Aquaculture site selection using big data from remote sensing
Aquaculture site selection using big data from remote sensing
WATER uses big data from remote sensing to evaluate multiple criteria such as depth for cage moorings, water temperature, and dissolved oxygen
Map depth, wave height, oxygen, and other parameters in regional seas. Use it to find out how well a particular species will grow in marine waters by analysing suitability. Using Big Data from satellite remote sensing and computer models we evaluate multiple criteria such as depth for cage moorings, water temperature, and dissolved oxygen.
Select over 50 species from Atlantic salmon or European seabass to check the suitability map scaled from one (bad) to five (highly suitable). The map shows suitability as the result of a Big Data index that combines six different parameters.
Suitable areas for aquaculture are shifting as our environment changes — WATER builds in the capacity to determine how the Blue Economy will be affected by climate change. Climate models that predict shifts in water temperature, oxygen, and other factors are used in WATER to help farmers, managers, and investors understand how business may be affected by such changes.
WATER reduces the risk and cost of aquaculture suitability assessment for all the major commercial aquaculture species
WATER provides existing and prospective aquaculture farms with an assessment of spatial suitability in different areas. Search for the parameters of interest including depth, current speed, wave height, oxygen and chlorophyll.
Big data from remote sensing leverages planning of suitable areas for aquaculture based in the exclusive economic zones based on parameters and species of interest. Reduce the due diligence cost and effort of determining which areas are suitable.
The climate change module models the likely suitability of different species in the future. Predict changes for both moderate and more extreme climate change scenarios, considering a medium-term (mid-century) and long-term (end-of-century) time horizon.
