Translator Disclaimer
22 December 2006 Analysis of urban reflectance and urban sprawl in China using TM/ETM+ imagery
Author Affiliations +
The future world is a world of city. Spectral characterization of urban reflectance is important. The overall reflectance of the urban mosaic is determined by the spectral reflectance of surface materials and shadows and their spatial distribution. Building materials dominate net reflectance in most cities but in many cases vegetation also has a very strong influence on urban reflectance. In the study, the spectral characterization of urban reflectance properties is analyzed using Landsat TM and ETM+ imagery of a collection of the province capital city in China. The result shows these urban areas have similar mixing space topologies and can be represented by three-component linear mixture models The reflectance of these cities can be described as linear combinations of High Albedo, Dark and Vegetation spectral endmembers within a three dimensional mixing space containing over 80% of the variance in the observed reflectance. The relative proportions of these endmembers vary considerably among different cities but in all cases the reflectance of the urban core lies near the dark end and the new build-up areas near the light end of a mixing line between the High Albedo and Dark endmembers. In spite of the spectral heterogeneity, built-up areas do occupy distinct regions of the spectral mixing space. Based on the above analyzation, the urban spatial extent of 34 cities of China, representing the physical manifestation of a range of social, economic, cultural, and political dimensions associated with urban dynamics, was mapped using Landsat imagery collected of 1990 and 2000.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hongen Zhang, Yanling Qiu, Ling Chen, and Jianfu Zhao "Analysis of urban reflectance and urban sprawl in China using TM/ETM+ imagery", Proc. SPIE 6405, Multispectral, Hyperspectral, and Ultraspectral Remote Sensing Technology, Techniques, and Applications, 64051F (22 December 2006);

Back to Top