Using Synthetic Aperture Radar (SAR) Imagery to Look Beneath Dry Soil Surfaces

One of the unique characteristics of Synthetic Aperture Radar (SAR) satellite remote sensing is that at smaller frequencies, the SAR signal can penetrate sand under dry conditions. The electromagnetic (EM) wave penetration in soil depends upon a parameter called the “relative permittivity”, which is actually a “complex” quantity, with real and imaginary parts. The real part is called “dielectric constant” and the imaginary part is called “loss factor.” The study of penetration of EM waves in materials is based on some mathematics and physics, which we will not discuss here (relax!). These theoretical foundations are mostly covered in any undergrad / grad course or relevant book on EM waves.

Anyway, to cut a long story short, scientists define the “penetration depth” of EM wave in any material as (beware, scientific jargon coming up): “the distance at which the power density of the electromagnetic wave drops to 1/e of its value at the immediate sub-surface.” Here, e is the base of the natural logarithm, with a value of 2.72, and therefore 1/e has a value of 0.37. So, in more layman terms, we can think of penetration depth as follows: If the incoming EM wave has a power density of 1 units at the surface, then the depth at which it is reduced to 0.37 units, is the penetration depth.

Under certain approximations, such as uniform material properties with depth, the penetration depth d can be defined mathematically as:

penetrationdeptheqn

This equation is very interesting; a quick analysis shows us the following:

  • Larger wavelength (smaller frequency) means more EM wave penetration
  • EM wave penetration increases as dielectric constant dielectric constant increases
  • EM wave penetration decreases as loss factor increases

So, to penetrate any material, the frequency should be small, the dielectric constant should be large, and the loss factor should be small. As moisture content in an object increases, the loss factor generally increases. Therefore, penetration depth decreases with increase in moisture content: More water molecules cause more EM wave observation at the microwave frequencies. Incidentally, this is the same principle on which the microwave oven works.

Summarizing the above passage in the context of soil surfaces, we can now state: Low-frequency SAR signals can penetrate in dry soil. In the case of very dry and arid regions, e.g. Sahara desert, low-frequency SAR signals can penetrate sand down to a depth of a few meters. In the figure below is a simulation of penetration depth with respect to volumetric moisture content in sand, at L-band frequencies.

lbandsarpenetration_richards2005

Simulation for SAR penetration depth in sand as a function of moisture content, at L-band wavelength of 23.5 cm. Taken from Richards (2009) – Remote Sensing with Imaging Radar.

I hope this blog post serves as a good introduction to the material penetration properties of SAR, which works for not only soil, but also for forests and snow / ice studies, among others.

In my next post, I will describe a research study we have conducted to detect a paleochannel in the Cholistan Desert in Pakistan using both SAR and optical remote sensing data.

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About WQ

I received my PhD (2013) in Remote Sensing, Earth and Space Science at the Dept. of Aerospace Engineering Sciences, University of Colorado, Boulder, USA, under a Fulbright fellowship. Currently, I'm an Assistant Professor in the Dept. of Space Science at Institute of Space Technology (IST), Islamabad, Pakistan, where I have been a founding member of the Geospatial Research & Education Lab (GREL). My general expertise is in Remote Sensing where I have worked with various remote sensing datasets through my career, while for my PhD thesis I specifically worked on Remote Sensing using SAR (Synthetic Aperture Radar) and Oceanography, working extensively on development of techniques to measure ocean surface currents from space-borne SAR intensity images and interferometric data. My research interests are: Remote sensing, Synthetic Aperture Radar (SAR) imagery and interferometric data processing & analysis, Visible/Infrared/High-resolution satellite image processing & analysis, Oceanography, Earth system study and modelling, LIDAR data processing and analysis, Scientific programming. I am a reviewer for IEEE Transactions on Geoscience & Remote Sensing, Forest Ecosystems, GIScience & Remote Sensing, Journal of African Earth Sciences, and Italian Journal of Agronomy. I am an alumnus of Pakistan National Physics Talent Contest (NPTC), an alumnus of the Lindau Nobel Laureate Meetings, a Fulbright alumnus, and the Pakistan National Point of Contact for Space Generation Advisory Council (SGAC). I was an invited speaker at the TEDxIslamabad event held in Nov., 2014. I've served as mentor in the NASA International Space App Challenge Islamabad events in April 2015 and April 2016.

One thought on “Using Synthetic Aperture Radar (SAR) Imagery to Look Beneath Dry Soil Surfaces

  1. Pingback: Looking Back in Time with SAR Satellite Imagery: Tracing the Path of a Dead River | EarthEnable

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