbody (T) in degrees Kelvin and its peak spectral exitance or dominant wavelength (λmax) is described by the

Wein’s displacement law:

λmax = k = 2898 μm ˚K

T T

where k is a constant equaling 2898 μm ˚K.


Wien's Law tells us that objects of different temperature emit spectra that peak at different wavelengths.

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For example, the average temperature of the Earth is 300 ˚K (80 ˚F).


K (80 F).

We compute the Earth’s dominant wavelength as:

λmax = 2898 μm ˚K

T

λmax = 2898 μm ˚K = 9.67 μm max

300 ˚K

WHAT IS SUN’S DOMINANT WAVELENGTH?

• The dominant wavelength provides valuable information about which part of the thermal spectrum we might want to


p p gsense in. For example, if we are looking for 800 ˚K forest fires that have a dominant wavelength of approximately 3.62 μm then the most appropriate remote sensing system might be a 3-5 μm thermal infrared detector.

• If we are interested in soil, water, and rock with ambient temperatures on the earth’s surface of 300 ˚K and a dominant wavelength of 9.66 μm, then a thermal infrared detector operating in the 8 - 14 μm region might be most appropriate.

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Blackbody Blackbody Radiation Radiation Curves for Curves for

Several Several Objects Objects Objects Objects

including the including the Sun and EarthSun and Earth

Explain the hot spot?

This can of suds is ice cold straight out of the fridge. When scanned with an infrared camera

Live image reveals truth.

The curtain is lifted and the truth revealed. The paint on the outside

scanned with an infrared camera you would expect the entire image

to be relatively even in temperature and to appear "cold" in relation to the background. Can

you explain the apparent "hot" spot in the center of the can.

Hint: it's not a fingerprint!

of the can has been scratched off in a small area. The bare aluminum has a different emissivity than the

painted aluminum. The camera can only allow for one emissivity setting

at one time so to the detector the bare aluminum "images" hotter than

the rest of the can.

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The world is not composed of radiating blackbodies. Rather it is composed of selectively radiating bodies such as rocks,

Emissivity (Emissivity (εε))

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, ε, is the ratio between the radiant flux exiting a real-world selective radiating body (Mr) and a blackbody at the same temperature (Mb):

(Mb) etemperatur same theat blackbody a of emittanceRadiant (Mr)object an of emittanceRadiant

=

• All selectively radiating bodies have emissivities ranging from 0 to <1 that fluctuate depending upon the wavelengths

Emissivity (Emissivity (εε))

p g p gof 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 μm. Others such as polished aluminum (0.08) and stainless steel (0.16) have very low emissivities.

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Spectral emissivity of a blackbody, a graybody, and a

hypothetical l ti di t

1

0.5

ectr

al E

mis

sivi

ty, ε

selective radiator

blackbody

ral Em

issi

vit

y,

ε

selective radiator0.1

0.1 1 10 100

106

108

Wavelength, μm

Spe

Exi

tanc

e -1

6,000 ÞK bl kb d

graybody

a.

Spectral radiant exitance distribution

Sp

ect

rt

Exit

an

cem

-1

0.1 100

100101

102

104

Wavelength, μm

Spec

tral

Rad

iant

EW

m-2

μm

- blackbody ε = 1.0

6,000 ÞK graybody ε = 0.1

6,000 ÞK selective radiator

b.

of the blackbody, graybody, and hypothetical

selective radiatorSp

ect

ral R

ad

ian

W m

-2u

m

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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. gy

• 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.

• 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.

ti th d f il ti ff t• 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.

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• viewing angle - the emissivity of an object can vary with sensor viewing anglesensor viewing angle.

We must take into account an object’s emissivity when we use our remote radiant temperature measurement to measure the object’s true kinetic temperature.

This is done by applying Kirchoff’s radiation law.

Remember that the terrain intercepts incident (incoming) radiant flux (Φ ) This incident energy interacts with

Kirchoff’sKirchoff’s Radiation LawRadiation Law

radiant flux (Φi). This incident energy interacts with terrain materials. The amount of radiant flux reflected from the surface (Φr), the amount of radiant flux absorbed by the surface (Φα), and the amount of radiant flux transmitted through the surface (Φτ) can be carefully measured as we apply the principle of conservation of energy and attempt to keep track of what happens to all theenergy and attempt to keep track of what happens to all the incident energy. The general equation for the interaction of spectral (λ) radiant flux with the terrain is:

1 = Φiλ = Φrλ + Φαλ + Φτλ

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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. αλ ~ ελ. 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 gthe other side of the terrain element. Therefore, we may assume transmittance, τλ = 0. Substituting emissivity for absorptance and removing transmittance from the equation yields:

1 = rλ + ελ

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


y gythe energy leaving the object must be accounted for by the inverse relationship between reflectance (rλ) and emissivity (ελ). 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.

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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 j g pthe 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 (Mr):

Mr = ε σTkin4

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.

• 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


p , kinthat the incorporation of emissivity in the previous equation has improved our measurement to the point that:

Mr = ε σ Tkin4 and we assume that

Mb = σ Trad4 and

M = Mb thenMr Mb then,

σ Trad4 = ε σ 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 = ε 1/4Tkin

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Water, rocks, soil, vegetation, the atmosphere, and human tissue all have the ability to conduct heat directly through

Thermal Properties of TerrainThermal Properties of Terrain

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).

• Thermal capacity (c) is the ability of a material to store heat. It is measured as the number of calories required to

Thermal Properties of TerrainThermal Properties of Terrain

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 p gsecond 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.

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• Thermal inertia (P) is a measurement of the thermal response of a material to temperature changes and is

Thermal InertiaThermal Inertia

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 cy, p y (g ),is thermal capacity. Density is the most important property in this equation because thermal inertia generally increases linearly with increasing material density.

• 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

Apparent Thermal InertiaApparent Thermal Inertia

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) perdaytime 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.

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Thermal Infrared Thermal Infrared Data CollectionData 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.device (CCD) detectors.

• Daedalus DS 1260 DS 1268 and Airborne Multispectral

Thermal Infrared Thermal Infrared Multispectral ScannersMultispectral 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 i h h i iddl i f dDS-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).

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Thermal Infrared Thermal Infrared Multispectral ScannersMultispectral Scanners

• The diameter of the circular ground area viewed by the sensor, D, is a function of the instantaneous-field-of-view, β, of the scanner measured in milliradians (mrad) and the altitude of the scanner above ground level, H, where:

D = H x β

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

Characteristics Characteristics of a Thermal of a Thermal

Infrared Infrared Airborne Airborne

amplifier

high-density magnetic

tape

hot lib i

optional film

recorder focusing mirrors

dewar of liquid

nitrogen

detector

recorder mirror

modulated light

source

motor

scan mirror

AcrossAcross--track track ScannerScanner

H

β β

calibration source cold

source

radiant flux, Φ within the

instantaneous-field-of-view, β

total angular field-of-

view

D

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Ground Resolution Cell Size Along a Ground Resolution Cell Size Along a Single AcrossSingle Across--Track ScanTrack Scan

Thermal infrared detectors are usually composed of:

• In:Sb (indium antimonide) with a peak sensitivity

Thermal Infrared DetectorsThermal Infrared Detectors

In:Sb (indium antimonide) with a peak sensitivity near 5µm;

• Gd:Hg (mercury-doped germanium) with a peak sensitivity near 10 µm, or

• Hg:Cd:Te (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.

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Peak Sensitivity of Indium-Antimonide and Mercury-doped

1011

1012

In:Sb (Indium Antimonide)

and Mercury-doped Germanium Thermal

InfraredDetectors

109

1010

Rel

ativ

e R

espo

nse

Ge:Hg (Mercury-doped Germanium)

1 1.5 2 3 4 5 6 7 8 10 15 20 108

10

Wavelength, μm

There is an inverse relationship between having high spatial resolution and high radiometric resolution when collecting thermal infrared data

Thermal Infrared Remote SensingThermal Infrared Remote Sensing

thermal infrared data. • The larger the radiometer instantaneous-field-of-view, β, 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

i i t d d f th t t Wh thi t knoise 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.

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Halving the distance of a remote sensing detector from a

InverseInverse--Square LawSquare 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.

D2

D1 2d

Inverse-square Law

remote detectors

The intensity of thermal

radiation emitted from a

i t S1

d

2d

Blackbody Point Source, S

1 cm2 point source, S, varies as the

inverse square of the distance, d,

between the source and

remote detectorremote detector receiver, D1 or

D2

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Most thermal infrared remote sensing investigations try to maintain good radiometric and spatial resolution by:

ConsiderationConsideration

• 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 efficientrequired 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.

Thermal infrared scanning systems (actually all scanning

Geometric Correction of AcrossGeometric Correction of Across--Track Track Thermal Infrared Scanner DataThermal Infrared Scanner Data

g y ( y gsystems) 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; ground swath width;

• spatial resolution cell size;

• tangential scale distortion, and

• one-dimensional relief displacement.

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Perspective Geometry of a Vertical Aerial Perspective Geometry of a Vertical Aerial Photograph Photograph

and Acrossand Across--track Onetrack One--dimensional Relief dimensional Relief DisplacementDisplacement

and Tangential Scale Distortionand Tangential Scale Distortion

Daytime Optical

and Nighttime Thermal Thermal Infrared Imagery of New

York City

Thermal Infrared

Aerial Photograph

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To use the thermal infrared remote sensor data for practical

Radiometric Calibration of Radiometric Calibration of Thermal Scanner DataThermal 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 internal blackbody source referencing, or

• external empirical referencing based on in situ data collection.

External Empirical Referencing External Empirical Referencing of Thermal Infrared Imageryof Thermal Infrared Imagery

100

80

60

40

100

80

60

40

adio

met

rica

lly U

ncal

ibra

ted

e

Sens

ing

Bri

ghtn

ess

Val

ue, B

V ij

40200

20

60 80 40200

20

60 80

BVij = -0.0148x2 + 2.1157x + 26.303

R2 = 0.9895

In situ True Kinetic Temperature Measurement, T kin

a. b. 0 0

Linear Non-linear: 2nd Order Polynomial

BVij = 0.6586x + 56.173

R2 = 0.8631

Ra

Rem

ote

In situ True Kinetic Temperature Measurement, T kin

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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:

PushPush--broom Linear and Area Array broom Linear and Area Array ChargeCharge--coupled device (CCD) Detectorscoupled device (CCD) Detectors

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 y g pradiometric 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.

ForwardForward--Looking Infrared (FLIR) Looking Infrared (FLIR) SystemsSystems

• 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 i i l t k i l di dprinciples 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.

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Forward Forward Looking Looking Infrared Infrared (FLIR) (FLIR)

ExamplesExamplesExamplesExamples

• The diurnal cycle encompasses 24 hours. Beginning at sunrise, the earth begins intercepting mainly short wavelength energy (0.4 - 0.7 μm) from the Sun From about 6:00 am to 8:00 pm the terrain intercepts the

Diurnal Temperature Cycle Diurnal Temperature Cycle of Typical Materialsof Typical Materials

the Sun. From about 6:00 am to 8:00 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 μm). 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.

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Peak Period of Peak Period of Daily Outgoing Daily Outgoing

Longwave Longwave Radiation and Radiation and Radiation and Radiation and

the Diurnal the Diurnal Radiant Radiant

Temperature of Temperature of Soils and Rocks, Soils and Rocks,

Vegetation, Vegetation, Vegetation, Vegetation, Water, Moist Soil Water, Moist Soil

and Metal and Metal ObjectsObjects

Nighttime Thermal Infrared Nighttime Thermal Infrared Imagery of an AirportImagery of an Airport

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LL--BAND ANTENNABAND ANTENNA

NOAA 12/14NOAA 15/16

Advanced Very High Resolution RadiometerAdvanced Very High Resolution Radiometer

((AVHRR)AVHRR)

BandBand Wavelength (Wavelength (μμm)m)BandBand Wavelength (Wavelength (μμm)m)11 0.580.58--0.680.6822 0.720.72--1.101.1033 3.553.55--3.933.9344 10.510.5--11.511.555 11.511.5--12.512.5

Sea Surface Temperature (SST)Sea Surface Temperature (SST)

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SatelliteNumber

LaunchDate

AscendingNode

DescendingNode Service Dates

TIROS-N 10/13/1978 1500 300 10/19/78 - 01/30/80

NOAA-6 6/27/1979 1930 730 06/27/79 - 11/16/86

TEMPORAL COVERAGE OF AVHRR

NOAA-7 6/23/1981 1430 230 08/24/81 - 02/01/85

NOAA-8 3/28/1983 1930 730 05/03/83 - 10/31/85

NOAA-9 12/12/1984 1420 220 02/25/85 - 11/07/98

NOAA-10 9/17/1986 1930 730 11/17/86 - 09/16/91 (still on standby)


NOAA-12 5/14/1991 1930 730 09/16/91 - 12/14/98


NOAA-14 12/30/1994 1340 140 12/30/94 - Present

NOAA-15 5/13/1998 1930 730 05/13/98 - Present

NOAA-16 9/21/2000 1340 140 Present

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LAKE SUPERIORLAKE SUPERIOR

MCSST Algorithm

Daytime Pass:

SST (oC) = a*T4 + b*(T4-T5) + cSST ( C) = a T4 + b (T4 T5) + c

Nighttime Pass:

SST (oC) = a*T4 +b*(T3-T5) + c

Where,

T3 = Brightness Temperature at Channel 3T4 = Brightness Temperature at Channel 4T5 = Brightness Temperature at Channel 5a b c = Weighting Coefficientsa, b, c = Weighting Coefficients

Reference: McClain, E.P., W.G. Pichel, and C.C. Walton. (1985)Comparative performance of AVHRR-Based Multichannel SeaSurface Temperature, Journal of Geophysical Research.90(11):11587-11601

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A New Set of MCSST Equations for NOAA-9/AVHRR

SHOICHI KIZU1 and FUTOKI SAKAIDA2

1Department of Geophysics, Graduate School of Science, Tohoku University, Aoba-ku, Sendai 980-77, Japan2Ocean Mechanical Engineering Chair, Kobe University of Mercantile Marine,5-1-1, Fukae-Minami-machi, Higashi-Nada-ku, Kobe 658, Japan5 1 1, Fukae Minami machi, Higashi Nada ku, Kobe 658, Japan(Received 24 July 1995; in revised form 26 October 1995; accepted 27 October 1995)

A new set of multi-channel sea surface temperature (MCSST) equations for theAdvanced Very High Resolution Radiometer (AVHRR) on NOAA-9 is derivedfrom regression analyses between two-channel brightness temperatures and in situSST obtained from moored buoys around Japan. Two equations are derived: onefor daytime and the other for nighttime. They are linear split window type and boththe equations contain a term dependent on satellite zenith angle, which has notbeen accounted for in the previous daytime split window equations for NOAA-9.It is shown that the new set of equation can give SSTs in much better precision thanthose without the zenith-angle-dependent terms. It is also found that the splitwindow equation for NOAA-9 provided by the National Oceanographic andAtmospheric Administration/National Environmental Satellite, Data and InformationService (NOAA/NESDIS) considerably underestimates the daytime SSTs;Service (NOAA/NESDIS) considerably underestimates the daytime SSTs;sometimes nighttime SSTs are even higher than daytime SSTs. This is because thezenith angle effect to the radiation deficit is neglected in the daytime equation byNOAA/NESDIS. By using the new MCSST equations, it is expected that the qualityof satellite MCSST would be much improved, at least in regional applicationsaround Japan, for the period of NOAA-9’s operation.

Journal of OceanographyVol. 52, pp. 235 to 249. 1996

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Sea Surface TemperatureSea Surface Temperature

ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is an imaging instrument that is flying on Terra, a satellite ) g g y g ,launched in December 1999 as part of NASA's Earth Observing System (EOS). ASTER is a cooperative effort between NASA and Japan's Ministry of Economy, Trade and Industry (METI) and the Earth Remote Sensing Data Analysis Center (ERSDAC). ASTER will be used to obtain detailed maps of land surface temperature, emissivity, reflectance and elevation. The EOS platforms are part of NASA's Earth Science Enterprise, whose goal is to obtain a better understanding of the interactions between the biosphere, hydrosphere, lithosphere and atmosphere.

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The current eruption of Mt. Etnastarted on July 17, 2001and hascontinued to the present (august3, 2001). This ASTER image wasacquired on Sunday, July 29 andshows advancing lava flows onthe southern flank of Mt. Etnaabove the town of Nicolosi,which is potentially threatened ifthe eruption increases inmagnitude. Also visible areglowing summit craters aboveg o g su t c ate s abo ethe main lava flows, and a smallfissure eruption. The bright puffyclouds were formed from watervapor released during theeruption. The image covers anarea of 24 x 30 km.

On April 3, 2000 ASTERcaptured this image of theerupting Mt. Usu volcano inHokkaido, Japan. This falsecolor infrared image,covering an area of 18 km(13 miles) by 22 km (15miles), of Mt Usu volcano is),dominated by Lake Toya, anancient volcanic caldera.

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On April 5 ASTER capturedthis night time thermalinfrared image of Mt. Usu.Hot thermal anomalies,appearing as bright spots,are seen on the west flankof Usu, site of theeruptions. Additional hote upt o s dd t o a otspots appear at thesummit, and at a vent onthe east flank.

LEFT: A January 6, 2002 ASTER nighttime thermal infrared image of Chiliquesvolcano in Chile shows a hot spot in the summit crater and several others along theupper flanks of the edifice, indicating new volcanic activity.

RIGHT: The daytime image was acquired on November 19, 2000 and was created bydisplaying ASTER bands 1,2 and 3 in blue, green and red. The nighttime image wasacquired January 6, 2002, and is a color-coded display of a single thermal infraredband. The hottest areas are white, and colder areas are darker shades of red.

CHAPTER 8 CHAPTER 8: Thermal Infrared Remote Sensing

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