Integrating Spatial Markov Chains and Geographically Weighted Regression-Based Cellular Automata to Simulate Urban Agglomeration Growth: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area

Integrating Spatial Markov Chains and Geographically Weighted Regression-Based Cellular Automata to Simulate Urban Agglomeration Growth: A Case Study of the Guangdong–Hong Kong–Macao Greater Bay Area

Urban agglomeration is an important spatial organization mode in China’s attempts to attain an advanced (mature) stage of urbanization, and to understand its consequences, accurate simulation scenarios are needed. Compared to traditional urban growth simulations, which operate on the scale of a sing...

Full description

Bibliographic Details
Main Authors: Yabo Zhao, Dixiang Xie, Xiwen Zhang, Shifa Ma
Format: Article
Language:English
Published: MDPI AG 2021-06-01
Series:Land
Subjects:
urban agglomeration
spatial Markov chains
cellular automata
geographic weighted regression
land use/cover change
Online Access:https://www.mdpi.com/2073-445X/10/6/633

Internet

https://www.mdpi.com/2073-445X/10/6/633

Similar Items