Salinity modelling by inverted Gaussian parameters of soil reflectance spectra

Abstract

This paper presents an approach to estimate soil salinity through modelling of soil spectra using an inverted Gaussian (IG) function. The approach is tested on experimental datasets including measurements of soil physicochemical properties and their spectral reflectance which are obtained under controlled laboratory conditions. The near-infrared (NIR) and shortwave infrared (SWIR) region of the salt-affected soil spectra were fitted to an inverted Gaussian curve. Parameters of the fitted curve, such as functional depth, distance to the inflection point and area under curve, were then used as predictors in regression analysis to estimate soil salinity levels. The results suggest a successful estimation of salinity levels, especially, for soil samples treated with epsomite and bischofite solutions. Amongst the calculated IG parameters, the area under fitted curve resulted in the most accurate estimations. The results demonstrate the relative utility of high spectral resolution data for estimating soil salinity under laboratory controlled conditions.

Prediction of Soil Moisture Content and Soil Salt Concentration from Hyperspectral Laboratory and Field Data

“…These ions constitute some typical minerals which have characteristic absorption features. For example, Farifteh, et al [47] We found a high correlation between similar wavebands at 1430, 1870 and 1940 nm. Halite (NaCl) has absorption features located at 1440 and 1933 nm, and Epsomite (MgSO4•7H2O) has absorption features at 793, 999, 1240, 1490, 1631, 1760 and 1946 nm.…”

Salinity stress detection in rice crops using time series MODIS VI data

“…Remote sensing has been used to detect salinity-affected soils (Metternicht and Zinck 2003;Allbed and Kumar 2013). Several studies have devised different salinity indices to identify salt-affected areas (Farifteh, Van der Meer, and Carranza 2007a;Dehni and Lounis 2012;Matinfar et al 2013) and have conducted modelling to map soil salinity using different spectral bands (Farifteh, Tolpekin, and Van der Meer 2010;Wu 2014). Different multi-spectral sensors, such as Landsat Thematic Mapper (TM), Landsat Multi Spectral Scanner (MSS) system, and the Indian Remote Sensing (IRS) satellite have been used to map salt-affected soils using purely spatial analyses (Verma et al 1994;Dwivedi 2001;Elnaggar and Noller 2009).…”