A low-altitude remote sensing (LARS) system with an unmanned radio-controlled helicopter platform was used to acquire high-quality images of land and crop properties with higher spatial and temporal resolution. It is vital to visualize the relationship of LARS-based images with crop parameters, such as crop nutrient levels, etc. Five N-treatment (0, 33, 66, 99 and 132 kg ha-1>) rates with three replications each were arranged in a randomized manner for testing the LARS image acquisition system. Images were taken by the image acquisition unit of the system operated at a height of 20 m over the experimental plots. The coefficient of determination (r2>) between N-treatments against NDVIlars>, NDVIspectro>, GNDVIlars>, and chlorophyll content estimated from leaf radiance values were in the range from 0.70 to 0.90, showing a high level of correlation between them. The test to verify the suitability of LARS-based images against spectrophotometer readings showed linear variation for the NDVI index with r2> of 0.70 and 0.80 for 45-day-old and 65-day-old crops, respectively, Linear models were also developed to estimate chlorophyll content from NDVIlars> and GNDVIlars> index values, from the images, with better correlation for the latter (r2> ≈ 0.82) and subsequently could determine the nitrogen deficiency level. The yield estimation model, with higher r2> values of 0.95 and 0.98 for NDVIlars> and GNDVIlars>, respectively, further justified the suitability of the LARS system.