Monitoring oil palm health using spatial data is essential for optimizing plantation productivity and supporting sustainable management. This study assessed vegetation conditions at Sultra Prima Lestari Ltd. plantation in Southeast Sulawesi, Indonesia, using Sentinel-2A imagery acquired in June 2025 and field data collected from Leaf Sampling Units (LSUs) between April-July 2025. The Normalized Difference Vegetation Index (NDVI) was calculated from the imagery and classified into three health categories: unhealthy (from −1.00 to 0.15), moderately healthy (from 0.15 to 0.35), and very healthy (from 0.35 to 1.00). Field validation across 94 stratified random sampling plots confirmed that NDVI reflects differences in canopy density and leaf greenness. Correlation analyses showed positive associations with plant macronutrients: nitrogen (R² = 0.603), phosphorus (R² = 0.575), potassium (R² = 0.645), and magnesium (R² = 0.520). Spatial analysis revealed heterogeneity in vegetation health across the plantation, with very healthy areas concentrated in central and western divisions, and unhealthy patches primarily in the eastern division. These results indicate that NDVI, when interpreted alongside systematic field measurements, is a cost-effective and spatially explicit indicator of oil palm physiological condition, without implying absolute validation. The findings support targeted, site-specific agronomic interventions and demonstrate the value of integrating moderate-resolution satellite imagery with field-based data for scalable monitoring of large-scale tropical plantations.
Salihin et al. (Thu,) studied this question.