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A new viewpoint for understanding the urban expansion using impervious surface information, which is obtained using remote sensing imagery is presented. The purpose of this study is to understand and describe the urban expansion pattern with the view of impervious surfaces instead of the conventional view of land use/land cover. Six years’ worth of impervious surface data (1990–2009) of Guangzhou are extracted via linear spectral unmixing analysis methods and spatial and temporal characteristics are discussed in detail. The area, density, and gravity centers changes of the impervious surfaces are analyzed to explain internal/external urban expansion. Meanwhile, five landscape indexes, such as patch density, edge density, mean patch size, area-weighted, and fragmentation index, are utilized to describe landscape changes of Guangzhou in past 20 years, which are influenced deeply by the impervious surface expansion. In order to detail landscape changes, two transects corresponding to the two urban expansion directions are designed and five landscape metrics in these two transects are reported. Conclusions can be drawn and shown as following: (1) temporally, the area of impervious surfaces increases from 12,998 to 59,911 ha from 1990 to 2009. The amount of impervious surface varies in different periods. The annual growth rates of impervious surface area during 1990–1995, 1995–1998, and 1998–2000 are 10.16%, 11.61%, and 10.78%, respectively; (2) annual growth rates decrease from 10.78% (1998–2000) to 5.67% (2000–2003). Nevertheless, from 2003–2009, the annual growth rate has a slight increase compared to a former period. The rate is 5.91%; (3) spatially, gravity centers of medium and high percentage impervious surfaces migrate slightly; and (4) according to the gradient analysis in the two transects, it can be observed that the high percentage of impervious surface increases gradually in new city districts (from west to east and from south to north).

journal of applied remote sensing

Understanding spatial-temporal urban expansion pattern (1990–2009) using impervious surface data and landscape indexes: a case study in Guangzhou (China)