Potential of Landsat 8 OLI for mapping and monitoring of soil salinity in an arid region: A case study in Dushak, Turkmenistan

Abstract

Soil salinity is the most common land degradation agent that impairs soil functions, ecosystem services and negatively affects agricultural production in arid and semi-arid regions of the world. Therefore, reliable methods are needed to estimate spatial distribution of soil salinity for the management, remediation, monitoring and utilization of saline soils. This study investigated the potential of Landsat 8 OLI satellite data and vegetation, soil salinity and moisture indices in estimating surface salinity of 1014.6 ha agricultural land located in Dushak, Turkmenistan. Linear regression model was developed between land measurements and remotely sensed indicators. A systematic regular grid-sampling method was used to collect 50 soil samples from 0–20 cm depth. Sixteen indices were extracted from Landsat-8 OLI satellite images. Simple and multivariate regression models were developed between the measured electrical conductivity values and the remotely sensed indicators. The highest correlation between remote sensing indicators and soil EC values in determining soil salinity was calculated in SAVI index (r = 0.54). The reliability indicated by R2 value (0.29) of regression model developed with the SAVI index was low. Therefore, new model was developed by selecting the indicators that can be included in the multiple regression model from the remote sensing indicators. A significant (r = 0.74) correlation was obtained between the multivariate regression model and soil EC values, and salinity was successfully mapped at a moderate level (R2: 0.55). The classification of the salinity map showed that 21.71% of the field was non-saline, 29.78% slightly saline, 31.40% moderately saline, 15.25% strongly saline and 1.44% very strongly. The results revealed that multivariate regression models with the help of Landsat 8 OLI satellite images and indices obtained from the images can be used for modeling and mapping soil salinity of small-scale lands.

Soil salinity assessment of a natural pasture using remote sensing techniques in central Anatolia, Turkey

“…Spatial resolution of satellite images is an important factor in determining and mapping salinity [ 14 , 20 , 56 ]. Therefore, Ahmed and Andrianasolo [ 57 ] revealed that soil salinity can be mapped in more detailed using SPOT XS images compared to Landsat TM images.…”

“…Therefore, determining and monitoring soil salinity with classical methods (laboratory analysis) is costly and time-consuming. Unlike conventional methods, remote sensing technologies offer significant cost-effective advantages in determining soil salinity for large areas at high accuracy [ 5 , 14 , 16 ].…”

“…Recording the energy reflected from earth surface in different spectral ranges by sensors placed on satellites allows the detection and monitoring of differences on earth surface [ 17 ]. Several studies have been carried out to investigate and map saline areas by remote sensing through examining spectral characteristics of saline soils in visible (VIS) and infrared (IR) wavelengths [ 1 , 14 , 18 , 19 ]. The basic approach in most of the studies was to develop regression models between ground sampling points and remote sensing datasets.…”

“…The basic approach in most of the studies was to develop regression models between ground sampling points and remote sensing datasets. Three different approaches, i.e., i) model development between reflection values of spectral bands in satellite images and measured soil salinity values [ 1 , 20 ], ii) estimating soil salinity directly by calculating salinity indices [ 14 , 19 , 21 ] and iii) estimating soil salinity indirectly by calculating vegetation indices [ 14 , 22 , 23 ] are used to map soil salinity.…”

Assessment of the saline biotope state of the North-Western Pryazovia as breeding sites of Glareola pratincola with the help of remote sensing data

“…The availability of remote sensing data (RS) opens up new opportunities for assessing the state and monitoring of biotopes, including the saline ones. In particular, they are used to map saline biotopes [3,4], vegetation status [5,6], analysis of their spatiotemporal changes [7,8]. The state assessment of the biotopes allows to identify some factors that affect the distribution of birds that inhabit them.…”