Landsat-based thermal change of Nisyros Island (volcanic)

November 2014 lava flow on Kilauea (USGS Volcano Observatory) (http://hvo.wr.usgs.gov)

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

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?

Thermal = Emitted Infrared IR = 0.720 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.

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 = єσT4 Peak wavelength emitted also depends on temperature (Wien’s Displacement Law) Peak λ(µm) = 3000/T(oK)

Wien’s Displacement Law

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

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

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 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

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

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

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

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…

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.

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

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!