Remote sensing technology using Unmanned Aerial Vehicles (UAVs/drones) offers up-to-date, high-resolution data that can effectively support agricultural monitoring, particularly in rice cultivation. This study analyzes the health of rice plants in Merauke, South Papua, Indonesia, using the Normalized Difference Vegetation Index (NDVI) derived from drone imagery. NDVI, which ranges from -1 to +1, is used to quantify vegetation greenness and thereby infer plant health status. The health of rice plants is categorized into four NDVI-based classes: very good (0.721–0.92), good (0.421–0.72), normal (0.221–0.42), and poor (0.11–0.22). Using this classification, the analysis shows rice areas with normal health covering 14,877,315 ha, good health 9,846,833 ha, and very good health 8,922,892 ha. The results demonstrate that drone-based NDVI analysis can provide fast and accurate spatial information on rice health, supporting decision making for crop management and food security.
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