1. Landsat-based thermal change of Nisyros Island (volcanic)

2. November 2014 lava flow on Kilauea (USGS Volcano Observatory)(

3. Thermal Remote Sensing
Distinguishing materials on the ground using differences in emissivity and temperature

4. Learning Objectives
What is emissivity and why is it relevant to thermal RS?
What is the difference between kinetic temperature and radiant temperature?
How do you interpret thermal images?
What is thermal lag and how can it be used to ID materials?
How can you use thermal RS to estimate actual evapotranspiration?

5. Thermal = Emitted Infrared
IR = μm to 1000 μm (wide range)
Reflective IR = 0.72 μm – 3.00 μm
Thermal IR for remote sensing = 7– 18 μm
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.

6. The Infrared portion of the electromagnetic spectrum
Emitted Thermal

7. Atmospheric transmission by λ

8. Thermal Properties of Objects
All objects with temperature > 0o K emit thermal radiation
Amount depends on temperature (Stefan-Boltzman Law)
M = єσT4
Peak wavelength emitted also depends on temperature (Wien’s Displacement Law)
Peak λ(µm) = 3000/T(oK)

9. Wien’s Displacement Law

10. Emissivity
Emissivity is the ratio of the energy emitted by an object to that of a Black Body at the same temperature
A black body has є = 1
A white body has є = 0
Water has є close to 1
Most vegetation has є close to 1
Many minerals have є << 1
Depends on wavelength!
Can find tables of emissivities in reference books and textbooks

11. 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

13. 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.

14. Interpreting Thermal Images
Thermal images are often single-band and so displayed as monochrome images.
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

15. Atlanta -- Daytime
Atlanta -- Nighttime

16. Daily change in radiant temperature of common objects

17. North
Thermal Infrared Multispectral Scanner (TIMS) image of Death Valley
Daytime Positive – Bright = warm, Dark = cool

18. 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.

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

20. 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

21. Complicating Factors
Topography (effects amount of incoming radiation from sun)
Fine scale differences in emissivity of materials in scene
Cloud cover history
Precipitation history – differences in soil moisture
Vegetation canopy geometry
Geothermal areas
Many others

22. 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 8 (Bands 10 & 11) (100 m spatial)
Landsat ETM+ (Band 6) (60 m spatial)
ASTER (5 thermal bands at 90 m spatial)
MODIS (many thermal bands at 1 km spatial resolution)
Many others…

23. 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.

24. 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.

25. R
- R

26. Thermal Image of Lava Flows
ASTER

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

28. ASTER images of San Francisco.
Bottom right is thermal image used for water temperature

29. 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!