Automated image analysis and processing using UAV-deployed remote sensors


UK Partners: Dr Ji ZHOU, Earlham Institute

China Partners: Prof Tao CHENG, Nanjing Agricultural University

Project Summary: 

China is using the world's 7% of the cultivated land to feed 22% of the world’s population, a remarkable achievement but at a cost of excessively using fertilisers and chemical applications such as herbicide, insecticide and fungicide in agriculture. A series of environmental and agronomical problems have emerged including soil compaction, acidification, pesticide residue toxicity, pest resistance, environmental pollution, and ecological imbalance. Hence, how to rationally, timely, and effectively apply fertilisers and other chemicals to enable better agronomic practices has become the utmost important challenge that needs to be addressed urgently; otherwise, it can threaten agricultural product quality and ecological environment safety, jeopardising the longterm economic growth in China. 

In this project, the partners will focus on developing an automated image analysis solution to identify key wheat growth stages based on large aerial images captured by UAVs (unmanned aerial vehicles) and fixed-wing light aircrafts in the UK and China. So, we can enable the Agri-Food sector to estimate the appropriate timing for applying fertilisers and chemicals during the season based on agricultural aerial imagery data. The solution will be built upon our existing analytic platform AirSurf, together with key intellectual inputs from our Chinese partners.