Abstract
Accurate mapping of urban land cover from satellite data provides essential input to urban landscape analysis, modelling and urban ecosystem studies. Additionally, analysis of urban landscape metrics will provide a positive step towards comprehensive understanding of the features of urban landscape structure and further planning. In the present study, multi-spectral Advanced Land Observing Satellite (ALOS)/Advanced Visible and Near Infrared Radiometer type 2 (AVNIR-2) images and ALOS/Phased Array type L-band Synthetic Aperture Radar (PALSAR) dual-polarized (FBD) microwave images were used to extract urban land cover information by applying the decision tree method, and additional Advanced Space borne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER/GDEM) was used to reduce the effects of mountains in Synthetic Aperture Radar (SAR) images due to high backscattering from urban construction land. A set of landscape metrics, such as landscape diversity, edge density and landscape shape indices with supplementary ecological meanings, were chosen to quantitatively analysis urban landscape patterns in arid environments. The overall accuracy assessment result was 91.50%, and the experimental results demonstrate that synergetic use of optical and SAR ALOS data has the potential and advantages for Arid Urban Region mapping, while the decision tree method showed intuitive simplicity and computational efficiency. The quantitative analysis results of landscape metrics showed that distribution of landscape types in Urumqi city were inhomogeneous, the urban landscape dominated by a few classes. Urbanization in this region has resulted in dramatic increases in patch density (PD), edge density (ED) and landscape shape complexity.
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