<![CDATA[This research aims to develop a method of mapping soil organic matter content in oil palm land using image processing technology. The data includes oil palm and bare land images and field measurements in pH, humidity, temperature, TDS, and EC. Correlation analysis showed a significant relationship between image spectral components (especially in the blue channel with r=0.3640) and soil organic matter content. The distribution of organic matter content showed concentrations in the 4.5-5.5% range with an average value of about 5%. The image processing-based predictive model successfully mapped the spatial variation of organic matter content with sufficient accuracy. The mapping results show spatial heterogeneity that can be used as a basis for implementing precision agriculture in oil palm lands. This research proves the potential of image processing technology as a non-destructive method for characterising and monitoring soil quality in oil palm plantations.]]>
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