Mapping the salt-affected soils (SAS) through spectral indices derived from satellite imagery is essential for its monitoring at a frequent interval and for the management. Several salinity indices have been developed based on the combination of spectral bands for predicting soil salinity in the arid environment. Present study attempted to identify and map the salt-affected soils (SAS) in inland plains of semi-arid agro-ecological region of Tamil Nadu, India using satellite image (Resourcesat-1(IRS-P6) LISS IV). Vertisols and Inceptisols are the major soil orders cultivated under paddy, sugarcane and pulses. An integrated approach of spectral bands and indices along with analytical data of samples collected from the field was used to develop multiple regression equations for prediction. The best linear regression model was selected based on adjusted R2 and MSE values for the prediction of pH, EC, and ESP. The variation observed between salt-affected soils predicted by multiple regression equations and measured data were 15, 10, and 5 percent for pH, EC, and ESP, respectively, due to weak variation in soil properties, sample density, better vegetation cover by management practices.
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Abbas, A., & Khan, S. (2007) Using remote sensing techniques for appraisal of irrigated soil salinity. In: Oxley L, Kulasiri D (eds) Advances and applications for management and decision making land, water and environmental management: integrated systems for sustainability MODSIM07, pp.2632–2638.
Adcock, D., McNeill, A. M., McDonald, G. K., & Armstrong, R. D. (2007). Subsoil constraints to crop production on neutral and alkaline soils in south-eastern Australia: A review of current knowledge and management strategies. Australian Journal of Experimental Agriculture, 47, 1245–1261.
Allbed, A., Kumar, L., & Sinha, P. (2014). Mapping and modelling spatial variation in soil salinity in the Al Hassa Oasis based on remote sensing indicators and regression techniques. Remote Sensing, 6, 1137–1157.
Bannari, A., Guedon, A. M., El-Harti, A., Cherkaoui, F. Z., & El-Ghmari, A. (2008). Characterization of slightly and moderately saline and sodic soils in irrigated agricultural land using simulated data of advanced land imaging sensor. Communications in Soil Science and Plant Analysis, 39, 19–20.
Berger, K. C., & Truog, E. (1939). Boron determination in soils and plants using the quinalizar in reaction. Industrial and Engineering Chemistry Analytical Edition, 11, 540–545.
Bouman, B. A. M., & Tuong, T. P. (2001). Field water management to save water and increase its productivity in irrigated lowland rice. Agricultural Water Management, 49, 11–30.
Broge, N. H., & Mortensen, J. V. (2002). Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data. Remote Sensing of Environment, 81, 45–57.
Dehni, A., & Lounis, M. (2012). Remote sensing techniques for salt affected soil mapping: Application to the Oran region of Algeria. Procedia Engineering, 33, 188–198.
Douaoui, A. E. K., Nicolas, H., & Walter, C. (2006). Detecting salinity hazards within a semiarid context by means of combining soil and remote-sensing data. Geoderma, 134(1–2), 217–230.
FAO. (2005) Global network on integrated soil management for sustainable use of salt affected soils. Rome, Italy. FAO Land and Plant Nutrition Management Service.
Farifteh, F., Farshad, A., & George, R. G. (2006). Assessing salt-affected soils using remote sensing, solute modelling, and geophysics. Geoderma, 130, 191–206. https://doi.org/10.1016/j.geoderma.2005.02.003.
Gracia, L., Eldeiry, A., & Elhaddad, A. (2005). Estimating soil salinity using remote sensing data. Proceedings of the 2005 Central Plains Irrigation Conference, 11, 223–288.
ICAR-CSSRI. (2015). ICAR-Central Soil Salinity Research Institute Vision 2050. New Delhi: Indian Council of Agricultural Research.
Khan, N. M., Rastoskuev, V. V., Sato, Y., & Shiozawa, S. (2005). Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators. Agricultural Water Management, 77, 96–109.
Minhas, P. S., & Samra, J. S. (2003). Quality assessment of water resources in the Indo-Gangetic Basin part in India. India: Central Soil Salinity Research Institute.
Naidu, R., & Rengasamy, P. (1993). Ion interactions and constraints to plant nutrition in Australian sodic soils. Australian Journal of Soil Research, 31, 801–819.
Piper, C. S. (1966). Soil and plant analysis. Bombay, India: Reprinted by Hans Publishers.
Qadir, M., Noble, A. D., Schubert, S., Thomas, R. J., & Arslan, A. (2006). Sodicity-induced land degradation and its sustainable management: Problems and prospects. Land Degradation and Development, 17, 661–676. https://doi.org/10.1002/ldr.751.
Qadir, M., & Schubert, S. (2002). Degradation processes and nutrient constraints in sodic soils. Land Degradation and Development, 13, 275–294.
Samra, J. S., Singh, G., & Ramakrishna, Y. S. (2006). Drought management strategies in India (p. 277). New Delhi: ICAR.
Saxena, R.K., Sharma, R. C., Verma, K. S., Pal, O. K.,&Mandai, A. K. (2004) Salt Affected Soils, Etah District (Uttar Pradesh). NBSS-CSSRI Publ.No 108, NBSS&LUP, Nagpur, pp–85.
Sehgal, J., & Abrol, I. P. (1994). Soil degradation in India status and impact (p. 80). India: Oxford and IBH.
Soil Survey Staff. (2008) Keys to soil taxonomy. 8th Edison. SCS, USDA, Washigton, DC.
Sumner, M. E., & Miller, W. P. (1996). Cation exchange capacity and exchange coefficients. In D. L. Sparks, A. L. Page, & P. A. Helmke (Eds.), Methods of Soil Analysis Part 3, Chemical Methods (pp. 1201–1229). Madison: Soil Science Society of America.
USDA. (2014) Saline, Saline-Sodic & Sodic Soils. Agro.Tech.Note.76. (http://www.nrcs.usda.gov/wps/portal/nrcs/detail/nm/technical/?cid=nrcs144p2_068965).
Walkley, A., & Black, I. A. (1934). An examination of the Degtjareff method for determining soil organic matter, and a proposed modification of the chromic acid titration method. Soil Sciences, 37, 29–38.
Whitney, D. A. (1998) Soil salinity. In: Brown, J.R. (Ed.), Recommended Chemical Soil Test Procedures for the North Central Region 221. North Central Regional Publication, Missouri Agriculture, pp. 59–60 (revised). (Exp, Stn. Bull. SB1001).
Wilding, L. P. (1985). Spatial Variability: its documentation, accommodation, and implication to soil surveys. In D. R. Nielsen & J. Bouma (Eds.), Soil Spatial Variability. Netherlands: Pudoc, Wageningen.
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Manickam, L., Subramanian, D., Khandal, S. et al. Modeling and Mapping of Salt-Affected Soils through Spectral Indices in Inland Plains of Semi-arid Agro-Ecological Region. J Indian Soc Remote Sens (2021). https://doi.org/10.1007/s12524-021-01321-w
- Salt-affected soils
- Soil properties
- Spectral indices
- Multi-linear regression