# METR155 Remote Sensing Lecture 4: Thermal Radiation, Spectral Signature.

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METR155 Remote Sensing Lecture 4: Thermal Radiation, Spectral Signature

Question: Earth Surface Equilibrium temperature (ET)
The energy that is absorbed by the Earth will be one that reaches the Earth from the Sun then subtracted from that which is reflected from the top of the atmosphere. The fraction of light reflected from the top of the atmosphere called the albedo (A). The albedo of Earth is 0.3 (approximately 30%). What would be the ET?

Answer the total power absorbed by the Earth is given by equation
Pabsorbed= S.(1-A).RT2 The power emitted by Earth is given by Pemitted = 4πRT2.σeT4 To be in radiative equilibrium the condition Pabsorbed = Pemitted Question? But the actual average temperature of Earth is 288 kelvin (15ºC) and not 255 kelvin. How is this possible? This can be rearranged to produce Answer: Due to greenhouse effect. T=255 K

This diagram for remote sensing

Radiative Transfer Easier to consider the specific problem of the radiance at a sensor at the top of the atmosphere viewing the surface

There will be three components of greatest interest in the
Radiation components There will be three components of greatest interest in the solar reflective part of the spectrum Unscattered, surface reflected radiation Lλsu Down scattered, surface reflected Lλsd skylight Up scattered path Lλsp radiance Radiance at the sensor is the sum of these three

Much of the previous discussion centered around the
Spectral signature Much of the previous discussion centered around the selection of the specific spectral bands for a given theme The key will be that different materials have different spectral reflectances As an example, consider the spectral reflectance curves of three different materials shown in the graph

Spectral Signature For any given material, the amount of solar radiation that it reflects, absorbs, transmits, or emits varies with wavelength a general example of a reflectance plot for some (unspecified) vegetation type (bio-organic material)

Spectral Signature For example, at some wavelengths, sand reflects more energy than green vegetation but at other wavelengths it absorbs more (reflects less) than does the vegetation. In principle, we can recognize various kinds of surface materials and distinguish them from each other by these differences in reflectance.

Spectral Signature - geologic
Minerals and rocks can have distinctive spectral shapes based on their chemical makeup and water content For example, chemically bound water can cause a similar feature to show up in several diverse sample types However, the specific spectral location of the features and their shape depends on the actual sample 1

Spectral signature - Vegetation
Samples shown here are for a variety of vegetation types All samples are of the leaves only That is, no effects due to the branches and stems is included

Vegetation spectral reflectance
Note that many of the themes for Landsat TM were based on the spectral reflectance of vegetation Show a typical vegetation spectra - KNOW THIS CURVE Also show the spectral bands of TM in the VNIR and SWIR as well as some of the basic physical process in each part of the spectrum

Recall the graph presented earlier showing the transmittance
Spectral signature - Atmosphere Recall the graph presented earlier showing the transmittance of the atmosphere Can see that there are absorption features in the atmosphere that could be used for atmospheric remote sensing Also clues us in to portions of the spectrum to avoid so that the ground is visible

Spectral Signature Spectral signature is the idea that a given material has a spectral reflectance/emissivity which distinguishes it from other materials Spectral reflectance is the efficiency by which a material reflects energy as a function of wavelength Challenges: Unfortunately, the problem is not as simple as it may appear since other factors beside the sensor play a role, such as Solar angle View angle Surface wetness Background and surrounding material Also have to deal with the fact that often the energy measured by the sensor will be from a mixture of many different materials This discussion will focus on the solar reflective for the time being

Have to keep in mind that a spectral signature is not always enough
A signature is not enough Have to keep in mind that a spectral signature is not always enough Signature of a water absorption feature in vegetation may not indicate the desired parameter Vegetation stress and health Vegetation amount Signatures are typically derived in the laboratory Field measurements can verify the laboratory data Laboratory measurements may not simulate what the satellite sensor would see Good example is the difficult nature of measuring the relationship between water content and plant health Once the plant material is removed from the plant to allow measurement it begins to dry out Using field-based measurements only is limited by the quality of the sensors The next question then becomes how many samples are needed to determine what signatures allow for a thematic measurement

Signature and resolution
The next thing to be concerned about is the fact that we will not fully sample the entire spectrum but rather use fewer bands In this case, all four bands will allow us to differentiate clay and grass Using bands 1, 3, and 4 would also be sufficient to do this Even using just bands 3 and 4 would allow us to separate clay and grass

Band selection and resolution for spectral signatures should
Signature and resolution Band selection and resolution for spectral signatures should be chosen first based on the shapes of the spectra That is, it is not recommended to rely on the absolute difference between two reflectance spectra for discrimination Numerous factors can alter the brightness of the sample while not impacting the spectral shape Shadow effects and illumination conditions Absolute calibration Sample purity Bands showngive Gypsum - Low, high, lower Montmorillonite - High, high, low Quartz - high, high, not so high

Spectral Signature is important property of matter makes it possible to identify different substances or classes and to separate them by their individual spectral signatures, as shown in the figure below.

Vegetation: NDVI NDVI - Normalized Difference Vegetation Index Video
Negative values of NDVI (values approaching -1) correspond to water. Values close to zero (-0.1 to 0.1) generally correspond to barren areas of rock, sand, or snow. Lastly, low, positive values represent shrub and grassland (approximately 0.2 to 0.4), while high values indicate temperate and tropical rainforests (values approaching 1).

Vegetation Spectral Signature
where RED and NIR stand for the spectral reflectance measurements acquired in the red and near-infrared regions, respectively. These spectral reflectances are themselves ratios of the reflected over the incoming radiation in each spectral band individually, hence they take on values between 0.0 and 1.0. By design, the NDVI itself thus varies between -1.0 and +1.0. The pigment in plant leaves, chlorophyll, strongly absorbs visible light (from 0.4 to 0.7 µm) for use in photosynthesis. The cell structure of the leaves, on the other hand, strongly reflects near-infrared light (from 0.7 to 1.1 µm). The more leaves a plant has, the more these wavelengths of light are affected, respectively.

Class Participation Calculate NDVI in these two trees.

Spectral signatures, image display, data systems
Remote Sensing Models Lecture 3 Spectral signatures, image display, data systems

Energy radiated by the earth peaks in the TIR Effective temperature of the earth-atmosphere system is 255 K Planck curves below relate to typical terrestrial temperatures

Solar-Terrestrial Comparison
When taking into account the earth-sun distance it can be shown that solar energy dominates in VNIR/SWIR and emitted terrestrial dominates in the TIR Sun emits more energy than the earth at ALL wavelengths It is a geometry effect that allows us to treat the wavelength regions separately

Solar-Terrestrial Comparison
Plots here show the energy from the sun at the sun and at the top of the earth’s atmosphere Also show the emitted energy from the earth

Vertical Profile of the Atmosphere
Understanding the vertical structure of the atmosphere allows one to understand better the effects of the atmosphere Atmosphere is divided into layers based on the change in temperature with height in that layer Troposphere is nearest the surface with temperature decreasing with height Stratosphere is next layer and temperature increases with height Mesosphere has decreasing temperatures

Atmospheric composition
Atmosphere is composed of dust and molecules which vary spatially and in concentration Dust also referred to as aerosols Also applies to liquid water, particulate matter, airplanes, etc. Primary source of aerosols is the earth's surface Size of most aerosols is between 0.2 and 5.0 micrometers Larger aerosols fall out due to gravity Smaller aerosols coagulate with other aerosols to make larger particles Both aerosols and molecules scatter light more efficiently at short wavelengths Molecules scatter very strongly with wavelength (blue sky) Molecular scattering is proportional to 1/(wavelength)4 Aerosols typically scatter with 1/(wavelength) Both aerosols and molecules absorb Molecular (or gaseous absorption is more wavelength dependent Depends on concentration of material

default ozone 60-degree zenith angle and no scattering
Absorption MODTRAN3 output for US Standard Atmosphere, 2.54 cm column water vapor, default ozone 60-degree zenith angle and no scattering

Same curve as previous page but includes molecular scatter
Absorption Same curve as previous page but includes molecular scatter

More material, lower transmittance Longer path, lower transmittance
Angular effect Changing the angle of the path through the atmosphere effectively changes the concentration More material, lower transmittance Longer path, lower transmittance

having complete absorption
At longer wavelengths, absorption plays a stronger role with some spectral regions having complete absorption Three absorption bands, at µm, µm, and µm

Absorption

The MWIR is dominated by water vapor and carbon dioxide absorption

In the TIR there is the “atmospheric window” from 8-12 μm
Absorption In the TIR there is the “atmospheric window” from 8-12 μm with a strong ozone band to consider

Infrared Infrared: 0.7 to 300 µm wavelength. This region is further divided into the following bands: Near Infrared (NIR): 0.7 to 1.5 µm. Short Wavelength Infrared (SWIR): 1.5 to 3 µm. Mid Wavelength Infrared (MWIR): 3 to 8 µm. Long Wanelength Infrared (LWIR): 8 to 15 µm. Far Infrared (FIR): longer than 15 µm.

Visible Light Visible Light: This narrow band of electromagnetic radiation extends from about 400 nm (violet) to about 700 nm (red). The various colour components of the visible spectrum fall roughly within the following wavelength regions: Red: nm Orange: nm Yellow: nm Green: nm Blue: nm Indigo: nm Violet: nm

UV Ultraviolet: 3 to 400 nm