The aim of this research is to provide an environmental visualization platform to transfer knowledge between scientists and local farmers, in order to assist farmers with managing their farmland effectively based on scientists' knowledge. Better productivity potential for farmland is based on EM38 datasets, which represent multi-depth soil moisture and are developed by the Precision Agriculture Research Group at the University OF NEW ENGLAND.
The environmental visualization platform SIEVE (Spatial Information Exploration And Visualization Environment) is used for simulating the
current situation of the farmland and predicting the future. Agronomic modeling is another key issue of the research - researchers can collaborate with scientists and local farmers and recommend practical agronomic models based on EM38. Afterwards, experiments to test the practicality of the platform are performed by dividing farmers and scientists into 3 groups to employ the platform in varying degrees. In the first group, farmer and scientists just transfer knowledge through phone and use traditional 2D maps of EM38;in the second group, farmer and scientists communicate though phone, and with 3D visualization tools support(not collaborative working); in the third group,farmers and scientists not only communicate on the phone, but also remotely access SIEVE server(with collaborative working support)to upload and obtain crops relative knowledge such as photos and documents. Finally, we compare the results of different groups by evaluating time consuming and level of mutual understanding, and test the benefit of environmental visualization techniques in transferring knowledge between scientists and farmers.