English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

A time series of fractal dimension values of urban form can form a fractaldimension curve and reflects urban growth. In many cases, the fractal dimensioncurves of cities can be modeled with logistic function, which in turn can beused to make prediction analysis and stage division studies of urban evolution.Although there is more than one method available, it is difficult for manyscholars to estimate the capacity parameter value in a logistic model. Thispaper shows a nonlinear autoregressive approach to estimating parameter valuesof logistic growth model of fractal dimension curves. The process is asfollows. First, differentiating logistic function in theory with respect totime yields a growth rate equation of fractal dimension. Second, discretizingthe growth rate equation yields a nonlinear autoregressive equation of fractaldimension. Third, applying the least square calculation to the nonlinearautoregressive equation yields partial parameter values of the logistic model.Fourth, substituting the preliminarily estimated results into the logisticmodels and changing it into a linear form, we can estimate the other parametervalues by linear regression analysis. Finally, a practical logistic model offractal dimension curves is obtained. The approach is applied the Baltimore'sand Shenzhen's fractal dimension curves to demonstrate how to make use of it.This study provides a simple and effective method for estimating logistic modelparameters, and it can be extended to the logistic models in other fields.

Nonlinear Autoregressive Approach to Estimating Logistic Model Parameters of Urban Fractal Dimension Curves