Journal of Engineering and Applied Sciences
ISSN: Online 1818-7803ISSN: Print 1816-949x
Abstract
The electrical conductivity is dielectric properties and able to identify normal soil and soil salinity. EC values is the method able to classify soil salinity levels quickly. To determine soil salinity from the field experience is very complicated and difficult. ALOS PALSAR is known as penetrated satellite data. They have been proved as a powerful tool to indicate the accuracy of salinity value in saline conditions. This reserce to study the sufficiency of EC as derived from ALOS PALSAR satellite data to predict EC values associated with soil salinity. A regression model was used to create an EC estimation model. This research developed an estimation model that could explain the EC of saline soil. This research illustrated that a relationship between two different data sources, ALOS PALSAR and ground data, the statistical model could be developed to accurately estimate the value of EC soil using ALOS satellite.
How to cite this article:
Walaiporn Phonphan. Using Regression Models to Predict Electrical Conductivity of
Soil Through ALOS PALSAR Satellite.
DOI: https://doi.org/10.36478/jeasci.2017.7276.7279
URL: https://www.makhillpublications.co/view-article/1816-949x/jeasci.2017.7276.7279