Bananas are considered vital for economic development and food security in many countries. Whilst the application of remote sensing for the improved management of some abiotic and biotic constraints and for production forecasting has been investigated, there still remains a substantial knowledge gap. This study addressed this gap by developing and testing the following remote sensing applications i) to establish a methodology for the accurate detection and delineation of individual banana crowns from unoccupied aerial vehicle (UAV) imagery to support the monitoring of individual plants within mixed age, asynchronous commercial banana plantations; ii) to derive a new time series approach for differentiating and quantifying key phenology growth stages, plant morphology and physiology in commercial banana plantations; iii) to assess the accuracies of hyperspectral and multispectral remote sensing for measuring the presence and severity of pest mite infestations on banana plants.

Datasets include UAV Parrot Sequoia Multispectral Camera captured over 22 flight campaigns (i and ii) and Hyperspectral datasets used for mite monitoring (iii).