Analyzing urbanization data using rural-urban interaction model and logistic growth model

Abstract The level of urbanization is a valuable indicator for projections of some global trends. However, urbanization levels may be based on unreliable data. This study proposes a simple method for identifying problems in the time series of urban and rural populations of a country. The time series were fitted to a rural–urban interaction population model, and improper model coefficients indicated that the time series were questionable. The upper limit of the urbanization level was calculated to determine whether the trend of the urbanization level follows the logistic growth model. An analysis of the frequency–spectrum relationship was performed to determine whether the urbanization process is a self-organized criticality and to consolidate the low possibility for chaos in the urbanization model. Empirical analyses were conducted using data from the United States, China, and India to verify data reliability and to determine the dynamical mechanism of urbanization. This is critical for demographers, geographers, other scientists, and policymakers.

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