Aquaculture farming plays a central role in humanity's challenge to feed the world population given its increasing importance in the seafood sector.

Aquaculture farms face risks from a multitude of physical and biological factors including long-term stressors, like climate change or eutrophication, or catastrophic events, like storms.
Meanwhile, different environmental factors affect the suitability of locations for aquaculture farming, like temperature and nutrient levels. Choosing farm locations with high productivity while minimizing risks and environmental impacts is a difficult decision problem. In particular, small and large scale farmers lack suitable information products that can facilitate making decisions on potential locations for setting up aquaculture farms. Available tools do not provide synthesized information in an open, coherent, and intuitive way.

Our goal in this project is to create maps of suitability for aquaculture farms by combining information about various risks and benefits at specific locations. To create these maps we use regional- and global-scale data on ocean characteristics provided by blue-cloud and a number of transparent algorithms for heuristic judgement and aggregation of these factors.
This can provide aquaculture farmers and policy-makers with a useful tool to support deciding on locations and, simultaneously, give them insights into relevant factors in their decision-making that can be flexibly explored by using different algorithms.



The Challenge



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    Hong Kong
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