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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.

BioSpace project provides early warning system for locust and fall armyworm pests in China and Laos

Improving soybean production in Kenya using digital and extension approaches

In Kenya, soybean is a key crop in helping to improve livelihoods and nutrition. However, production only meets 10% of the market needs due to the effects of poor agricultural practices and pests and diseases. To address these issues, this project will provide a frontier system that integrates Earth Observation technology, pest modelling and best-practice approaches in agricultural extension to increase soybean productivity and quality. The project aims to reach 30,000 farmers, of which support will be given particularly to women farmers in helping them to engage with this high-value commodity, access local markets and improve their livelihoods.

BioSpace: Using space-enabled remote sensing for long term sustainable growth of biopesticide use

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.

Remote sensing use for mapping Parthenium in Pakistan

It is projected that food demand will more than double by 2050 due to climate changes. Food security in Pakistan is particularly reliant on its ability to produce wheat and rice, however, an invasive species of weed, the “Famine Weed” (Parthenium hysterophorus), has been identified as a critical threat to agriculture and human prosperity in Pakistan.