<![CDATA[The productivity of brackish water aquaculture is often fluctuative due to suboptimal water quality and the difficulty of monitoring pond water fertility over large areas. This study aims to identify the main components of pond water fertility and to examine the relationship between RGB spectral values from drone imagery with nitrate and phosphate parameters. Image acquisition was carried out using a DJI Mavic 2 Pro drone at an altitude of 50 m, with 15 samples collected from three semi-intensive ponds in Pondong Baru Village, Kuaro District, Paser Regency. The measured parameters included brightness, temperature, salinity, pH, dissolved oxygen, turbidity, nitrate, and phosphate. Data analysis was performed using Principal Component Analysis (PCA) and linear regression. The results showed that two principal components (PCs) explain 87.1% of the data variation. PC1 is dominated by temperature (0.967), pH (0.912), brightness (0.882), and dissolved oxygen (0.851), while PC2 is dominated by phosphate (0.798) and nitrate (-0,637). Linear regression for phosphate showed R² = 0.495 (marginal significance), while nitrate was not significant (R² = 0.033). Drone imagery has the potential to be effective for monitoring pond water fertility, particularly for phosphate parameters. Keywords: pond water fertility, drone imagery, RGB, PCA, linear regression, nitrate, phosphate]]>
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