Forecasting rice production in Luzon using integrated spatio-temporal forecasting framework

Rice is a staple in every Filipino home where it is eaten three times a day or sometimes more. Luzon is the top producer of rice for the past years among the other two island groups. Rice plays a critical role in food security. This is one of the importance of rice forecasting. This study explores the possibility of using spatial data and temporal data on forecasting the production of rice at the same time. A Spatio-temporal Forecasting model is used to forecast the quarterly harvest of each of the seven rice producing regions of Luzon. This enables the gathered data to be utilized and manipulated for rice production forecasting. The effect of spatial correlations on the prediction accuracy of spatial forecasting is explored. The study showed that Spatio-temporal forecasting model is better than the most commonly used ARIMA forecasting.Rice is a staple in every Filipino home where it is eaten three times a day or sometimes more. Luzon is the top producer of rice for the past years among the other two island groups. Rice plays a critical role in food security. This is one of the importance of rice forecasting. This study explores the possibility of using spatial data and temporal data on forecasting the production of rice at the same time. A Spatio-temporal Forecasting model is used to forecast the quarterly harvest of each of the seven rice producing regions of Luzon. This enables the gathered data to be utilized and manipulated for rice production forecasting. The effect of spatial correlations on the prediction accuracy of spatial forecasting is explored. The study showed that Spatio-temporal forecasting model is better than the most commonly used ARIMA forecasting.