Bananas diseases and insect infestations monitoring using multi-spectral camera RTK UAV images

Recent advances in multi-spectral imagery generated using Unmanned Aerial Vehicles (UAVs) have opened new possibilities for agricultural crop monitoring and management, even in small-holder farms. In this study, Vegetation Indices (VIs) derived from UAV-captured multi-spectral images with Real-time kinematic positioning were applied to assess the health and growth of banana plants and fruits. Multi-spectral images consisting of Red, Green, Blue, Red-EDGE, and Near-Infrared were collected using quadcopter UAV flown at a height of 80 m. Several VIs was examined with ground truth from 67 sampling sites for healthy and stressed banana plants. The results indicate that Triangular Vegetation Index (TVI), Normalized Difference Red Edge Index (NDRE) and Normalized Difference Vegetation Index (NDVI) provide valuable information for crop monitoring in a timely and quantifiable manner. Kappa coefficients comparing plant health with TVI (0.85), NRDE (0.83) and NDVI (0.75) provide excellent result with overall accuracy being 92.48%, 89.66% and 88.95%, respectively. The data preparation workflow was implemented using Free and Open-Source Software. The datasets generated and the procedures described are not only useful to local farmers for mitigating loss in yield in banana plantations but can also offer a generic solution in promoting smart farming.