Editorial Feature

The Use of Raman Spectroscopy in Remote Landmine Detection Technology

Despite huge efforts to restrict the use of landmines and improvised explosive devices (IEDs), landmines still claim nearly 10,000 lives each year.1 The majority of those killed are civilians and for the 50% of people who survive the initial landmine explosion, the majority suffer from extensive and life-changing injuries.2

minefield, raman spectroscopy

Image Credit: Steve Allen/Shutterstock.com

Alongside the risk of injury and death to those who find them, landmines can have seriously detrimental effects on land use. In Libya, it is estimated that 27% of arable land is covered by minefields, preventing its use. In both Zimbabwe and Ethiopia, significant stretches of arable and pastureland remain abandoned due to the lurking threat of minefields in the areas.

Advances in landmine technologies have made it possible to better disguise the detonators, including the use of plastics to evade detection. Autonomous vehicles and remote delivery methods mean that huge numbers of landmines can now be dispersed over greater areas, creating an even larger and unpredictable threat.

Detecting Landmines

There are several different approaches to landmine detection. The most manual of these is ‘mine cleaners’ that search terrain likely to contain minefields and prod regions in the soil to look for unexploded devices. The safety risks associated with this are significant, and this is incredibly inefficient and lengthy work.

Other approaches make use of unmanned aerial vehicles to use photography and image recognition to find evidence of detonators and devices. These technologies are still in their infancy, and the complex terrain of many potential minefields can pose a challenge for the movement of ground robots.           

Another family of approaches relies on chemical sensing. Animals, such as dogs, can be trained to recognize the smell of certain explosive compounds and to alert others to the presence of a possible device. A more exotic approach is to use transgenic plants that will change color in the presence of explosive chemical material. Fast-growing species that turn red in the presence of chemical species related to tri-nitrotoluene (TNT), still one of the most commonly used explosives, can be seeded over large areas to test for the presence of any explosive devices.3

Where possible, soils can be removed for offline chemical techniques with highly sensitive methods such as liquid-chromatography mass spectrometry which are suitable for even trace chemical analysis. However, the use of such techniques is again time-consuming and requires extensive site sampling which is not always suitable for suspected minefields.

Raman Spectroscopy and the Detection of Landmines

While there are many efforts to develop more advanced autonomous vehicles that can be used for both device location and detonation, Raman spectroscopy has become one of the most widely adopted chemical sensing techniques.

Raman spectroscopy recovers both qualitative and quantitative chemical information and is well-suited for the detection of explosive compounds such as TNT. This is because every molecule has several vibrational modes proportional to the number of atoms and many of these will have associated peaks in the Raman spectra that give rise to characteristic patterns considered the ‘fingerprint’ of the molecules.4

A variant of Raman spectroscopy, surface-enhanced Raman spectroscopy (SERS), which is sensitive to species deposited on surface layers, has been of particular interest for landmine detection.5

SERS is well-suited to detection of either TNT itself or other nitrotoluene derivatives that are likely indicators of the presence of explosives.

While SERS and other variants of Raman spectroscopy had shown promise in laboratory tests on soil samples and explosive compounds deposited on metal films, recent work showing that Raman spectroscopy could be used to detect even buried devices from remote distances shows the promise of non-destructive field measurements.4

An advantage of Raman spectroscopy is that its ability to detect explosive residues and their decomposition products in waters and soils means that, depending on how far the explosive traces have leeched into the environment, sampling does not need to be performed in the direct vicinity of the explosive device.

The selectivity of Raman spectroscopy helps to reduce the risk of false alarms, a critical criterion for explosives screening. Raman signals could be observed for both wet and dry soil types, though the signals were weakest from the driest soils.

The team is now hoping that this technology can be implemented for field measurements alongside complementary techniques such as LIDAR. Raman instruments are already sufficiently compact to be mounted on aerial vehicles.

There are still challenges for field-ready Raman measurements, including accounting for issues with signal backgrounds arising from local temperature hotspots, unwanted fluorescence, and potentially poor signal-to-noise. Environmental contaminants with overlapping Raman signals may also pose a challenge for the identification of explosives.

References and Further Reading

  1. Landmine and Cluster Monitor 2019 (2019) Statistics, http://the-monitor.org/en-gb/reports/2019/landmine-monitor-2019/casualties.aspx, accessed October 2021

  2. ICRC (2021) The Human Cost of Landmines, https://www.icrc.org/en/doc/resources/documents/misc/57jmcy.htm., accessed October 2021

  3. Deyholos, M., Faust, A. A., Miao, M., Montoya, R., & Donahue, D. A. (2006). Feasibility of landmine detection using transgenic plants. Detection and Remediation Technologies for Mines and Minelike Targets XI, 6217(May 2006), 62172B. https://doi.org/10.1117/12.668290

  4. Karnik, S., & Prabhu, R. (2021). Chemical detection of explosives in soil for locating buried landmine. In H. Bouma, R. Prabhu, R. J. Stokes, & Y. Yitzhaky (Eds.), Counterterrorism, Crime Fighting, Forensics, and Surveillance Technologies V (Vol. 11869, pp. 29–34). SPIE. https://doi.org/10.1117/12.2601741

  5. Spencer, K. M., Sylvia, J. M., Janni, J. A., & Klein, J. D. (1999). Advances in land mine detection using surface-enhanced Raman spectroscopy. Detection and Remediation Technologies for Mines and Minelike Targets IV, 3710(August 1999), 373. https://doi.org/10.1117/12.357060

Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.

Rebecca Ingle, Ph.D

Written by

Rebecca Ingle, Ph.D

Dr. Rebecca Ingle is a researcher in the field of ultrafast spectroscopy, where she specializes in using X-ray and optical spectroscopies to track precisely what happens during light-triggered chemical reactions.


Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Ingle, Rebecca. (2021, October 19). The Use of Raman Spectroscopy in Remote Landmine Detection Technology. AZoOptics. Retrieved on May 23, 2024 from https://www.azooptics.com/Article.aspx?ArticleID=2022.

  • MLA

    Ingle, Rebecca. "The Use of Raman Spectroscopy in Remote Landmine Detection Technology". AZoOptics. 23 May 2024. <https://www.azooptics.com/Article.aspx?ArticleID=2022>.

  • Chicago

    Ingle, Rebecca. "The Use of Raman Spectroscopy in Remote Landmine Detection Technology". AZoOptics. https://www.azooptics.com/Article.aspx?ArticleID=2022. (accessed May 23, 2024).

  • Harvard

    Ingle, Rebecca. 2021. The Use of Raman Spectroscopy in Remote Landmine Detection Technology. AZoOptics, viewed 23 May 2024, https://www.azooptics.com/Article.aspx?ArticleID=2022.

Tell Us What You Think

Do you have a review, update or anything you would like to add to this article?

Leave your feedback
Your comment type

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.