Journal of Radio Electronics. eISSN 1684-1719. 2025. ¹5
Full text in Russian (pdf)
DOI: https://doi.org/10.30898/1684-1719.2025.5.7
MEASUREMENT OF AGROSOILS MOISTURE UNDER BARLEY,
WHEAT AND OATS CROPS BY ELECTROMAGNETIC IMPULSES
FROM AN UNMANNED AERIAL VEHICLE
Kirensky Institute of Physics SB RAS
660036, Russia, Krasnoyarsk, Akademgorodok 50, bld. 38
The paper was received November 5, 2024.
Abstract. During long-term experiments, the feasibility of remote sensing the moisture content of agrosoils under barley, oats, and wheat using electromagnetic pulses from an unmanned aerial vehicle (UAV), both during natural moistening and drying of crops, was demonstrated. The test fields were situated within the territory of the Minino Experimental Farm (located near Minino village, Krasnoyarsk Krai). Sensing impulses were synthesized based on spectral measurements (using a Caban R60 vector network analyzer) of the reflection coefficient at the input terminals of the log-periodic transmitting and receiving antenna. Soil moisture was determined by solving the inverse problem of minimizing the norm of the discrepancy between the modules of the reflection coefficient, calculated using the Fresnel formula (for a dielectrically homogeneous half-space) and the average values of those measured in the MHz frequency range at various hovering heights of the UAV above the test fields. The advantages and disadvantages of the proposed method, as well as the prospects for the development of technology for remote sensing of soil moisture using multi-rotor UAVs are discussed.
Key words: UAV, radiolocation, ultra-wideband impulses, soil moisture.
Financing: Results were obtained within the regional competitions of the Russian Science Foundation and the Krasnoyarsk Regional Science Foundation No. 22-17-20042.
Corresponding author: Muzalevskiy Konstantin Victorovich, email: rsdkm@ksc.krasn.ru
References
1. Khang A. et al. Handbook of Research on AI-Equipped IoT Applications in High-Tech Agriculture. Hershey, PA: IGI Global.– 2023.– 473 p.
2. Zaman Q. et al. Precision Agriculture Evolution, Insights and Emerging Trends. Academic press. Elsevier.– 2023.– 260 p.
3. Cognitive Technologies. Available online: URL: https://cognitivepilot.com/breaking-news/vopros-otvet-o-rabote-novogo-avtopilota-na-traktorah-kirovecz-k-7m/ (accessed on 01.07.2024).
4. Bertalan L., Holb I., Pataki A. et al. UAV-based multispectral and thermal cameras to predict soil water content–A machine learning approach// Computers and Electronics in Agriculture.– 2022.– V. 200.– p. 107262.
5. Guan Y., Grote K. Assessing the Potential of UAV-Based Multispectral and Thermal Data to Estimate Soil Water Content Using Geophysical Methods// Remote Sens.– 2024.–V. 16.– No. 61.– p. 1-23.
6. Lu F., Sun Y., Hou F. Using UAV Visible Images to Estimate the Soil Moisture of Steppe// Water.– 2020.–V. 12.– p. 2334.
7. ten Harkel J., Bartholomeus H., Kooistra L. Biomass and Crop Height Estimation of Different Crops Using UAV-Based Lidar// Remote Sens.– 2020. V. 12. No. 17. – p. 1-18.
8. Bates J.S., Montzka, C., Schmidt M., Jonard F. Estimating Canopy Density Parameters Time-Series for Winter Wheat Using UAS Mounted LiDAR// Remote Sens.– 2021.– V. 13. –No. 4.– p. 1-21.
9. Huisman J.A., Hubbard S.S., Redman J.D., Annan A.P. Measuring soil water content with ground penetrating radar: A review// Vadose zone journal.– 2003.– V. 2.–No. 4.–p. 476-491.
10. Tran A.P., Bogaert P., Wiaux F. et al. High-resolution space–time quantification of soil moisture along a hillslope using joint analysis of ground penetrating radar and frequency domain reflectometry data// Journal of Hydrology.– 2015.–V. 523.– p. 252-261.
11. Dehem M. Soil moisture mapping using a drone-borne Ground Penetrating Radar. Faculté des bioingénieurs, Université catholique de Louvain. Thesis of master degree.– 2020. 67 p.
12. Di Mauro A., Scozzari A., Soldovieri F. et al. Instrumentation and Measurement Technologies for Water Cycle Management// Springer Water.– 2022.– 599 p. (pp. 417-436).
13. Wu K., Desesquelles H., Cockenpot R. Ground-Penetrating Radar Full-Wave Inversion for Soil Moisture Mapping in Trench-Hill Potato Fields for Precise Irrigation// Remote Sens.– 2022.– V. 14.– No. 23.– p. 1-16.
14. Cheng Q., Su Q., Binley A. Estimation of surface soil moisture by a multi-elevation UAV-based ground penetrating radar// Water Resources Research.– 2023.– V. 59.–No. e2022WR032621.–p. 1-21.
15. Karpukhin V.I., Peshkov A.N. Measurement of height and biomass of vegetation canopy by radar method// Proceedings of theory and technology of radar, radio navigation and radio communications in civil aviation. The Riga Institute of Civil Aviation Engineers.– 1985.– p. 69-73.
16. Serbin G., Or D. Near‐surface soil water content measurements using horn antenna radar: Methodology and overview// Vadose Zone Journal.– 2003.–V. 2.–No. 4.– p. 500-510.
17. Serbin G., Or D. Ground-penetrating radar measurement of crop and surface water content dynamics// Remote Sensing of Environment.– 2005.– V. 96.– No. 1. P. 119-134.
18. Serbin G., Dani O.R. Frequency-domain analyses of GPR waveforms: Enhancing near-surface observational capabilities// In proceedings of symposium S7 held during the Seventh IAHS Scientific Assembly at Foz do Iguaçu, Brazil, IAHS Publ.– 2006.– V. 303.–p. 274-285. Available online: https://iahs.info/uploads/dms/13440.36-274-285-S7-29-serbin.pdf
19. Ardekani M. R., et al. A Layered Vegetation Model for GPR Full-Wave Inversion// IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.– 2016.–V. 9.– No. 1.– p. 18-28.
20. Ardekani M. R., et al. GPR data inversion for vegetation layer// Proceedings of the 15th International Conference on Ground Penetrating Radar, Brussels.– 2014.– p. 170-175.
21. Pramudita A.A., Wahyu Y., Rizal S. et al. Soil water content estimation with the presence of vegetation using ultra wideband radar-drone// IEEE Access.– 2022.–V. 10.–p. 85213-85227.
22. Topp G.C., Davis J. L., Annan A. P. Electromagnetic determination of soil water content: Measurements in coaxial transmission lines// Water Resour. Res.– 1980.– V. 16.–No. 3.– p. 574–582.
23. Jonard F., Weihermuller L., Jadoon K.Z. et al. Mapping field-scale soil moisture with L-band radiometer and ground-penetrating radar over bare soil// IEEE Transactions on Geoscience and Remote Sensing.– 2011.– V. 49.– No. 8.–p. 2863-2875.
24. Kim K.Y. et al. Precision Soil Moisture Monitoring With Passive Microwave L-Band UAS Mapping// IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.–2024.–V. 17.– p. 7684-7694.
25. Dai E., Gasiewski A. J., Venkitasubramony A. et al. High Spatial Resolution Soil Moisture Mapping Using a Lobe Differencing Correlation Radiometer on a Small Unmanned Aerial System// IEEE Transactions on Geoscience and Remote Sensing.– 2021, 59, 5, 4062-4079. https://doi.org/10.1109/TGRS.2020.3005385.
26. Gleich D. SAR UAV for soil moisture estimation// 8th Asia-Pacific Conference on Synthetic Aperture Radar (APSAR), Bali, Indonesia.– 2023.– pp. 1-4.
27. Farhad M., Gurbuz A.C., Kurum M. et al. Soil Moisture Mapper: a GNSS-R approach for soil moisture retrieval on UAV// AI for Agriculture and Food Systems.– 2022.– p. 1-4.
28. Wu K., Rodriguez G.A., Zajc M. et al. A new drone-borne GPR for soil moisture mapping// Remote Sensing of Environment.– 2019.– V. 235.– No. 111456.
29. Muzalevskiy K. LPDA Calibration Using an UAV for Synthesizing UWB Impulses// IEEE Antennas and Wireless Propagation Letters.– 2023.– V. 22.–No. 9.– p. 2140-2144.
30. Muzalevskiy K., Mikhaylov M., Ruzicka Z. Synthesizing of UltraWide Band Impulse by means of a Log-Periodic Dipole Antenna. Case Study for a Radar Stand Experiment// IEEE International Multi Conference on Engineering, Computer and Information Sciences (SIBIRCON), Yekaterinburg, Russian Federation.– 2022.– p. 1140-1143.
31. Muzalevsky K.V. Synthesis of an Ultra-Wideband Pulse by a Log-Periodic Antenna with Continuous Excitation by Harmonic Oscillations// Radiophysics and Quantum Electronics.– 2023.–V. 65.– No. 8.– p. 615-623.
32. Ìóçàëåâñêèé Ê.Â., Ôîìèí Ñ.Â., Êàðàâàéñêèé À.Þ., è äð. Çîíäèðîâàíèå âëàæíîñòè ïî÷âû ñâåðõøèðîêîïîëîñíûìè ýëåêòðîìàãíèòíûìè èìïóëüñàìè ñ áîðòà áåñïèëîòíîãî ëåòàòåëüíîãî àïïàðàòà// Æóðíàë ðàäèîòåõíèêè è ýëåêòðîíèêè.–2024. –¹7 (ïðèíÿòà ê ïå÷àòè).
33. Muzalevskiy K., Fomin S., Karavayskiy A., Leskova J., Lipshin A., Romanov V. Measuring Biophysical Parameters of Wheat Canopy with MHz- and GHz-Frequency Range Impulses Employing Contactless GPR// Remote Sens.– 2024.– Ò. 16.–¹ 19.– ñ. 3547.
34. Mironov L., Bobrov P.P., Fomin S.V. Dielectric model of moist soils with varying clay content in the 0.04 to 26.5 GHz frequency range. International Siberian Conference on Control and Communications (SIBCON).– 2013. p. 1-4.
35. Yuan W, Li J, Bhatta M, Shi Y, Baenziger PS, Ge Y. Wheat Height Estimation Using LiDAR in Comparison to Ultrasonic Sensor and UAS// Sensors (Basel).– 2018– V. 18.– No. 3731. p. 1-20.
36. Bobrov P. P., Kroshka E. S., Muzalevskiy K. V. The Effect of Dielectric Relaxation Processes on the Complex Dielectric Permittivity of Soils at Frequencies From 10 kHz to 8 GHz–Part II: Broadband Analysis// IEEE Transactions on Geoscience and Remote Sensing.– 2024.– V. 62.– No. 2000411.–p. 1-11.
37. Bobrov P. P., Belyaeva T. A., Kroshka E. S., Rodionova O. V. The Effect of Dielectric Relaxation Processes on the Complex Dielectric Permittivity of Soils at Frequencies From 10 kHz to 8 GHz–Part I: Experimental// IEEE Transactions on Geoscience and Remote Sensing.–2022.–V. 60.– no. 2005409.– p. 1-9.
For citation:
Muzalevskiy K.V. Measurement of agrosoils moisture under barley, wheat and oats crops by electromagnetic impulses from an unmanned aerial vehicle. // Journal of Radio Electronics. – 2025 – ¹.5. https://doi.org/10.30898/1684-1719.2025.5.7 (In Russian)