Soil salinity is one of the main agricultural problems which expand to larger areas. Soil scientists categorize salinity level by electrical conductivity (EC) measurement. However, field measurements of EC require extensive time, cost and experiences. Remote sensing is one suitable option to investigate and collect spatial data in larger areas. Many researches estimated soil moisture through microwave, but there are fewer studies which mentioned about direct relationship between EC and backscattering coefficient (BC). Thus, this study aims to propose the estimation of EC directly from BC of microwave. The relationship between EC obtained from field survey and BC from microwave is non-linear, artificial neural network (ANN) is one technique proposed in this study to figure out EC and BC relationship. ANN uses multilayer of interconnected processing resulting in EC value with high accuracy which is acceptable. For this reason, ANN model can be successfully utilized as an effective tool for EC estimation from microwave.
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
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