Application of Unmanned aerial vehicles (UAVs) for remote sensing has given many advantages. The measurement of reflectance spectra in plant canopies can be the basis in detecting nitrogen content. Chlorophyll concentrations at different levels resulted in the reflectance spectra measured in the canopy, also being different. This study aimed to develop the method of Nitrogen monitoring using UAV imagery combined with Leaf Chart Color (LCC) to estimate plant nitrogen concentration in rice. To develop the Normalized Difference Vegetation Index (NDVI) indices, the Leaf Chart Color was used to measure the greenness of the leaf crop. A high-resolution digital camera modified with NDVI-7 filter mounted to UAV that sensitive to infrared wavelength. The flight altitude was 3, 10, and 15 m. To measure the strength of a linear association between LCC measurements and NDVI estimations, we used a Pearson one-tailed correlation. The Pearson coefficient indicates that the correlation is a strong negative correlation (-0.822) at 3 m altitude, weak correlation (-0.4562) at 10 m altitude, and no correlation at 15 m altitude.