Real Time CHIS Model for Efficient Sugarcane Plant Growth and Yield Estimation Model using Satellite Images

Abstract

The research on plant growth estimation of sugarcane plants is a key factor ongoing now days. The problem of plant growth and yield estimation of sugarcane plants is well studied. There are number of solutions recommended by different researchers, still they suffer with poor accuracy. Existing methods measure the plant growth according to the rainfall and temperature which introduces poor performance. To improve the performance, an efficient Climate Hydro Image Soil Model (CHISM) is presented. The model considers various properties namely climate conditions like temperature, humidity and hydrologic features namely rainfall, water poured and soil conditions towards plant growth. The method uses the satellite images in obtaining the soil condition, by applying image processing technique, the soil condition are obtained. Remaining features are obtained through the regional data set provided by agriculture sector. Using all these features, the method estimates various influence measure on different features considered. The method computes rainfall influence measure (RIM), water influence measure (WIM), temperature influence measure (TIM), humidity influence measure (HIM), and soil influence measure (SIM). Using all these measure, the model computes the plant growth rate (PGR) and Yield Rate (YR) in different time window. According to the measures estimated, the model performs water regulation. The method improves the performance of plant growth estimation and crop yield.