Skip to main content
Log in

Analysis of Irrigated Salt-Affected Soils in the Central Fergana Valley, Uzbekistan, Using Landsat 8 and Sentinel-2 Satellite Images, Laboratory Studies, and Spectral Index-Based Approaches

  • DEGRADATION, REHABILITATION, AND CONSERVATION OF SOILS
  • Published:
Eurasian Soil Science Aims and scope Submit manuscript

Abstract

Soil salinity is a fundamental barrier to soil fertility, particularly in dry climates, and is a limiting factor for agricultural output and subterranean water utilization. Soil salinity significantly restricts agricultural soils in Uzbekistan. Remote sensing and satellite images were used to evaluate soil salinity in the Mingbulak District of Uzbekistan. In October 2019, soil samples were taken from various locations and analyzed, and soil salinity indices were calculated. The region’s soil salinity was then mapped and modeled. The results revealed that SI 12 and the NDSI from Landsat 8 were superior to the others. The accuracy of the single band B2 and that of salinity indices SI1 and SI8 of Landsat 8 and Sentinel-2A were higher in the deeper layers than in the upper. NDSI was used to model the relationship between soil salinity (electrical conductivity) and the prominent salt ion \({\text{SO}}_{4}^{{2 - }}.\) The model was validated successfully, and a soil salinity map was created. According to the findings, the NDSI provided more accurate information on soil salinity than the other salinity indices, and the blue band was successful in depicting sublayers and the overall salinity of the region.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1.
Fig. 2.
Fig. 3.
Fig. 4.
Fig. 5.

Similar content being viewed by others

REFERENCES

  1. A. Allbed, L. Kumar, and Y. Y. Aldakheel, “Assessing soil salinity using soil salinity and vegetation indices derived from IKONOS high-spatial resolution imageries: applications in a date palm dominated region,” Geoderma 230–231, 1–8 (2014). https://doi.org/10.1016/j.geoderma.2014.03.025

    Article  Google Scholar 

  2. A. Allbed and L. Kumar, “Soil salinity mapping and monitoring in arid and semi-arid regions using remote sensing technology: a review,” Adv. Remote Sens. 02, 373–385 (2013). https://doi.org/10.4236/ars.2013.24040

    Article  Google Scholar 

  3. E. Asfaw, K. V. Suryabhagavan, and M. Argaw, “Soil salinity modeling and mapping using remote sensing and GIS: the case of Wonji sugar cane irrigation farm, Ethiopia,” J. Saudi Soc. Agric. Sci. 17, 250–258 (2018). https://doi.org/10.1016/j.jssas.2016.05.003

    Article  Google Scholar 

  4. I. Aslanov, S. Kholdorov, S. Ochilov, A. Jumanov, Z. Jabbarov, I. Jumaniyazov, and N. Namozov, “Evaluation of soil salinity level through using Landsat-8 OLI in Central Fergana valley, Uzbekistan,” E3S Web Conf., (2021). https://doi.org/10.1051/e3sconf/202125803012

  5. A. Bannari, A. M. Guedon, A. El-Harti, F. Z. Cherkaoui, and A. El-Ghmari, “Characterization of slightly and moderately saline and sodic soils in irrigated agricultural land using simulated data of advanced land imaging (EO-1) sensor,” Commun. Soil Sci. Plant Anal. 39, 2795–2811 (2008). https://doi.org/10.1080/00103620802432717

    Article  Google Scholar 

  6. M. Bouaziz, J. Matschullat, and R. Gloaguen, “Improved remote sensing detection of soil salinity from a semi-arid climate in Northeast Brazil,” C. R. Geosci. 343, 795–803 (2011). https://doi.org/10.1016/j.crte.2011.09.003

    Article  Google Scholar 

  7. E. Davis, Master’s Thesis (Univ. of South Carolina, Los Angeles, 2018).

  8. M. A. Delavar, A. Naderi, Y. Ghorbani, A. Mehrpouyan, and A. Bakhshi, “Soil salinity mapping by remote sensing south of Urmia Lake, Iran,” Geoderma Reg. 22, e00317 (2020). https://doi.org/10.1016/j.geodrs.2020.e00317

    Article  Google Scholar 

  9. A. E. K. Douaoui, H. Nicolas, and C. Walter, “Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data,” Geoderma 134, 217–230 (2006). https://doi.org/10.1016/j.geoderma.2005.10.009

    Article  Google Scholar 

  10. FAO, Standard Operating Procedure for Soil Electrical Conductivity, Soil/Water, 1 : 5, (Rome, 2021).

  11. N. Farahmand and V. Sadeghi, “Estimating soil salinity in the dried lake bed of Urmia Lake using optical sentinel-2 images and nonlinear regression models,” J. Indian Soc. Remote Sens. 48, 675–687 (2020). https://doi.org/10.1007/s12524-019-01100-8

    Article  Google Scholar 

  12. T. Gorji, A. Yildirim, N. Hamzehpour, A. Tanik, and E. Sertel, “Soil salinity analysis of Urmia Lake Basin using Landsat-8 OLI and Sentinel-2A based spectral indices and electrical conductivity measurements,” Ecol. Indic. 112, 106173 (2020). https://doi.org/10.1016/j.ecolind.2020.106173

    Article  Google Scholar 

  13. E. Günal, X. Wang, O. M. Kılıc, M. Budak, S. al Obaid, M. J. Ansari, and M. Brestic, “Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: a case study in Dushak, Turkmenistan,” PLoS One 16, (2021). https://doi.org/10.1371/journal.pone.0259695

  14. V. Habibi, H. Ahmadi, M. Jafari, and A. Moeini, “Machine learning and multispectral data-based detection of soil salinity in an arid region, Central Iran,” Environ. Monit. Assess. 192, (2020). https://doi.org/10.1007/s10661-020-08718-z

  15. A. A. Hammam and E. S. Mohamed, “Mapping soil salinity in the East Nile Delta using several methodological approaches of salinity assessment,” Egypt. J. Remote Sens. Space Sci. 23, 125–131 (2020). https://doi.org/10.1016/j.ejrs.2018.11.002

    Article  Google Scholar 

  16. R. Hassan, Z. Ahmed, Md. T. Islam, R. Alam, and Z. Xie, “Soil salinity detection using salinity indices from Landsat 8 satellite image at Rampal, Bangladesh,” Remote Sens. Earth Syst. Sci. 4, 1–12 (2021). https://doi.org/10.1007/s41976-020-00041-y

    Article  Google Scholar 

  17. F. M. Howari, P. C. Goodell, and S. Miyamoto, “Spectral properties of salt crusts formed on saline soils,” J. Environ. Qual. 31, 1453–1461 (2002). https://doi.org/10.2134/jeq2002.1453

    Article  Google Scholar 

  18. M. Ijaz, H. R. Ahmad, S. Bibi, M. A. Ayub, and S. Khalid, “Soil salinity detection and monitoring using Landsat data: a case study from Kot Addu, Pakistan,” Arabian J. Geosci. 13 (2020). https://doi.org/10.1007/s12517-020-05572-8

  19. A. Keshavarzi and F. Sarmadian, “Mapping of spatial distribution of soil salinity and alkalinity in a semi-arid region,” Ann. Warsaw Univ. Life Sci.–SGGW, Land Reclam. 44, (2012). https://doi.org/10.2478/v10060-011-0057-x

  20. F. K. Khadim, H. Su, L. Xu, and J. Tian, “Soil salinity mapping in Everglades National Park using remote sensing techniques and vegetation salt tolerance,” Phys. Chem. Earth 110, 31–50 (2019). https://doi.org/10.1016/j.pce.2019.01.004

    Article  Google Scholar 

  21. N. M. Khan, V. V. Rastoskuev, E. V. Shalina, and Y. Sato, “Mapping salt-affected soils using remote sensing indicators-a simple approach with the use of GIS IDRISI,” in Proceedings of 22nd Asian Conference on Remote Sensing (2001), Vol. 5.

  22. S. Khan and A. Abbas, “Using remote sensing techniques for appraisal of irrigated soil salinity,” in Proceedings of International Congress on Modelling and Simulation (2007).

  23. A. A. Lamqadem, G. M. Afrasinei, and H. Saber, “Analysis of Landsat-derived multitemporal vegetation cover to understand drivers of oasis agroecosystems change,” J. Appl. Remote Sens. 13, 1 (2019). https://doi.org/10.1117/1.jrs.13.014517

    Article  Google Scholar 

  24. D. I. Rukhovich, E. I. Pankova, G. I. Chernousenko, and P. V. Koroleva, “Long-term salinization dynamics in irrigated soils of the Golodnaya Steppe and methods of their assessment on the basis of remote sensing data,” Eurasian Soil Sci. 43, 682–692 (2010). https://doi.org/10.1134/S1064229310060098

    Article  Google Scholar 

  25. G. Sahbeni, “Soil salinity mapping using Landsat 8 OLI data and regression modeling in the Great Hungarian Plain,” SN Appl. Sci. 3 (2021). https://doi.org/10.1007/s42452-021-04587-4

  26. Y. Shirokova, I. Forkutsa, and N. Sharafutdinova, “Use of electrical conductivity instead of soluble salts for soil salinity monitoring in Central Asia,” Irrig. Drain. Syst. 14, 199–205 (2000). https://doi.org/10.1023/A:1026560204665

    Article  Google Scholar 

  27. I. Stavi, N. Thevs, and S. Priori, “Soil salinity and sodicity in drylands: a review of causes, effects, monitoring, and restoration measures,” Front. Environ. Sci. 9 (2021). https://doi.org/10.3389/fenvs.2021.712831

  28. SUHET, Sentinel-2 User Handbook (ESA Standard Document, 2015).

  29. V. Ihlen, Landsat 8 (L8) Data Users Handbook (South Dakota, 2019).

    Google Scholar 

  30. J. Wang, D. Liu, J. Ma, Y. Cheng, and L. Wang, “Development of a large-scale remote sensing ecological index in arid areas and its application in the Aral Sea Basin,” J. Arid Land 13, 40–55 (2021). https://doi.org/10.1007/s40333-021-0052-y

    Article  Google Scholar 

  31. J. Wang, J. Ding, D. Yu, D. Teng, B. He, X. Chen, X. Ge, Z. Zhang, Y. Wang, X. Yang, T. Shi, and F. Su, “Machine learning-based detection of soil salinity in an arid desert region, Northwest China: a comparison between Landsat-8 OLI and Sentinel-2 MSI,” Sci. Total Environ. 707 (2020). https://doi.org/10.1016/j.scitotenv.2019.136092

  32. Z. Wang, F. Zhang, X. Zhang, N. W. Chan, H.-te Kung, M. Ariken, X. Zhou, and Y. Wang, “Regional suitability prediction of soil salinization based on remote-sensing derivatives and optimal spectral index,” Sci. Total Environ. 775, 145807 (2021) https://doi.org/10.1016/j.scitotenv.2021.145807

    Article  Google Scholar 

Download references

ACKNOWLEDGMENTS

The author’s team wishes to thank the USAID Regional Water and Environment Project for technical and financial assistance in the framework of the Young Scientists Competition. Author Lakshmi Gopakumar, Tomoaki Yamaguchi, Megumi Yamashita, and Keisuke Katsura declare they have no financial interests.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to K. Katsura.

Ethics declarations

The authors declare that they have no conflicts of interest.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Kholdorov, S., Lakshmi, G., Jabbarov, Z. et al. Analysis of Irrigated Salt-Affected Soils in the Central Fergana Valley, Uzbekistan, Using Landsat 8 and Sentinel-2 Satellite Images, Laboratory Studies, and Spectral Index-Based Approaches. Eurasian Soil Sc. 56, 1178–1189 (2023). https://doi.org/10.1134/S1064229323600185

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1134/S1064229323600185

Keywords:

Navigation