  We model two time and space scales discrete observations by using a unique
continuous diffusion process with time dependent coefficient. We define new
parameters for the large scale model as functions of the small scale
distribution cumulants. We use the non - uniform distribution of the
observation time intervals to obtain consistent and unbiased estimators for
these parameters. Closed form expressions for migration proportions between
spatial domains are derived as functions of these parameters. The models are
applied to estimate migration patterns from satellite tag data.
