Ground Penetrating Radar - Science topic

Thank you all for your very useful answers. Video on the Jordanian shore of the Dead Sea . Najib Abou Karaki

Agreeding with Doug, use seismic methods to evaluate soil stiffness or strength. MASW, or crosshole/downhole tests (if boreholes available).

Please keep in mind that you will not be able to derive seismic velocities from GPR measurements. If you are however interested in imaging the structure of the soil and topmost layers, then GPR will offer you highest imaging resolution.

Dear;

Kindly check:

Ground penetrating radar 2004 2 ed

Regards

GPR's is the best available option....

try to use an aerogravity survey and separate the Bouguer gravity map at very shallow depth. or apply the downward continuation at successive shallow levels

You can try gprMax (www.gprMax .com) which is a Free Open Source FDTD solver used to model GPR by many researchers for many years. There is no GUI to build models though if this is what you need.

Hi Filippo, I am not aware of any GPR pulse speed slower than 33 cm/ns. The table that you show does not list a speed of "0.030" m/ns, but "0.03" m/ns. So, I think we are dealing with the effect of rounding inaccuracy rather than an actually observed velocity of 30 cm/ns. I would like to recommend Jürg Leckbusch's site on GPR antenna and material parameters: http://gpr-parameters.ch/material_properties.php

I believe that the only ways to improve the penetration of EM waves through high-saline soils are:

(i) use lower frequencies

(ii) increase the transmitted power

(iii) both of the above.

Regards,

Ray

I think manual set up using TerraSirch mode is always better for the cavity search.

Depending on how many observations and variables for each one you have, you can train a model to predict the "risk degree" of different cases or possible scenarios.

I have studied a bit about artificial intelligence, but actually I have not applied it to real data, nevertheless, despite my short expertise in that field, I think that it is highly possible to estimate the "risk degree" for sinkholes if your data is robust enough.

Best regards,

Samples can conventiently be held in a 2D array of samples within each FM sweep (rows) vs samples from successive sweeps (columns). You will first want to focus the array by making phase offsets on samples as a function of their range and location within the synthetic array. Then a 2D FFT process of data will yield the cross-range vs range map. The FFT of the slow-time samples from successive sweeps gives the Doppler shift of a point which is a function of its cross-range location. The FFT of the fast-time samples within any given sweep gives the beat frequency which is a function of its range. This will get you a basic image/map.

Dear Konstantinos, please, try this article by Kovin and Anderson, available at RG website.

Basically, the idea is use the same principles such as 3D seismic interpretation: it means: time-slices, horizon-slices, and attributes, e.g., coherency, curvature, spectral decomposition, to identified the fractures.

Please, let me know, I can send to you an example from seismic interpretation.

Mario

See chapter 9 in the book "Hydrology of Disasters" By Vijay Singh.

Also see this book chapter:

Formulations gave in both.

When you import the data into ReflexW (that is when you convert it to the internally used format), use a Geometry file (e.g. "Geometry.1") in which you have described the geometry of the survey (see page 211 in the ReflexW manual for the format of the geometry file: https://www.sandmeier-geo.de/Download/reflexw_manual_a4.pdf ). In the import menu select "geometry file" under "ConversionMode". Then process the 2D profiles. Once you are happy with a representative profile, save the applied processing sequence as batch job and apply it through "Sequence Processing" to all profiles. Then exit the 2D mode and enter the 3D module. Here you have to specify for the X- and Y-Rasterincrement the crossline and inline sample spacing, so 2.5m and whatever your inline trace spacing was. The X- and YInterpolation are the horizontal dimensions of the generated and interpolated 3D volume. When ReflexW complains about too many data values, then increase the X- and YInterpolation values. It is not meaningful to interpolate to 10cm cell size when your profile spacing was 250cm. Maybe try 50cm and 10cm. for crossline and inline spacing?

I'm glad to attend, I will get in touch with you.

The answer depends on the depth of target. As you know very well depth penetration of GPR method is very limited. Besides, deriving the fractures within rocks based on GPS is very hard. Therefore, classification of rock type beneath a site have to be done using other geophysical methods.

Please see

How large is the distance of the motion and its time duration?

Thank you for bringing this up! Regarding the statement "Users must be of a class of professionals as designated on the labelling on the GPR instrument", which professionals qualify as GPR users and how is "professionals" defined in this context (someone who earns a living by using GPR, someone with a certain degree, education, training)?

Peter

The general issue that you pose for the GPR technology is generalizable for other ones in geophysics. (see for example the use and applications of seismic tomography)

It Is the general issue of "the mature technologies" and we should to satisfied with the fact that GPR technology became a mature technology.

A mature technology is characterized by:

-consolidated basic theoretical standards

-relatively low instrumental costs

-relatively low logistic/operational costs

-relatively low software costs

-methodological simplicity (low processing time with not high analyst level request)

-high demand for this technology in different application fields

As a consequence, a mature technology has a high diffusion inside applied science operators and professionals and it opens opportunities for different stakeholders (mainly economic-professional) as you claimed in the blog. It is good.

I agree with you that we must spend more effort to diffuse and improve in all forums (educational, professional and societal-economic) the best standards and the best practices of the technology. But Its not matter to defend a mature technology in regards the "absolute quality" because, in this case, it is regulated only by the "natural selection" mainly operated by "the final users of results" (in scientific and professional frameworks). It is so, even though this could appear "raw". Differently should be a matter to discuss the technological-scientific future of a mature technology, in Research&Development, (as it is GPR), because in this case, the effort to be made is far greater than that of an unripe technology. In my opinion, when a technology goes forward, in a sustainable way, it also improves the feedback on its applications.

Thanks very much Dr. Omid Ahmadi for sharing important informations

Regards!

Estimating soil moisture from single SAR images is nearly impossible due to the following reasons:

1. As you said, SAR backscatter not only depends from moisture (dielectricity) but also from roughness and orientation of a surface. You would have to mask out vegetated areas at first, because c-band SAR (ERS, ENVISAT, Seneinel-1) doesn't penetrate vegetation and you could not say if the signal reaches the ground.

2. Second, variations in backscatter intensity in a single image doesn't give you information on temporal variation. Only when you use multi-temporal images (at best ranging over both the dry and rainy season) you get an idea on what is normal seasonal variation and which patterns within that are caused by short-term variations of soil moisture. And this, again, only works on homogenous areas. So including a land-cover classification helps to see which patterns can be related and which can not. I tried to demonstrate that in my last publication (please see the attached image).

3. Lastly, what you basically would need is field data. Measurements on soil-moisture can help to find a relation between SAR backscatter intensity and real moisture content. It is strongly dependent on the soil characteristics, climate and other factors (imaging geometry, spatial resolution) so no approach is comparable or transferable into other regions. Most of the studies published use their own measurements to find regression curves which approximate the soil moisture based on values in the SAR image. But just taking their models and apply it to your data would result in serious errors.

As you are mentioning ground-penetrating radar in your tags: If you have the chance to measure that in the field, at best when you know Sentinel-1 is passing that area (can be retrieved in the acquisition plan), you would have at least field information which can be attached to the SAR image.

There are missions which operationally estimate soil mousture (SMOS, for example). But they operate at spatial resolutions of kilometers, for a very good reason. It is just not feasible with higher resolution data. Some studies try to up-sample the SMOS data by images of higher resolutions but I doubt that is reliable.

Just retrieving soil moisture (like calculating the NDVI from optical images) won't work. So you will have to come up with your own ideas which fit to your data, region and desired application.

@Paiboon Yoiyod I am doing the same but problem is time axis, I am not getting proper results on required time, second for unknown distance how to know the time delay.

Every GPR system contains one or multiple antennas. These antennas transmit and receive radio frequency waves. 

GPR has the same basic principles as a metal detector. A metal detector sends energy into the earth in up to 17 frequencies. When that energy meets a metallic object, it is translated into a recognizable tone. The GPR sends out millions of frequencies that return to the antenna and translate material composition definition in the subsurface. Radar is sensitive to changes in material composition. 

Radar GPR Systems are designed to display differences in material composition. They can be used to locate any object that has a different composition than it's surrounding materials. For example, water, a PVC pipe will have a different composition than the surrounding soil. Voids and excavations that have been filled in will also have different compositions than the surrounding soil.

The depth of your findings will be determined by three factors:

Soil type

Antenna frequency

Size of Target

you my take alook on the attached article. I hope it will help

Dear Dr. Igo,

Yes, GPR can. There are many publications regarding detection of subsurface discontinuities and stratification using GPR, however, as answered by the colleagues here, it is a matter of using the most suitable antenna that satisfies your target (resolution and penetration depth). You may have a look to this paper, for example:

Dear Gamil and dear all, please note that there more to GPR than the monostatic configuration you all appear to have in mind. So, to begin with the original question is improperly posed and could be recast as follows:

1) "Can we distinguish in the geometry of the target buried when scanning by MONOSTATIC GPR?". The answer is that any type of horizontal or subhorizontal interface can be resolved to the detail affordable by combination of host material, depth and size of the target on one hand, and the antenna frequency on the other. Right combinations allow for arbitrarilly good resolution. Conversely, vertical and subvertical interfaces cannot be resolved because they do not reflect the signal.

2) "Can we distinguish in the geometry of the target buried when scanning by BISTATIC GPR, say one used a densely spaced Common MidPoint mode?" If the combination of material, depth, size and antenna allows, the answer is generally yes we can, because in this case we receive returns from vertical and subvertical interfaces as well. 

3) "Can we distinguish in the geometry of the target buried when scanning in tomographic mode using antenna arrays?". If the target is smaller than the array and the combination of material, depth and antennae allows, the answer is a definite yes.  

A few forward modelling and migration exercises, preferably with FDTD and 2-D migration techniques can easily demonstrate these points.

Wish you all the best

I came across a paper describing a method of determining diameters for deformed bars using Surface Penetrating Radar. Link attached

There are many small CW (and even some pulsed) Doppler sensing radar modules commercially available ranging in price from a few $ up to a few hundred $ (e.g. see those of RFBeam GmbH). Most of these operate at 24GHz and output about a few milliWatts of RF power and would therefore not be suitable for through the wall imaging.  For through-the-wall imaging you need (i) low frequencies (so as to get the penetration through building materials) and wide signal bandwidth (so as to achieve a fine level of resolution). These two requirements tend to run contrary to each other and so it is immediately obvious that a budget system is unlikely. The earlier response from Prasanna Waichal suggests 2.4GHz, which would be a good start but in truth you need a bandwidth of say 1GHz to 4GHz, giving 5cm range resolution. I can advise further, if needed. Google my company and email me at the address you find there.

Good luck, Clive

Dewow in Reflex acts on each trace in the profile in turn. For each point on each trace, it calculates the mean value of all the points either side of that point within the time range specified; and subtracts this mean value from the original point. It does this as a running average through all the points in the trace, moving the time window with the point, It does this on each trace independantly.

I don't use this function very often as there are more efficient methods. All depends what you are trying to achieve. In my experience the fewer processing steps you can get away with, the better. Each processing step adds its own artifacts to the mix and you need to be aware of this.  

Hi;

Below are some references I would like to share. Please check GPR radargrams included in the references, especially interpreted radargrams. I think they could give some ideas that will help in your work, Sir.

In addition to the basic data processing steps such as background removal, I would like to suggest you to apply de-convolution and migration to reduce your data. It seems to me both data processing steps would make your data more interpretable.

I hope the references given below could be helpful

Kind Regards

REFERENCES

 

Xu, X., Xia, T., Venkatachalam, A., 2012. Development of high-speed ultrawideband ground-penetrating radar for rebar detection. J. Eng. Mech. 139, 272–285. doi:http://dx.doi.org/10.1061/(ASCE)EM.1943-7889.0000458

Yehia, S., Abudayyeh, O., Abdel-Qader, I., Zalt, A., 2008. Ground-Penetrating Radar, Chain Drag, and Ground Truth: Correlation of Bridge Deck Assessment Data. Transp. Res. Rec. J. Transp. Res. Board 2044, 39–50. doi:10.3141/2044-05

URL 1 https://fhwaapps.fhwa.dot.gov/ndep/DisplayTechnology.aspx?tech_id=24

URL 2 http://www.ijser.org/paper/Thickness-evaluation-of-asphalt-and-base-layers-of-some-major-and-minor-arterial-roads-in-Kumasi-using-ground-penetrating-radar.html

URL 3 http://foundationperformance.org/pastpresentations/gehrig_paper_march2004.pdf

URL 4 http://ntl.bts.gov/lib/43000/43000/43073/134431_FR.pdf

URL 5 http://www.sciencedirect.com/science/article/pii/S0963869504001021

URL 6 http://www.mdpi.com/1424-8220/9/3/1454/htm

I want it @Farad Gholamian

Thank you.

Dear Ebrahim,  We did a study to capture landfill leachate plumes via surface resistivity. I am sending you its outcome for your information. Hope this will help you. Good luck.

http://www.tandfonline.com/doi/full/10.1080/09593330.2014.963697 

Thanks for sharing very good conducive comments and documents

Look at the software Reflex developed by Sandmeier (and his website), you will find all the answers over there.

Chris

If you want a quick low tech solution you could use a rod probe (commercially available or make your own) which you can push through soft soil until you hit rock. Alternatively, if the clays is too stiff or too deep you could use a small diameter hand auger or a dynamic cone penetrometer. Both typically come with extentions.

You might look at our use of UAV-based thermal imaging described in the following article: 

Hi Pranjal,

Sometimes Energy Decay Gain can be too aggressive and over gain any skew or low frequency  noise variations between traces. Try using a gain function to see if this provides any improvement. Use a negative exponent to avoid overgaining the noise at the bottom of the range. Change the other parameters by trial and error until you get a suitable gain distribution. Use the example trace on the gain window as a guide. Also, try leaving out the Subtract-Mean (Dewow) prior to the gain function as any small artifacts it may introduces will be amplified. This should not affect the result provided any dc-shift is constant across all traces. Note that the bandpass filter applied after the gain function will remove any dc-shift any way. Move the background filter to the last processing step. As this is a 2-D filter, it is applied between traces. Any processing step that applies to individual trace like a bandpass filter may affect the result of the background removal. 

With regards to high amplitude bands in your data it may be an artifact introduced in your processing flow or may be due to the signal ringing from your equipment. Difficult to say without seeing your data.

Regards,

Val

I would add to Christoph's answers (which are great by the way):

- better automated target recognition software

 

In order to get suitable results for identifying the depth of water table, For me the ERT technique is good,with short distance between the electrode and choose the optimum electrode array, but for more detail about this you can use the VES. the integration of both technique gives many information for the target of interest. Many scientific papers available that use ERT and VES at the same time.    

I would be very surprise if there is a relationship between dielectric constant and pavement strength. Moisture and density and compositional changes in the unbound material have a larger affect on dielectric than any related strength variation in the material itself. Dielectric can be used to map variations in pavement materials and possibly by inference information regarding its condition. Particularly when considered in context with thickness variation and other signal anomalies.  Variations in dielectric can be determine using wave a ratio analysis, provided that sufficient reflection amplitude can be achieved from the material layers in question. Some relavent papers attached.

Ground Penetrating Radar Surveys to Characterize Pavement Layer Thickness Variations at GPS Sites  Kenneth R.Mase 1994

Road evaluation with ground penetrating radar

T Saarenketo, T Scullion - Journal of applied geophysics, 2000

What filtering you require will depend of the system used to collect the data. Often some filtering is already done during data collection and little filtering is required. Most common filter to use is a 2D background removal filter which removes the temporally static noise bands. In the case of 32bit systems, virtually no filtering is done to the during data collection. In this case you often need to apply a gain function (such as an energy decay function) to restore amplitude before you proceed further.

If you need a generic GPR processing software I would highly recommend Reflexw by Sandmeir Software. Very versatile and reasonably priced.

Ground Penetrating Radar can work well on macadam. Higher frequencies tend to get a lot of clutter because of the rocky fill material. Also, as the subgrade material often becomes intermixed with the base of the material the bottom of the macadam can be difficult to detect. In this case a lower frequencies antenna tends to be more effective at detecting the base at the expense of the definition/resolution. A 900MHz centre frequency antennat will probably work best but experiment with other frequencies as every pavement is different. If you are only interested in depth try using cross polar antenna orientation as this will reduce clutter and accentuate layers. Unfortunately to get accurate results you will need to do regular test pits or auger holes to determine signal velocity and hence depth determination. Signal velocity varies significantly with variation in moisture content.

Most GPR data formats simply store the binary floating point values one after the other, trace after trace. Hence if you know the number of samples per trace and desired trace number you can calculate the offset. Some formats also have a header that is easy to find when looking at the binary data. If it is a Mala dataset the header is in a separate file anyway. If there is a Segy output you'll find the documentation of the format in the internet.

Regards, Juerg Leckebusch

Is 2mm required for range resolution or azimuth resolution?

Kindly take a look at the following link for a summary of SAR and its parameters:

I would recommend Ground Penetrating Radar (if surface and soil conditions permit) or electromagnetic imaging. An slower alternative would be electrical resistance tomography. The choice of methods depends on the site that you would like to investigate, on the desired depth of investigation, on the resolution and the physical conrtast between the infiltrating medium. What type of infiltration are you interested in?

Hi

You may be interested by Mr Balayssac's or Mr Desrobert's research works  (https://www.researchgate.net/profile/J_Balayssac/publications and https://www.researchgate.net/profile/Xavier_Derobert/publications), or who are French specialists of GPR for RC structures.

Good luck

Bonjour,

les valeurs disponibles sont en effet généralement limitées à 1 GHz car sur les sondes co-axiales communément utilisées cela correspond généralement à la fréquence de coupure à partir de laquelle on n'a plus de mode TEM mais des modes complexes pour lesquels les modèles ne sont plus valables. Vous pourriez toutefois contacter Xavier Dérobert à l'IFSTTAR de Nantes car ils ont développé des sondes  qui permettent de travailler jusqu'à au moins 5 GHz de mémoire. Ensuite il faut quand même reconnaître qu'avec les antennes GSSI à 1.5 GHz dans l'air, dans le béton on est plus près du GHz. Donc ces résultats suffisent. Ensuite la dispersion électromagnétique si tant est qu'elle existe est faible à ces fréquences là.

Bonne journée et bien cordialement

i work in GHz frequency and i study back scattered and ground penetrated wave. Since circular/elliptical polarization associates many waves, so i hope soil model related to wireless underground sensor may work for me...

 

Unless you're in a child's sandbox with clean sand, nearly all soils have anisotropy, texture, etc.  If they contain clay minerals, then clay water interactions are important below 300 MHz.  If they contain water, then temperature and salinity are important.  If They contain iron mineralogy, then complex magnetic permeability is important. Is there any tilt (dip) to the soil stratigraphy?

No. There may be geological structural effects as low as the kHz and ice dielectric relaxation effects from 10 kHz down (depending upon temperature). Rough volume and surface scattering may masquerade as loss effects at almost any frequency. For general EM propagation, magnetic relaxation may also come into play if iron bearing minerals are present, so the total EM loss tangent (both dielectric and magnetic) must be considered. See: http://mars.mines.edu for some relevant links, publications and discussion.

There is no one place, nor simple explanation. The target contrast, thickness of the contrast transition, target shape and orientation, EM wave polarization, smoothness of the target surface and embedding material (or roughness) all come into play, not just EM wavelength versus target size and resolution....these are covered as individual papers in the literature or chapters in books, but nowhere in one place. Further, these factors interact, so the scattering from a sharp boundary such as a water table in coarse sand versus a more diffuse and rough boundary in a fine sand interacts with

the angle of the antenna if the surface of the earth is not parallel to the water table. These effects are also changed by signal processing choices (which may be built into the GPR hardware, giving the user no choice).

Thank you very mach for your intervention. I already had GPR data from an USA researcher .

If it is possible, I would like to know if you work on the GPR data. If so, I have a small question in the field of Clutter reduction from the Bscan data signals. This task is easy to do with simple method or not?.

Thank you again.

A very powerful and well maintained FDTD package is meep from MIT (http://ab-initio.mit.edu/wiki/index.php/Meep). It can handle chi^(2), chi^(3) and probably higher-order optical nonlinearities and even has a short tutorial on this (http://ab-initio.mit.edu/wiki/index.php/Meep_Tutorial/Third_harmonic_generation).

However, the "user interface" means scripting in scheme which takes some getting used to.