volume | PIER Journals

Abstract

Studies of soil moisture with Global Navigation Satellite System (GNSS) have gained the attention of several researchers. Multipath amplitude, multipath phase, and multipath frequency are multipath observables that are utilized in the study of soil moisture. However, an inter-comparison of the performance of these parameters for soil moisture under different roughness and vegetation conditions is very much required to have a better insight so that more robust inversion algorithm for soil moisture retrieval with multipath observables can be designed. Therefore, this paper analyses the performance of these multipath observables for soil moisture over bare smooth soil, rough surface, and vegetated soil. Two different fields have been investigated to include the location variability. Navigation with Indian constellation (NavIC) multipath signal has been used in this study. Statistical parameters such as correlation coefficient (R), Root Mean Square Error (RMSE), and sensitivity have been determined to study the performance of multipath observable for soil moisture under different surface roughness and vegetation conditions.

1. Zavorotny, V. U., K. M. Larson, J. J. Braun, E. E. Small, E. D. Gutmann, and A. L. Bilich, "A physical model for GPS multipath caused by land reflections: Toward bare soil moisture retrievals," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., Vol. 3, 100-110, 2010, doi: 10.1109/JSTARS.2009.2033608.
doi:10.1109/JSTARS.2009.2033608 Google Scholar

2. Chew, C. C., E. E. Small, K. M. Larson, and V. U. Zavorotny, "Vegetation sensing using GPS-interferometric reflectometry: Theoretical effects of canopy parameters on signal-to-noise ratio data," Vegetation sensing using GPS-interferometric reflectometry: Theoretical effects of canopy parameters on signal-to-noise ratio da, Vol. 53, 2755-2764, 2015, doi: 10.1109/TGRS.2014.2364513. Google Scholar

3. Zhang, S., N. Roussel, K. Boniface, M. C. Ha, F. Frappart, J. Darrozes, F. Baup, and J. C. Calvet, "Use of reflected GNSS SNR data to retrieve either soil moisture or vegetation height from a wheat crop," Hydrol. Earth Syst. Sci., Vol. 21, 4767-4784, 2017, doi: 10.5194/hess-21-4767-2017.
doi:10.5194/hess-21-4767-2017 Google Scholar

4. Roussel, N., F. Frappart, G. Ramillien, J. Darrozes, F. Baup, L. Lestarquit, and M. C. Ha, "Detection of soil moisture variations using GPS and GLONASS SNR data for elevation angles ranging from 2^◦ to 70^◦," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., Vol. 9, 4781-4794, 2016, doi: 10.1109/JSTARS.2016.2537847.
doi:10.1109/JSTARS.2016.2537847 Google Scholar

5. Link, M., C. Montzka, T. Jagdhuber, S. S. Søjærg, S. Dill, M. Peichl, T. Meyer, and F. Jonard, "Impact of permittivity patterns on fully polarimetric brightness temperature signatures at L-band," Progress In Electromagnetics Research, Vol. 166, 75-93, 2019.
doi:10.2528/PIER19080204 Google Scholar

6. Small, E. E., K. M. Larson, C. C. Chew, J. Dong, and T. E. Ochsner, "Validation of GPS-IR soil moisture retrievals: Comparison of different algorithms to remove vegetation effects," IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens., Vol. 9, 4759-4770, 2016, doi: 10.1109/JSTARS.2015.2504527.
doi:10.1109/JSTARS.2015.2504527 Google Scholar

7. Chew, C., E. E. Small, and K. M. Larson, "An algorithm for soil moisture estimation using GPS-interferometric reflectometry for bare and vegetated soil," GPS Solut., Vol. 20, 525-537, 2016, doi: 10.1007/s10291-015-0462-4.
doi:10.1007/s10291-015-0462-4 Google Scholar

8. Shekhar, S., R. Prakash, D. K. Pandey, A. Vidyarthi, S. Tyagi, D. Putrevu, and A. Misra, "Sensitivity of multipath peak frequency of Navigation with Indian Constellation (NavIC) towards surface soil moisture over bare land," Int. Geosci. Remote Sens. Symp., 7000-7003, 2021, doi: 10.1109/IGARSS47720.2021.9554474. Google Scholar

9. Lv, J., R. Zhang, J. Tu, M. Liao, J. Pang, B. Yu, K. Li, W. Xiang, Y. Fu, and G. Liu, "A GNSS-IR method for retrieving soil moisture content from integrated multi-satellite data that accounts for the impact of vegetation moisture content," Remote Sens, Vol. 13, 2021, doi: 10.3390/rs13132442. Google Scholar

10. Zhang, S., T.Wang, L.Wang, J. Zhang, J. Peng, and Q. Liu, "Evaluation of GNSS-IR for retrieving soil moisture and vegetation growth characteristics in wheat farmland," J. Surv. Eng., Vol. 147, 1-14, 2021, doi: 10.1061/(asce)su.1943-5428.0000355. Google Scholar

11. Yang, T., W. Wan, X. Chen, T. Chu, and Y. Hong, "Using BDS SNR observations to measure near-surface soil moisture fluctuations: Results from low vegetated surface," IEEE Geosci. Remote Sens. Lett., Vol. 14, 1308-1312, 2017, doi: 10.1109/LGRS.2017.2710083.
doi:10.1109/LGRS.2017.2710083 Google Scholar

12. Rodriguez-Alvarez, N., A. Camps, M. Vall-Llossera, X. Bosch-Lluis, A. Monerris, I. Ramos-Perez, E. Valencia, J. Martinez-Fernandez, and G. Baroncini-Turric, "Land geophysical parameters retrieval using the interference pattern GNSS-R technique," IEEE Trans. Geosci. Remote Sens., Vol. 49, 71-84, 2011, doi: 10.1109/TGRS.2010.2049023.
doi:10.1109/TGRS.2010.2049023 Google Scholar

13. Chamoli, V., R. Prakash, A. Vidyarthi, and A. Ray, "Capability of NavIC, an Indian GNSS constellation, for retrieval of surface soil moisture," Progress In Electromagnetics Research C, Vol. 106, 255-270, 2020.
doi:10.2528/PIERC20090904 Google Scholar

14. Shekhar, S., R. Prakash, A. Vidyarthi, and D. K. Pandey, "Sensitivity analysis of Navigation with Indian Constellation (NavIC) derived multipath phase towards surface soil moisture over agricultural land," 2020 6th Int. Conf. Signal Process. Commun. ICSC 2020, 138-142, 2020, doi: 10.1109/ICSC48311.2020.9182714. Google Scholar

15. Zhang, Y., L. Jing, Y. Zhao, H. Ruan, L. Yang, and B. Sun, "GNSS-IR soil moisture inversion method based on random forest," China Satellite Navigation Conference (CSNC), 133-144, 2021.
doi:10.1007/978-981-16-3138-2_14 Google Scholar

16. Zhang, S., J. C. Calvet, J. Darrozes, N. Roussel, F. Frappart, and G. Bouhours, "Deriving surface soil moisture from reflected GNSS signal observations from a grassland site in southwestern france," Hydrol. Earth Syst. Sci., Vol. 22, 1931-1946, 2018, doi: 10.5194/hess-22-1931-2018.
doi:10.5194/hess-22-1931-2018 Google Scholar

17. Wan, W., K. M. Larson, E. E. Small, C. C. Chew, and J. J. Braun, "Using geodetic GPS receivers to measure vegetation water content," GPS Solut., Vol. 19, 237-248, 2015, doi: 10.1007/s10291-014-0383-7.
doi:10.1007/s10291-014-0383-7 Google Scholar

18. Shekhar, S., R. Prakash, D. K. Pandey, A. Vidyarthi, S. Tyagi, D. Putrevu, and A. Misra, "Development of soil moisture inversion model for bare soil using Navigation with Indian Constellation (NavIC)," IEEE Geosci. Remote Sens. Lett., Vol. 19, 1-5, 2022, doi: 10.1109/LGRS.2021.3090568.
doi:10.1109/LGRS.2021.3090568 Google Scholar

19. Han, M., Y. Zhu, D. Yang, X. Hong, and S. Song, "A semi-empirical SNR model for soil moisture retrieval using GNSS SNR data," Remote Sens., Vol. 10, 1-19, 2018, doi: 10.3390/rs10020280. Google Scholar

20. Entekhabi, D., R. H. Reichle, R. D. Koster, and W. T. Crow, "Performance metrics for soil moisture retrievals and application requirements," J. Hydrometeorol., Vol. 11, 832-840, 2010, doi: 10.1175/2010JHM1223.1.
doi:10.1175/2010JHM1223.1 Google Scholar

Mr. Sushant Shekhar

Dr. Rishi Prakash

Mr. Dharmendra Kumar Pandey

Dr. Anurag Vidyarthi

Dr. Deepak Putrevu

Dr. Nilesh M. Desai