Abstract
The green vegetation fraction (GVF) and surface albedo are important land surface parameters often used for validation of climate and land surface models that are influenced largely by environmental gradients and human activities. In this study, fine resolution GVF and albedo values derived from Landsat Thematic Mapper/Enhanced Thematic Mapper Plus images from 1990 to 2000 were used to examine the relationship of both GVF and albedo values to the spatial gradients of parameters related to dramatic urbanization in the Greater Guangzhou metropolitan area, Guangdong Province, in South China. Moderate resolution GVF and albedo datasets derived from the MODIS Collection 5 product were used to analyze the seasonal variation of GVF and albedo with rapid urban expansion from 2001 to 2007. The results show that the shortwave albedo had a clear declining trend from the urban center to natural land in 1990. However, no obvious trend in shortwave albedo change was observed along urban–rural gradients caused by the expansion of low-albedo urban buildings and more heterogeneous land cover patterns in 2000. A threshold of GVF (~0.21) was estimated for determining the change of albedo associated with vegetation fraction. Vegetation cover modified by urban expansion changed surface reflectance and influenced the surface energy balance. It is suggested that a large portion of energy absorbed in an urban area is likely to be converted to thermal energy that heating up is near the surface and emitted as longwave radiation.
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Acknowledgments
This study was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDA05090200), the National Basic Research Program of China (2009CB723904), the Arid Science Project (IAM201212) and the National Natural Science Foundation of China (41201044). We thank the anonymous reviewers and the editor-in-chief for their constructive comments.
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Hou, M., Hu, Y. & He, Y. Modifications in vegetation cover and surface albedo during rapid urbanization: a case study from South China. Environ Earth Sci 72, 1659–1666 (2014). https://doi.org/10.1007/s12665-014-3070-7
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DOI: https://doi.org/10.1007/s12665-014-3070-7