Remote Sensing and Soil Thermal Properties:

1. Remote Sensing and Soil Thermal Properties: Conductivity, Heat Capacity, and Electromagnetics! OH MY! Eric Russell 4/9/2010 Agron 577: Soil Physics

2. 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

3. 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)

4. EM Spectrum

5. Base Electromagnetic equations • Maxwell’s equations • Set of equations that relate the characteristics and propagation of magnetic and electrical fields

6. 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)

7. Temperature and Radiation • Temperature is defined as the average kinetic energy of molecules in a substance • Anything that has a temperature radiates via the Stefan-Boltzmann law: J = εσT4 , where ε = emissivity and σ = 5.67x10-8 [W/m2K4] • Wien’s Displacement law: 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

8. Brightness Temperature • Standard measurement for remote sensing signal • More strictly correct is the spectral irradiance I(l,T) obtained via Plank’s Law: (J·s-1·m-2·sr-1·Hz-1) • But brightness temperature is easier: Tb = εT where Tb = brightness temperature (K), T = temperature of material (K), and ε = emissivity

9. Simplify to Rayleigh-Jean law • Bypass Plank’s law: estimate Tb using the spectral brightness Bl(T) from the Rayleigh-Jean law: where k = Boltzmann constant, c = speed of light, Tb = brightness temperature, and λ= wavelength. • Then back out the brightness temperature

10. Example of data collected

11. 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: • From remote sensing: where DG = variation in surface heat flux, DT = Tmax – Tmin, and ω = 2p/86400s

12. 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

13. 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

14. Figure Blitzkrieg!!!!

15. Left: Nighttime temperature over bare soil Right: Daytime temperature over bare soil Minacapilli and Blanda 2009

16. (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

17. 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)

18. Idso et al 1976

19. Idso et al1976

20. Smits et al 2010

21. 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.

22. Questions? Comments?