Cultivated Paddy Area Identification and Rice Yield Estimation Using Free Satellite Images

Abstract

An effective pre-harvest rice yield estimation method is very important for assessment of seasonal rice production for strategic planning purposes. In Sri Lanka, a conventional method is used to estimate seasonal rice production and it fails to forecast rice yield before harvest because the experiment is conducted during the harvest. This study was focused to identify cultivated paddy lands and forecast rice yield using free satellite data. 8-day composite images (250m spatial resolution) from Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard the NASA EOS Terra satellite were used from 2007 to 2014. In this study, a new method has been suggested to identify cultivated paddy lands by analyzing temporal dynamics of the paddy cultivation. Then linear and exponential yield forecasting models were built at different times of the season based on NDVI and EVI2 vegetation indices. Accuracy assessment results show that the suggested cultivated paddy lands identification method has ability to identify cultivated paddy lands with 74% average accuracy. According to the comparison between estimated yield and national statistical data, both NDVI and EVI2 based models give more reliable estimations about 96 days after beginning time of the season. But, EVI2 based model (derived at 96 days) give more reliable estimations than NDVI based model with 92% average accuracy. Therefore seasonal rice yield can successfully be forecast before one month to harvest time using EVI2 based model. Improvement of this study will help to forecast national level yield estimations in the country by illuminating problems faced with current system.