Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

Yu Nong; Qingyun Du; Kun Wang; Lei Miao; Weiwei Zhang

doi:10.1117/12.812718

5 November 2008 Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China

Yu Nong, Qingyun Du, Kun Wang, Lei Miao, Weiwei Zhang

Author Affiliations +

Proceedings Volume 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics; 71440Q (2008) https://doi.org/10.1117/12.812718
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Urban growth modeling, one of the most important aspects of land use and land cover change study, has attracted substantial attention because it helps to comprehend the mechanisms of land use change thus helps relevant policies made. This study applied multinomial logistic regression to model urban growth in the Jiayu county of Hubei province, China to discover the relationship between urban growth and the driving forces of which biophysical and social-economic factors are selected as independent variables. This type of regression is similar to binary logistic regression, but it is more general because the dependent variable is not restricted to two categories, as those previous studies did. The multinomial one can simulate the process of multiple land use competition between urban land, bare land, cultivated land and orchard land. Taking the land use type of Urban as reference category, parameters could be estimated with odds ratio. A probability map is generated from the model to predict where urban growth will occur as a result of the computation.

Citation Download Citation

Yu Nong, Qingyun Du, Kun Wang, Lei Miao, and Weiwei Zhang "Modeling the dynamics of urban growth using multinomial logistic regression: a case study of Jiayu County, Hubei Province, China", Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71440Q (5 November 2008); https://doi.org/10.1117/12.812718

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KEYWORDS

Roads

Geographic information systems

Systems modeling

Agriculture

Data modeling

Binary data

Decision support systems

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