Modeling urban growth with geographically weighted multinomial logistic regression

Jun Luo; Nagaraj Kapi Kanala

doi:10.1117/12.812714

5 November 2008 Modeling urban growth with geographically weighted multinomial logistic regression

Jun Luo, Nagaraj Kapi Kanala

Proceedings Volume 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics; 71440M (2008) https://doi.org/10.1117/12.812714
Event: Geoinformatics 2008 and Joint Conference on GIS and Built Environment: Geo-Simulation and Virtual GIS Environments, 2008, Guangzhou, China

Abstract

Spatial heterogeneity is usually ignored in previous land use change studies. This paper presents a geographically weighted multinomial logistic regression model for investigating multiple land use conversion in the urban growth process. The proposed model makes estimation at each sample location and generates local coefficients of driving factors for land use conversion. A Gaussian function is used for determine the geographic weights guarantying that all other samples are involved in the calibration of the model for one location. A case study on Springfield metropolitan area is conducted. A set of independent variables are selected as driving factors. A traditional multinomial logistic regression model is set up and compared with the proposed model. Spatial variations of coefficients of independent variables are revealed by investigating the estimations at sample locations.

Citation Download Citation

Jun Luo and Nagaraj Kapi Kanala "Modeling urban growth with geographically weighted multinomial logistic regression", Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71440M (5 November 2008); https://doi.org/10.1117/12.812714

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