Abstract
Soil salinity is one of the most important problems affecting many areas of the world. Saline soils present in agricultural areas reduce the annual yields of most crops. This research deals with the soil salinity mapping of Seyhan plate of Adana district in Turkey from the years 2009 to 2010, using remote sensing technology. In the analysis, multitemporal data acquired from LANDSAT 7-ETM<sup>+</sup> satellite in four different dates (19 April 2009, 12 October 2009, 21 March 2010, 31 October 2010) are used. As a first step, preprocessing of Landsat images is applied. Several salinity indices such as NDSI (Normalized Difference Salinity Index), BI (Brightness Index) and SI (Salinity Index) are used besides some vegetation indices such as NDVI (Normalized Difference Vegetation Index), RVI (Ratio Vegetation Index), SAVI (Soil Adjusted Vegetation Index) and EVI (Enhamced Vegetation Index) for the soil salinity mapping of the study area. The field’s electrical conductivity (EC) measurements done in 2009 and 2010, are used as a ground truth data for the correlation analysis with the original band values and different index image bands values. In the correlation analysis, two regression models, the simple linear regression (SLR) and multiple linear regression (MLR) are considered. According to the highest correlation obtained, the 21st March, 2010 dataset is chosen for production of the soil salinity map in the area. Finally, the efficiency of the remote sensing technology in the soil salinity mapping is outlined.
Highlights
Soil salinity is one of the widespread environmental hazards all around the world, especially in arid and semiarid regions
Soil salinity has been measured by collecting soil samples in the region of interest, and the samples were analyzed in laboratory in order to determine the amount of electric conductivity in the soil but this method was time and cost consuming
The images were georectified to a Universal Transverse Mercator (UTM) coordinate system, using World Geodetic System (WGS) 1984 datum, assigned to north UTM zone 36 and Path 175 Row 34, 35
Summary
Soil salinity is one of the widespread environmental hazards all around the world, especially in arid and semiarid regions. Like salinization, remotely sensed data has great potential; it uses aerial photography, thermal infrared or multispectral data acquired from platforms such as Landsat satellite (Allbed and Kumar, 2013). There are many satellites and sensors, which are useful in detecting and monitoring the saline soil. Multispectral data such as LANDSAT, SPOT, IKONOS, EO1, IRS, and Terra-ASTER with the resolution can be ranged from medium to high as well as hyperspectral sensors. The sensors scan only the soil surface, while the entire soil profile is involved and should be considered This limitation highlights the necessity of using other data and techniques, in combination with remote sensing (Farifteh, 2006). The main objectives of this study are: (i) to understand the spectral reflectance characteristics of saline soil in Seyhan plate, (ii) to explore the potential of Landsat imagery to detect and map the soil salinity over the study area, (iii) to analyse the correlation between field measurements and Landsat imagery, and (iv) to produce the soil salinity map according to high, moderate and low saline content
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
