Remote Sensing

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Thermal Remote Sensing

Distinguishing materials on the ground using differences in emissivity and temperature

Landsat-based thermal change of Nisyros Island (volcanic)

Thermal = Emitted Infrared • IR = 0.76 um to 1000 um

– Reflective IR = 0.7 – 3.0 um – Thermal IR for remote sensing = 7 – 18 um

• Sometimes called far IR (vs. near and mid IR)

• Experiences almost no atmospheric scattering

• But…lots of absorption by atmospheric gases (e.g., CO2) – Must use atmospheric windows for rem. sens.

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The Infrared portion of the electromagnetic spectrum

Emitted Thermal

Atmospheric transmission by λ

Thermal Properties of Objects

• All objects with temperature > 0o K emit thermal radiation – Amount depends on temperature (Stefan-

Boltzman Law) • M = εσT4

– Peak wavelength emitted also depends on temperature (Wien’s Displacement Law)

• Peak λ(µm) = 3000/T(oK)

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Wien’s Displacement Law

Emissivity

• Emissivity is the ratio of the emittance of an object to that of a Black Body – A black body has ε = 1

– A white body has ε = 0

– Water has ε close to 1

– Most vegetation has ε close to 1

– Many minerals have ε << 1

• Can find tables of emissivities in reference books and textbooks

Kinetic Temperature vs. Radiant Temperature

• Kinetic temperature is caused by the vibration of molecules – sometimes called “true temperature”

– measured using conventional temperature scales (e.g. oF, oC, oK)

• Radiant temperature is the emitted energy of an object – sometimes called “apparent temperature”

– what we measure with thermal remote sensing

– depends on kinetic temperature and emissivity

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Thermal Remote Sensing

• Incoming radiation from the sun is absorbed (converted to kinetic energy) and object emits EMR

• Objects vary in the amount of sun they “see” (different slopes, etc.) and in their emissivity

• Thermal remote sensing is sensitive to differences in emissivity.

Interpreting Thermal Images • Thermal images are often single-band and

look like black and white photographs – Bright areas = relatively warmer places – Dark areas = relatively cooler places – Can be the opposite for thermal weather

images!

• Must know if the image is a negative or a positive!

• Should know the time of day the image was acquired – day vs. night alters the interpretation

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Atlanta -- Daytime Atlanta -- Nighttime

Daily change in radiant temperature of common objects

North

Thermal Infrared Multispectral Scanner (TIMS) image of Death Valley

Daytime Positive – Bright = warm, Dark = cool

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Multi-band thermal

• Thermal imagery can also be multi-band (different parts of the thermal IR spectrum)

• When displayed in color, colors primarily represent differences in emissivity.

North

TIMS image of Death Valley made by combining thermal bands from different wavelengths after “decorrelation stretching”

Interpretation (cont.) • It is difficult to accurately calculate the

kinetic temperature of objects from their radiant temperature – Must know the emissivity of the target(s)

– Often have to estimate or assume emissivity values

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Complicating Factors

• Topography (effects amount of incoming radiation from sun)

• Fine scale differences in emissivities of materials in scene

• Cloud cover history

• Precipitation history – differences in soil moisture

• Vegetation canopy geometry

• Geothermal areas

• Many others

Thermal Sensors

• Thermal Infrared Multispectral Scanner (TIMS) (Airborne – 18 m spatial res.)

• Landsat 3 MSS (237 m spatial resolution)

• Landsat TM (Band 6) (120 m spatial)

• Landsat ETM+ (Band 6) (60 m spatial)

• Landsat 8 (Band 10 and 11) (100 m spatial)

• ASTER (5 thermal bands at 90 m spatial)

• MODIS (many thermal bands at 1 km spatial resolution)

• Many others…

Applications

• Agricultural water stress (energy balance)

• Heat loss from urban areas

• Identifying and mapping materials based on their emissivities (e.g. minerals)

• Earthquake and volcanic activity prediction

• Mapping moisture amounts

• Ocean current mapping

• Plumes of warm water from power plants, etc.

• Atmospheric studies, weather forecasting, etc.

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Evapotranspiration (ET) estimation using thermal RS

• If you know how much energy is being used to evaporate water, you can estimate how much water is evaporating!

E = H + L + r + G

Where E = irradiance, H = sensible heat, L = latent heat, r = reflected energy, and G = ground storage of energy.

- R

R

Thermal Image of Lava Flows

ASTER

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Airborne thermal image of warm creek flowing into ocean near Anchorage, AK

ASTER images of San Francisco.

Bottom right is thermal image used for water temperature

Summary – Thermal Remote Sensing

• Typically used to map surface materials that differ in thermal properties (like emissivity)

• Usually NOT used to map absolute kinetic temperature

• Many applications but not especially good for distinguishing among vegetation types because all veg has about the same emissivity

• Gives us another tool to help distinguish materials that may be spectrally similar in the reflected wavelengths!