Pasar al contenido principal

page search

Biblioteca A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model

A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model

A Partitioned and Heterogeneous Land-Use Simulation Model by Integrating CA and Markov Model

Resource information

Date of publication
Diciembre 2022
Resource Language
ISBN / Resource ID
LP-midp000146

Conversion rule is a key element for a cellular automata (CA) model, and it is a significant and challenging issue for both domestic and international experts. Traditional research regarding CA models often constructs a single conversion rule for the entire study area, without differentiating it on the basis of the unique growth features of each location. On the basis of this, a partitioned and heterogeneous land-use simulation model (PHLUS) is constructed by integrating a CA and Markov model: (1) A general conversion rule is constructed for the entire study area. By establishing a land development potential evaluation index system, the conversion rule is refined and differentiated; (2) By coupling a CA model with a Markov model, PHLUS can realize land-use simulation both in micro and macro scales. A simulation study is conducted for the Pearl River Delta region. The results show that: (1) By transforming the CA model rules to further distinguish zones, the accuracy is improved. Compared with the traditional CA-Markov model, the simulation accuracies for 2010 and 2020 are improved by 11.55% and 7.14%, respectively. For built-up land simulation, the PHLUS simulation errors for 2010 and 2020 are only 0.7% and 0.57%, respectively; and (2) Under land-use simulation for 2030, cultivated land and forest land will transfer to built-up land. The built-up land area will reach 10,919 km2. Guangzhou and Shenzhen have the greatest potential for land development, and the built-up land area for the two cities will reach 2727 km2.

Share on RLBI navigator
NO

Authors and Publishers

Author(s), editor(s), contributor(s)

Wang, QihaoLiu, DongyaGao, FeiyaoZheng, XinqiShang, Yiqun

Corporate Author(s)
Geographical focus