Transcript Remote Sensing and Soil Thermal Properties:

Remote Sensing and Soil Thermal
Properties:
Conductivity, Heat Capacity, and
Electromagnetics! OH MY!
Eric Russell
4/9/2010
Agron 577: Soil Physics
Outline
• What is remote sensing?
– Microwave remote sensing
• Very basic electromagnetics
– Blackbody radiation, Wien’s law, Stefan-Boltzmann
law, brightness temperature
• Soil thermal properties
• Combining the previous two (the OH MY! part)
• Figures
What is remote sensing?
• Taking measurements from a place when not
being in physical contact of that place.
• Satellites, MRI’s, IR thermometers, RADAR,
LiDAR, camera
– For this presentation: microwaves
• Utilizes the electromagnetic spectrum (EM)
EM Spectrum
Base Electromagnetic equations
• Maxwell’s equations
– Set of equations that relate the characteristics and
propagation of magnetic and electrical fields
Blackbodies
• Theoretical concept
– Perfect absorber and emitter
• Objects can exhibit blackbody-like
characteristics at certain temperatures
– Preferentially emits at specific
wavelength/frequency
• Can use as an approximation (usually pretty
good)
Temperature and Radiation
• Temperature is defined as the average kinetic energy of
molecules in a substance
• Anything that has a temperature radiates via the StefanBoltzmann law:
J = εσT4 , where ε = emissivity and σ = 5.67x10-8 [W/m2K4]
• Wien’s Displacement law:
lmax
b

T
l = wavelength, b = 2.8977685(51)×10−3 m·K
• a (absorbtivity) + r (reflectivity) + t (transmissivity) = 1
• Kirchoff’s Law: at thermal equilibrium, emissivity (ε) = a
• Higher the temperature, greater the radiation emitted
Brightness Temperature
• Standard measurement for remote sensing
signal
• More strictly correct is the spectral irradiance
I(l,T) obtained via Plank’s Law:
1
hl
3
2hl  kT 
I l , T   2  e  1 (J·s-1·m-2·sr-1·Hz-1)
c 

• But brightness temperature is easier:
Tb = εT
where Tb = brightness temperature (K), T =
temperature of material (K), and ε = emissivity
Simplify to Rayleigh-Jean law
• Bypass Plank’s law: estimate Tb using the
spectral brightness Bl(T) from the RayleighJean law:
Bl T  
2ckT b
l
4
where k = Boltzmann constant,
c = speed of light, Tb = brightness
temperature, and λ= wavelength.
• Then back out the brightness temperature
Example of data collected
Soil Thermal Properties
• Thermal conductivity k: Heat transfer through a
unit area of soil (J/s m K, or W/m K)
• Heat capacity crb: Change in unit volume’s heat
content per unit change in temperature (J/m3 K)
• Soil Thermal Inertia: P  k sat csat rb
2DG
• From remote sensing: P 
DT 
where DG = variation in surface heat flux,
DT = Tmax – Tmin, and ω = 2p/86400s
Thermal Inertia and Soil Moisture
• As discussed, thermal properties depend upon
many factors
– Focus on soil moisture (because it’s awesome…
and where my research lies)
• Can create relationships between θ and
thermal inertia (can’t separate the individual
properties through remote sensing)
• We are now done with big scary equations
and models
Even more on this…
• Can’t separate conductivity from capacity from just
remote sensing
– Properties depend on too many variables
– Can estimate thermal inertia P using model shown
– Can estimate parameters in thermal inertia if know soil
type/texture/moisture content, etc.
• Due to variable needs in approximation, need more
than one measurement
– Can model heat flux through energy balance
– Diurnal temperature changes are easy to get
Left: Nighttime temperature over bare soil
Right: Daytime temperature over bare soil
Minacapilli and Blanda 2009
(a) Ground heat flux G ≡ Q(0, t) (W m−2), and (b) surface (skin)
temperature Ts ≡ T(0, t) (°C) measured at the Lucky Hill site in the
Walnut Gulch Watershed, 5–16 June 2008.
Wang et al 2010
Left: Soil thermal inertia P as a function of θ
Right: Normalized soil thermal inertia Kp as a function of
degree of saturation (normalized q)
Lu et al. (2009)
Idso et al 1976
Idso et al1976
Smits et al 2010
References
•
Bachmann, J., R. Horton, T. Ren, and R R Van Der Ploeg. "Comparison of the Thermal Properties of
Four Wettable and Four Water-repellent Soils." Soil Sci. Soc. Am. J. 65 (2001): 1675-679.
•
Campbell, Gaylon S., and John M. Norman. Introduction to Environmental Biophysics. 2nd ed. New
York: Springer, 1998.
•
Hillel, Daniel. Introduction to Environmental Soil Physics. Amsterdam: Elsevier Academic, 2004.
•
Idso, Sherwood B., Ray D. Jackson, and Robert J. Reginato. "Compensating for Environmental
Variability in the Thermal Inertia Approach to Remote Sensing of Soil Moisture." Journal of
Applied Meteorology 15 (1976): 811-17.
•
Lu, Sen, Zhaoqiang Ju, Tusheng Ren, and Robert Horton. "A General Approach to Estimate Soil
Water Content from Thermal Inertia." Agricultural and Forest Meteorology 149 (2009): 1693-698.
•
Lu, Xinrui, Tusheng Ren, and Yuanshi Gong. "Experimental Inverstigation of Thermal Dispersion in
Saturated Soils with One-Dimensional Water Flow." Soil Sci. Soc. Am. J. 73 (2009): 1912-920.
•
Minacapilli, M., M. Iovino, and F. Blanda. "High Resolution Remote Estimation of Soil Surface
Water Content by a Thermal Inertia Approach." Journal of Hydrology 379 (2009): 229-38.
•
Smits, Kathleen M., Toshihiro Sakaki, Anuchit Limsuwat, and Tissa H. Illangasekare. "Thermal
Conductivity of Sands under Varying Moisture and Porosity in Drainage-Wetting Cycles." Vadose
Zone J. 9 (2010): 1-9.
•
Wang, J., R. L. Bras, G. Sivandran, and R. G. Knox. "A Simple Method for the Estimation of Thermal
Inertia." Geophysical Research Letters 37 (2010): L05404.
Questions? Comments?