Drones, or unmanned aerial vehicles (UAVs), have become synonymous with death and destruction. Then again, as UAVs have become more affordable and ubiquitous, they have also been adapted for diverse applications – ranging from the quixotic (hurricane-hunting, Amazon delivery) to the recreational (photography and videography) and the utilitarian (3D mapping, remote-sensing, policing and disaster management). In fact, if projections are anything to go by, these ‘harbingers of doom’ could become indispensable tools to promote life in the next decade or so.

 

As technology has infiltrated our lives through smartphones, computers and the internet, agriculture has remained the last bastion of tradition as an enterprise of human labour and intellect. Despite mechanisation, much of farming involves human labour and legwork. Farmers walk down their fields checking for plant health, the presence of weeds, bugs, parched soil and other overt signs of distress. However, even with a trained eye, it is often hard to notice diminished photosynthesis or signs of pathogen infestation early enough to avoid large losses. This, in turn, has led to a culture of prevention where farmers have resorted to the excessive use of water, fertilisers, pesticides, etc. Otherwise, the cost of non-intervention, or even late intervention, is massive crop failure.

 

As the world’s population inches toward eight billion, the focus worldwide has shifted to feeding it in a sustainable way. This has led to the emerging concept of precision agriculture – a farm management concept that is based on observing, measuring and responding to both inter- and intra-field variability in crops. The goal, simply stated, is to more efficiently apply a farm and farmer’s limited resources to gain maximum yield. This requires constant observation, realtime feedback and an objective analysis of the outcomes in terms of crop yields, plant health and other data. Drones are fast becoming an efficient tool to collect aerial images and to use them to generate such meaningful data.

 

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