This study evaluates the applicability of two multiband cameras used with a small unmanned aerial vehicle (UAV) for stress detection in citrus orchards. The aerial images were acquired using both cameras at UAV flying altitudes of 30, 60, and 90 m were processed to extract histogram distributions of green normalized difference vegetative index as feature datasets. Support vector machine based classification results revealed that the high resolution camera with near infrared (670–750 nm) and green bands was better in detecting healthy and unhealthy citrus trees. The highest average overall classification accuracy of 91±7% (mean ± standard deviation) was obtained using feature datasets of high resolution camera images acquired at an altitude of 60 m.