Estimating harvest yield using sentinel 2 derivative vegetation indices (Case study: Organic paddy in Candipuro, Lumajang).

The demand for crop production has increased as well as human population. Consequently, agricultural production needs to be enhanced to meet these food requirements. Rice plays a crucial role as a commodity, producing rice, a staple food for humans. Therefore, to support this, a faster, easier, and more accurate modern method is needed to estimate harvest yields and determine food supply quantities. The use of remote sensing technology is becoming an alternative method for estimating harvest yields. This study was conducted in the organic rice fields of Candipuro District, Lumajang Regency. The objective of this study was to analyze and test the accuracy of SAVI (Soil Adjusted Vegetation Index) and EVI (Enhanced Vegetation Index) in estimating the harvest yield of organic rice. The images used were from Sentinel 2 acquired on November 6, 2020 (period I) and June 4, 2021 (period II). There were 30 land plots with a total of 311 sample points determined randomly. The best correlation results for periods I and II were found with EVI transformation, with correlation coefficient values (r) of 0.849 and 0.865, respectively. The highest accuracy level was obtained from the EVI calculation in period II with the equation Y = 35.262X - 4.062, resulting in an RMSE (Root Mean Square Error) value of 0.071 ton/ha. [ABSTRACT FROM AUTHOR]