  Fourier analysis and cross-correlation function are successfully applied to
improving the conventional gravity model of interaction between cities by
introducing a time variable to the attraction measures (e.g., city sizes). The
traditional model assumes spatial interaction as instantaneous, while the new
model considers the interaction as a temporal process and measures it as an
aggregation over a period of time. By doing so, the new model not only is more
theoretically sound, but also enables us to integrate the analysis of temporal
process into spatial interaction modeling. Based on cross-correlation function,
the developed model is calibrated by Fourier analysis techniques, and the
computation process is demonstrated in four steps. The paper uses a simple case
study to illustrate the approach to modeling the interurban interaction, and
highlight the relationship between the new model and the conventional gravity
model.
