文摘
The rates of urbanization and increase in urban sprawl that have occurred in China over the past thirty years have been unprecedented. This article presents a new city-scale dasymetric modelling approach that incorporates historical census data for 28 cities in the Pearl River Delta area of southern China. It combines Landsat imagery (from 2000, 2005, 2010, and 2015) with a ‘limiting variable’ estimation algorithm to generate a gridded estimate of population density. These gridded population patches are organized as a city-network to reveal the influence of urban agglomeration on population spreading processes. We then combine population patches and graph-based connectivity metrics to describe the spatial-temporal evolution of each city within the urban agglomeration. Our population disaggregation results yield accuracy improvements of 40%–60% over three traditional population disaggregation methods, to reflect the population distribution characteristics more explicitly and in greater detail. The probability of connectivity metrics from dasymetric population maps in Pearl River Delta (1) outline the role of urban agglomeration in population spread, (2) simulate the evolution of ‘polycentric’ urban agglomeration, and (3) outline the individual components of the polycentric megaregion. Our outlined approach is a transferable and an improved means of producing city-scale dasymetric population maps. Our case study provides practical guidance on wide applications of the medium resolution remote sensing data in delineating, measuring, and quantifying the evolution of urban agglomeration across different jurisdictional boundaries and time periods.
