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Proceedings Paper

Modeling urban growth with geographically weighted multinomial logistic regression
Author(s): Jun Luo; Nagaraj Kapi Kanala
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Paper 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.

Paper Details

Date Published: 5 November 2008
PDF: 11 pages
Proc. SPIE 7144, Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics, 71440M (5 November 2008); doi: 10.1117/12.812714
Show Author Affiliations
Jun Luo, Missouri State Univ. (United States)
Nagaraj Kapi Kanala, Missouri State Univ. (United States)


Published in SPIE Proceedings Vol. 7144:
Geoinformatics 2008 and Joint Conference on GIS and Built Environment: The Built Environment and Its Dynamics
Lin Liu; Xia Li; Kai Liu; Xinchang Zhang; Xinhao Wang, Editor(s)

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