Implementing spatiotemporal kriging interpolation based on 3D model

When sample and unsample locations are relative with time and space, the replacement of pure space with spatiotemporal geo-statistical approaches can offer more data to support research. This led to the study of spatiotemporal geo-statistical models and spatiotemporal interpolation. The 3D model is to take time as third dimension coordinate and replace separation between a pair of survey station in pure space with spatiotemporal ones. Firstly analysis about the attribute, distribution and relevance of spatiotemporal data were done. Secondly the maximum likely variogram model and effective sill, nugget, range were derived. Thirdly, the spatiotemporal kriging interpolation was implemented in two kind models and the result of interpolation was showed in 3D curve surface. Lastly, cross validation was done to test the validity of spatiotemporal interpolation based on 3D model and the results was analyzed. It shows that spatiotemporal approaches implemented in here can provide more information on random domains with some accuracy.