以厦门岛为研究区，以CBERS-02B的CCD影像为数据源，采用基于可变端元的线性光谱混合模型估算了城市不 透水面组分含量，并探讨了该方法的实现过程与优势。通过端元评估确定了研究区的４个典型端元，即高反射不透水 面、低反射不透水面、高反射土壤和植被。在此基础上，以高、低反射不透水面端元的组分含量对城市不透水面含量 进行估算。精度评价结果显示：基于可变端元的方法要优于一般带全约束法；而在混合像元分解过程中加入全色波段 （band5）有助于提高模型估算精度，使得在像元尺度的精度与采用Landsat的已有报道相近，而在土地利用单元尺度实 现了对城市不透水面的无偏估计。研究实例也表明，尽管目前CBERS-02B数据在辐射定标和地理定位等方面还有待改 进，通过采用适当的处理过程和技术手段，依然能利用该数据对城市不透水面进行有效估算。

At present, it has become one of the vital research topics to estimate the distribution of urban impervious surface (UIS) precisely and effectively using remote sensing technologies. In this paper, while Xiamen Island was taken as the study area, the selective endmember linear spectral mixture model (LSMM) was applied to model the UIS distribution using China Brazil Earth Resources Satellite-02B (CBERS-02B) CCD data, and its advantage was discussed. Four typical endmembers were selected including high albedo impervious surface (High Imp), low albedo impervious surface (Low Imp), high albedo soil (High Soil) and vegetation for this region, and the UIS fraction was estimated from the fractions of High Imp and Low Imp consequently. Validation results indicated that the selective endmember method was superior to the generally fully constrained (GFC) method in view of several error measurements, and the UIS estimation obtained by taking into account the panchromatic band (band5) was more precise compared to which obtained without it. Consequently, at pixel scale the accuracy of the modeled UIS fraction was parallel with others using Landsat images, while unbiased estimation was obtained at land use polygon scale. Accordingly, our experiments suggest that UIS can be accurately estimated by using CBERS-02B data through proper processing and effective approaches, in spite of its imperfections related to radiometric calibration and geographical registration,which need to be improved further.