Rice yield estimation using Landsat ETM plus Data

Paddy rice areas in Larkana district in Sindh province, Pakistan, were mapped over eight years. Landsat 7 ETM+ satellite imagery was classified for rice areas using training data collected through visual interpretation and using a bagged decision tree approach. Within the rice areas, we estimated yield for the 2013 season using regression models based on Landsat-derived normalized difference vegetation index (NDVI) and ratio vegetation index (RVI) values against historic, reported yield values. The annual cropped rice area estimated from satellite imagery was between 19% and 24% lower than the area reported by the Crop Reporting Service, Sindh. A positive and strong relationship with coefficient of determination (R-2) of 0.94 was observed between the reported rice crop yield and NDVI at the peak of the growing season for the years 2006 to 2013. A fair relation (R2 = 0.875) between rice crop yield and RVI was observed for the same years. A strong relationship between observed and predicted rice production with model efficiency = 0.925, mean bias error = -85; 016 t, and RMSE = 80; 726 t was obtained. Thus, Landsat ETM+ has a high potential for estimating rice yield and production at the district level in Pakistan and elsewhere. (C) 2015 Society of Photo-Optical Instrumentation Engineers (SPIE)