Estimating electrical conductivity of soil through ALOS satellite data using regression models

Abstract

The Electrical Conductivity (EC) is the value of dielectric properties in soil normally used for significant indicator identifying normal soil and salt-affected soil. EC is influenced by many factors such as soil moisture, soil porosity, texture, and organic matter. EC estimation is the method able to classify soil salinity levels quickly and sufficiently accurate. To determine and monitor the spatial variations in saline soil from the field experience is very complicated and difficult as it often requires dependable models in applying to the specific arrangement and environmental limitations of the study to learn how it impacts on saline soil. ALOS is known as penetrated satellite data as it can detect character of land surface. They have been proved as a powerful tool to indicate the accuracy of salinity value in saline conditions. The main objective was to study the sufficiency of EC as derived from satellite data to predict EC values associated with soil salinity. A regression model was used to create an EC estimation model. EC values were related to scattering values extracted from ALOS satellite data which this research developed an estimation model that could explain the EC of saline soil. The results illustrated that a relationship between two different data sources, satellite data and ground data, the statistical model could be developed to accurately estimate the value of EC soil using ALOS satellite