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Developing a dynamic approach using earth observation technology to improve pest risk modelling

Earth observation to improve critical datasets for pest risk modelling

Rising temperatures have led to pests, diseases and weeds establishing in areas of the world that were previously uninhabitable. Furthermore, growth in global trade and new trade pathways increase the risk of accidental movement of pests. Earth Observation (EO) and climatic data can help by improving predictions about where potential agricultural pests and diseases may be a threat. Information produced by models can help decision makers understand and prepare for future risks. Working with a consortium of researchers, this project will use EO data to improve the data layers used in models that predict where pests can establish, including irrigation, areas under protected agriculture and climatic canopy conditions, demonstrating the improvements made to species distribution estimations for key pests and biological control agents.

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Pests and diseases cause significant losses of crops around the world and are a significant threat to food security. In China and Laos, locusts affect over two million hectares of agricultural land and recently, the fall armyworm is becoming prevalent in China and Southeast Asia, already affecting 35,000 hectares of maize in Laos. Due to a lack of detailed information on where risks to crops are greatest and farmers using inappropriate and ineffective control measures, managing the damage from pests can be problematic.