Abstract

Soil moisture is one indicator or parameter of field quality. Soil moisture represents the soil water content which is essentially needed by vegetation to grow. Vegetation will experience with stress when the soil moisture is not adequate to grow the plant well. Therefore the soil moisture can be measured indirectly by determining the vegetation index by using remote sensing data. The methods applied in this study to calculate the vegetation index are soil adjusted vegetation index (SAVI) and normalized difference moisture index (NOMI). The results showed that most areas (more than 80%) in Jember have high SAVI and NOMI values which represent high soil moisture and it is good for the plants to grow. This study also measured the soil moisture from 20 soil samples in different locations along Jember regency. It is found the relationship functions of soil moisture and SAVI by the linear function of y = 0,0182 x - 0,3731 with the linearity of 94.4%, while the linear function of soil moisture and NOMI is y = 0,0151 x - 0,3817 with linearity 94.6%. This study resulted a mathematical model to determine soil moisture value based on the SAVI or NOMI values from satellite data. The error of this model is only about 5%, means this model can be considered as accurate model to determine soil moisture from SAVI an NOMI.

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