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Modeling the drivers of urban land use change in the Pearl River Delta, China: Integrating remote sensing with socioeconomic data

Karen Seto and 1 other contributor

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    Abstract

    This paper estimates econometric models of the socioeconomic drivers of urban land use change in the Pearl River Delta, China. The panel data used to estimate the models are generated by combining high-resolution remote sensing data with economic and demographic data from annual compendium. The relations between variables are estimated using a random coefficient model. Results indicate that urban expansion is associated with foreign direct investment and relative rates of productivity generated by land associated with agricultural and urban uses. This suggests that large-scale investments in industrial development, rather than local land users, play the major role in urban land conversion.