EFFICACY OF THE RICE CROP GROWTH USING DIFFERENT SMOOTHING METHODS

Abstract

Rice is one of India’s most important food crops. The government of India has a major duty in agriculture: perfect mapping and continual monitoring of paddy rice fields. Rice growth has a major impact on SCATSAT-1 backscatter images, and rice fields have been successfully mapped using a time-series analysis employing satellite data. SCATSAT-1 time-series data was used to detect single-cropped, double-cropped, and triple-cropped rice fields (1 to 3 harvests per year) and identify different phonological stages using a crop phenology-based categorization. The usefulness of rice crop growth utilizing exponential smoothing approaches to estimate and forecast yield growth is demonstrated in this paper. The Holt linear trend, Holt-Winters methods (additive and multiplicative), and Mean Absolute Error (MAE), Sum Squared Error (SSE), Mean Squared Error (MSE), Mean Percentile Error (MPE), and Mean Absolute Percentage Error (MAPE) are used as error factors to choose the best forecasting methods among the exponential smoothing techniques.