Estimation of coffee garden productivity using sentinel 2A-imagery by simple ratio vegetation index

The southern part of Malang Regency is developing coffee plants, but information related to coffee production has not been presented regularly. Therefore, it is necessary to analyse coffee production to obtain information on the potential of coffee production in the southern Malang Regency. Usually, the analysis is done by waiting for the coffee harvest time, but it takes a long time. Remote sensing technology has been developed that utilises high-resolution imagery in Sentinel 2A. This technology is expected to overcome these problems. The analysis was carried out through a spectral transformation approach using a vegetation index as a simple ratio (SR). The study aims to analyse the SR-based coffee production estimation model. The research was conducted on the people's coffee plantation land of Wajak District and its surroundings. Determination of point observation using land unit maps based on differences in slope, soil type, and land use using the stratified randomised sampling point method. The modelling application uses ArcGIS 10.8, QGIS 3.24, and RStudio, analysis methods through correlation, linear regression, and validation tests using mean absolute percentage error. The research parameters are the spectral transformation of Sentinel 2A images into SR and the actual production of coffee (tons/ha/year). The average coffee production in the study area ranged from 0.32 to 2.57 tons/ha/year. Land characteristics influence the distribution of coffee production in the study area. The production model (Ŷ) based on SR (x) is Ŷ = 0.27×SR-0.74 (R²=0.7724; p<0.05). SR has an estimated effect on coffee production of 77.24%. The model compiled by the model is classified as feasible (37.39%). Coffee production in the study area can be analysed using SR with good model accuracy.