Thermal Infrared Remote Sensing John R Jensen Department

Thermal Infrared Remote Sensing John R. Jensen Department of Geography University of South Carolina Columbia, South Carolina 29208

Selected Applications of Thermal Infrared Remote Sensing

Nighttime Thermal Infrared Imagery of an Airport

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 thermal characteristics of the landscape.

Atmospheric Windows in the Electromagnetic Spectrum

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.

Methods of Heat Transfer

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

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 (Ge: Hg), indium antimonide (In. Sb) and other substances that are very responsive to infrared radiation. We also have computers to rapidly process and display thermal radiometric measurements. • In 1968, the government declassified thermal infrared remote sensing systems that did not exceed a certain spatial resolution and temperature sensitivity.

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 (1: 30 pm) and night (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.

History of Thermal Infrared Remote Sensing • In 1980, NASA and the Jet Propulsion Laboratory developed thermal infrared multispectral scanner (TIMS) that acquires thermal infrared energy in six bands at wavelength intervals of <1. 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 thermal infrared sensor.

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 person’s daily life as we watch the nightly weather report.

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 terrain’s emitted thermal infrared electromagnetic radiation. Finally, the analyst must understand how both the sensor system itself and the terrain can introduce noise into thermal infrared image that might make the data less useful or lead to incorrect image interpretation.

Characteristics of a Thermal Infrared Airborne Across-track Scanner

Pre-dawn Thermal Infrared Image of Effluent Entering the Savannah River Swamp System Savannah River 2 x reduction March 31, 1981 4: 28 am; 3 x 3 m

Pre-dawn Thermal Infrared Image of a Residential Subdivision in Forth Worth, Texas 250 m AGL 1 mrad IFOV 6: 45 am Jan 10, 1980 0. 25 x 0. 25 m

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.

Kinetic Heat, Temperature, Radiant Energy and Radiant Flux • Fortunately for us, an object’s 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 object’s true kinetic temperature. This is the basis of thermal infrared remote sensing.

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.

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 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 (H 2 O), carbon dioxide (CO 2), and ozone (O 3) are responsible for most of the absorption. For example, atmospheric water vapor (H 2 O) absorbs most of the energy exiting the terrain in the region from 5 to 7 m making it almost useless for remote sensing.

Atmospheric Windows in the Electromagnetic Spectrum

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, Kodak’s 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).

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 Earth’s ozone (O 3) layer absorbs much of 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.

Daytime Optical and Nighttime Thermal Infrared Imagery of the University of South Carolina Campus 2 x reduction April 26, 1981 4: 56 am 1 x 1 m

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 Wein’s displacement law.

Stephen Boltzmann Law The total spectral radiant flux exitance (Fb) measured in watts m 2 leaving a blackbody is proportional to the fourth power of its temperature (T). This is the Stefan-Boltzmann law and is expressed as: Fb = k. T 4 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 m 2 (the area under the curve) increases and the radiant energy peak shifts to shorter wavelengths.

Blackbody Radiation Curves for Several Objects including the Sun and Earth

Wein’s 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 Wein’s displacement law: max = k = 2898 m ˚K T where k is a constant equaling 2898 m ˚K. T

Wein’s Displacement Law For example, the average temperature of the Earth is 300 ˚K (80 ˚F). We compute the Earth’s dominant wavelength as: max = 2898 m ˚K T max = 2898 m ˚K = 9. 67 m 300 ˚K

Wein’s Displacement Law • The dominant wavelength provides valuable information about which part of 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 earth’s 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.

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

Emissivity • All selectively radiating bodies have emissivities ranging from 0 to <1 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.

Spectral Radiant Exitance W m-2 um-1 Spectral Emissivity, e Spectral emissivity of a blackbody, a graybody, and a hypothetical selective radiator 2 x reduction Spectral radiant exitance distribution of the blackbody, graybody, and hypothetical selective radiator

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.

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.

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

Kirchoff’s 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: = i = r + +

Kirchoff’s Radiation Law • Dividing each of the variables by the original incident radiant flux: i / i = ( r / 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.

Kirchoff’s 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 +

Kirchoff’s 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.

Kirchoff’s 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.

Kirchoff’s 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 Trad 4 and Fr = Fb then, k Trad 4 = 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 = 1/4 Tkin

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).

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.

Thermal Inertia • Thermal inertia (P) is a measurement of 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.

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.

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.

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 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).

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=Hx 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 of a Thermal Infrared Airborne Across-track Scanner

Ground Resolution Cell Size Along a Single Across-Track Scan

Thermal Infrared Detectors Thermal infrared detectors are usually composed of: • 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.

Peak Sensitivity of Indium. Antimonide and Mercurydoped Germanium Thermal Infrared. Detectors

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-of-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.

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.

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, D 1 or D 2

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.

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 thermal infrared data. The most important considerations are: • ground swath width; • spatial resolution cell size; • tangential scale distortion, and • one-dimensional relief displacement.

Perspective Geometry of a Vertical Aerial Photograph and Across-track One-dimensional Relief Displacement and Tangential Scale Distortion

Daytime Optical and Nighttime Thermal Infrared Imagery of New York City Aerial Photograph Thermal Infrared

Daytime Optical and Nighttime Thermal Infrared Imagery of the University of South Carolina Campus 2 x reduction April 26, 1981 4: 56 am 1 x 1 m

Radiometric Calibration of Thermal Scanner Data To use 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.

External Empirical Referencing of Thermal Infrared Imagery

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 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.

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 highquality 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.

Forward Looking Infrared (FLIR) Examples

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 6: 00 am to 8: 00 pm, the terrain intercepts the incoming short wavelength energy and reflects much of it back into the atmosphere 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.

Peak Period of Daily Outgoing Longwave Radiation and the Diurnal Radiant Temperature of Soils and Rocks, Vegetation, Water, Moist Soil and Metal Objects

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 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.

Solomon Blatt Fieldhouse on the University of South Carolina Campus March 10, 1983 4: 30 am 0. 5 x 0. 5 m

Relative Radiated Intensity Blackbody Radiation Curves for Several Objects including the Sun and the Earth