Urban expansion using remote-sensing data and a monocentric urban model

Abstract The expansion of urban land use is an indispensable tool of urban policy, particularly in developing countries which are facing rapid urbanization. However, most sophisticated spatial-analysis methods used in developed countries are not applicable to developing countries due to the limited availability of spatially-resolved statistical data. This study examines the applicability of a simple, classic monocentric urban model for capturing urban activities in three Chinese cities in 2003 and 2013. The model estimates traffic cost, goods consumption, area of available residential floor space, and rents for residential floor space by aggregating urban statistics and estimating urban areas using remote sensing data. We find that some predictions of our model are inaccurate due to its simple, static nature; however, the model predicts meaningful temporal trends in key variables and meaningful differences among the population and economic growth trajectories of the three cities. Our results imply that the classic monocentric model is useful for approximating urban activities and for strategic planning of urban traffic policies, as it allows tracing of the causal mechanisms of urban activity and furnishes estimates for several critical statistical measures needed for policy evaluation. Although a monocentric model may not allow detailed representation of urban activity, we show that our simple model nonetheless offers advantages for studying urban planning practices in developing nations in which the availability of statistical data is limited.

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