Title : Spatial assessment of soil salinity using pca and geospatial techniques; a case study of Punjab Pakistan
Both natural and man-made soil salinity is a major geological disaster in arid and semi-arid landscapes. In agricultural land, it has a negative impact on plant growth and crop yields, while in semi-arid and arid non-agricultural areas, due to subsidence, corrosion and groundwater quality, it affects urban structures, leading to further soil erosion and land degradation. The study was conducted at central Punjab, Pakistan with the aim to develop a baseline and to show the precision and accuracy of GIS technology for delineating soil salinity in no data region. Soil samples were collected from 0-15 and 15-30cm and laboratory analysis was performed for three parameters (pH, EC and SAR). Landsat 8 OLI imagery were used for salinity indices development. A statistical index relationship was established between the soil salinity measured in the field soil samples and the thirteen GIS-based salinity indexes. Based on regression model fitting, influence significance and model parameters were evaluated for different soil salinity indexes. The data were classified into three class i.e. i) Ground dataset ii) Brightness/Intensity Indices and iii) Salinity Indices. Principal component analysis (PCA) were performed on data. Results show that salinity indices have associated positively to the ground data sets, while the brightness/intensity indices have no significant relation with Ground data sets.