Estimation of Rubber Yield Using Sentinel-2 Satellite Data

Rubber is a perennial plant grown to produce natural rubber. It raw material for industrial and non-industrial products important the world economy. The sustainability of rubber production is, therefore, critical smallholder livelihoods economic development. To maintain price stability, it estimate yields in advance. Remote sensing technology can effectively provide large-scale spatial data; however, productivity estimates need be processed from high resolution data generated satellites with accuracy reliability, especially livelihood areas where smaller plots contrast large farms. This study used reflectance Sentinel-2 satellite imagery acquired 12 months between December 2020 November 2021. included 213 on agriculture were collected. Six vegetation indices (Vis), namely Green Soil Adjusted Vegetation Index (GSAVI), Modified Simple Ratio (MSR), Normalized Burn (NBR), Difference (NDVI), (NR), (RVI) yield. found that red edge spectral band (band 5) provided best prediction R2 = 0.79 RMSE 29.63 kg/ha, outperforming all other bands VIs. MSR index highest coefficient determination, 0.62 39.25 kg/ha. When was combined VI, MSR, model only slightly improved, determination (R2) 0.80 an 29.42 results demonstrated are suitable yield farmers. findings this as guideline apply countries or areas. Future studies will require use derived combination meteorological data, well application complex models, such machine learning deep learning.