INTRODUCTION hectares of reproductive rice, and 7.52 hectares of ripening rice.
The images of airborne line scanner can be used for interpretation and classification in some rice plant growth stages. Every rice plant growth stage has
its own characteristics, in general like fallow, green in vegetative phase, and yellow in generativeripening phase. The color in every rice plant growth stage
will give information, which can be used for age prediction of plant. With Remote Sensing method and Geographic Information System, area of rice plant growth
stage on agricultural land can be classified and calculated. The remote sensing methods can automatically recognize the spectral classes that represent rice plant
growth stage. In other disciplines, ANFIS has been a good classifier for medical image classification Monireh et al., 2012.
ANFIS is the implementation of fuzzy inference system to adaptive networks for developing fuzzy rules with suitable membership functions to have
required inputs and outputs. Using a given data set, the ANFIS method constructs a fuzzy inference system whose membership function parameters are tuned
adjusted using gradient descent algorithm and least squares estimation method. Since this method was introduced in 1993 Jang, 1993, ANFIS has been
used in various studies. For image processing, ANFIS is widely used in biomedical research and the limited use for Remote Sensing applications. More
research is needed to determine the ability of ANFIS methods in remote sensing applications. This study has applied ANFIS and integrated with remote sensing
techniques. Remote sensing data can be from the airborne line scanner that captures the agricultural land. Agricultural land has been classified into several
rice plant growth stages to provide more valuable information.