Related Experiment Video
Updated: Jun 6, 2025

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Nonlinear and synergistic effects of demographic characteristics on urban polycentric structure using SHAP
Yichen Ruan1, Xiaoyi Zhang1, Mingyu Zhang2
1School of Spatial Planning and Design, Hangzhou City University, Hangzhou, 310015, China.
Abstract:
Polycentric urban development is promoted by urban planners and policy makers for its perceived benefits of alleviating urban issues. Theoretically, a polycentric urban structure is formed when different demographic groups present a collection of diverse and unique housing location preferences. Yet, only limited empirical studies have fully captured the complex effects of demographic characteristics on urban polycentric structures. Our study utilizes detailed demographic data and employs interpretable machine learning models to elucidate the nonlinear and synergistic relationship between demographic characteristics and the urban polycentric structure in the context of a city of 10 million population in China. When characterizing urban centers, the three most important demographic groups are young females, senior married couples, and middle-aged single individuals with basic education. Each urban center presents distinctive demographic compositions; for instance, middle-aged married individuals exerting a stronger influence in certain contexts, whereas in senior resident groups, married individuals have a more pronounced impact. Spatial heterogeneity is observed in the demographic profiles of urban centers; for instance, primary central cores are predominantly young, single females, whereas peripheral and secondary centers have stronger presence of highly educated residents.
Related Concept Videos
Analysis of Population Pharmacokinetic Data
Relationship Formation
Mechanistic Models: Compartment Models in Individual and Population Analysis
Mechanistic Models: Compartment Models in Algorithms for Numerical Problem Solving
In individual population analyses, different algorithms are employed, such as Cauchy's method, which uses a...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This...

