Project Description

Land-Satellite imagery will be used to provide a sequence of terrain maps showing changing weather patterns over time.  Superimposed on these will be environmental data collected in real time from sample locations in Chile, the USA and New Zealand to illustrate the atmospheric variability of the individual regions, which will provide a visual comparison in addition to the numeric correlations resulting from analysis of the data collected by telemetry devices feeding in real time to the GIS database, which can be interrogated for numerous cross-correlation purposes.  

In some cases the data received will be in fuzzy form.  Using contemporary neural network modelling software, these results will be collated and depicted in such a manner that scenarios for considering the ‘best year’ proposition can be appreciated and in conjunction with other factors, lead to the modification and optimisation of both growing and production methods.   These neural networks will be analysed statistically to extract knowledge as to which variables have most effect on desired outcomes.

Project Diagram illustrates the principal components, their interactions and data flow through the concept intended for prototype implementation.