Evaluating Within-field Rice Growth Variability Using Quickbird and Ikonos Images

Measuring within-field variability is essential for precision farming, and remote sensing is an important tool to obtain the needed information. The objective of this study was to evaluate rice (Oryza sativa L., irrigated lowland rice) growth variability in Qixing farm considering different fields, management practice and cultivars using high resolution optical satellite image data. Based on the spectral dataset of 2007 and 2008, vegetation indices were calculated to quantify the rice growth variability. The vegetation indices were statistically evaluated and were joined with the spatial field data. The results of the spatial analyses show that growth variability was influenced by field conditions (Coefficient of Variation from 1.3 % to 19.8 %) and the farmer's management, mainly dominated by cultivar differences.