Using NDVI algorithm in Sentinel-2A imagery for rice productivity estimation (Case study: Compreng sub-district, Subang Regency, West Java)

Abstract

Abstract Rice is the major staple food for nearly half of Indonesia’s population and has a considerable contribution to the global agricultural economy. As a rice granary with the highest rice productivity in Subang Regency, Compreng Sub-district plays an important role in food security. In 2017 Compreng Sub-district had 5,263 ha of rice harvested area with the productivity of 5.7 tons/ha. Therefore, it is urgently necessary to update information about the area and distribution of rice fields to estimate its productivity accurately. This study aims to explain the correlation between the Normalised Difference Vegetation Index (NDVI) values and rice productivity and then to estimate the rice productivity in Compreng Sub-district, Subang Regency in 2017. The methods used were Sentinel-2A imagery with NDVI equation. The results indicated that a Linear R Correlation best described the correlation between the NDVI value and rice productivity and an R2 value of 0.88 was obtained. The estimated calculation of Compreng Sub-district productivity in 2017 is an average of 5.65 ton/ha and the results of data accuracy using Root Mean Square Error between rice productivity estimation with the data from Department of Agriculture in Compreng Sub-district is 0.63.