<![CDATA[Indonesia’s potato fields are typically small and fragmented, making coarse resolution moisture products prone to spatial mismatch and limiting their usefulness for precision water management. This study developed plot scale, water based suitability information for potato by integrating UAV multispectral imagery with field measurements of soil water availability and plant height response. UAV imagery was processed into four vegetation indices, namely NDWI, SAVI, MSAVI, and SR, followed by geostatistical mapping. Relationships between indices and measured water availability were evaluated using correlation, linear regression, paired t test, and principal component analysis to examine inter index structure and redundancy. NDWI showed the most consistent performance, with a moderate positive correlation with measured water availability (r = 0.47), while SAVI and MSAVI were negatively correlated (r = −0.46) and SR showed the weakest association (r = −0.33). The NDWI based regression for water availability estimation was y = 0.50x + 29.68 with R² = 0.22. The paired t test indicated no significant difference between NDWI based estimates and field measurements, with mean values of 30.09 percent and 30.52 percent, respectively, across 17 observations. Water based land suitability classes were then refined using boundary line analysis linking water availability to plant height response, producing plot scale criteria suitable for precision zoning rather than landscape level evaluation.]]>
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