The study on the exploratory spatial data mining method based on partial random walk and its application in GPS TEC analysis

The Ionosphere plays an important role in atmosphere, whose globally distributed total electronic content (TEC) obtained by GPS technology is the important data source of geographic or earth information system for monitoring global change. This paper applies the rigging method of deionization variable theory to mine the knowledge of large scale of tendency variation and small scale of random variation, and discovered that the large scale tendency can be modelled as a 9 orders of globe harmony function, and the small scale variation more prefers to a zero mean non-stationary random process of symmetrically distributed. Applying the developed unit-root test, the small scale residual is identified with the characteristic of 3 orders of partial random walk, and thus the residuals after performing 3 orders of difference show the property of white noise process. The general Kriging predication method based on the partial random walk model is constructed to re-build the spatial process precisely. The result exhibits that the partial-random-walk-based test can be used to mine the auto-correlated structure of zero mean non-stationary error function or small scale variation, and the constructed general kriging method can improve the prediction result.