Age Estimation of Paddy using Sentinel-2 Imagery: A Case Study in Java Island, Indonesia

Abstract

Plant age plays a crucial role in determining rice yield. The study on the prediction model of spatially specific rice plant age was still less reported, especially that based on high spatial resolution multispectral data. This study investigates the use of Geographic Weighted Regression (GWR) and extracted vegetation indexes (VI) from the Sentinel-2 multispectral image to build the prediction model based on the time-series dataset from the paddy field observation station. The GWR result was also compared to the Linear Regression (LR) model to demonstrate the impact of including spatial attribute into the prediction model. Since the majority of paddy field observation stations are situated on Java Island, it served as the research location for this investigation. The results indicate that VI from the Sentinel-2 image shows a significant correlation with the age of the paddy, then the VI was able to use as a predictor to build the paddy age prediction model. In the statistical evaluation of the model, the coefficient of determination values (R2) reached 0.65, and the RMSE of estimate value was 15 days.

Keywords

• gwr
• java island
• paddy age
• sentinel-2
• vegetation index