Remote Measurement of Nitrogen and Leaf Chlorophyll Concentration Using UAV-Based Multispectral Imagery from Rice Crop Field in Sri Lanka

Abstract

Rice is the staple food in Sri Lanka and the widely cultivated crop among farmers. Proper assessment of crop nitrogen and rice crop condition in on-going cultivation helps farmers to effectively manage the crop inputs. Conventional methods of assessing rice crop condition, i.e., crop greenness by human eyes and leaf color chart method, are subjective and have limitations in converting in to quantitative decisions. Thus, assessing the nitrogen level, leaf greenness and leaf chlorophyll concentration has become challenging with traditional methods in Sri Lankan rice industry. This study evaluates the performance of applying remote sensing technique using unmanned aerial vehicle (UAV) for non-destructive, measurement of crop nitrogen level, leaf greenness and chlorophyll concentration. Multispectral UAV images were acquired using multispectral drone from a controlled rice field (Bg 300, at booting stage) in the rice research station with four blocks of treated nitrogen application levels. On-ground measurements were taken from quadrant size (1 m × 1 m) sample areas in each block. From the UAV-derived RGB orthomossaic and reflectance maps, normalized vegetative index (NDVI) was calculated. Finally, the averaged NDVI values extracted from the quadrant areas of the rice crops were compared against the ground measured values using Pearson correlation fit analysis. The results proved that NDVI strongly correlated with leaf chlorophyll, leaf greenness and nitrogen level with R2 = 97%, 96.8% and 96.4%, respectively. Findings strongly suggest the possibility of remotely measuring of nitrogen and chlorophyll level of the rice crop field.