基于HJ-1数据和V-I-S模型的城市不透水层变化分析

An Analysis of Changes of Urban Impervious Surface Area Based on HJ-1 Multispectral Images and V-I-S Model

选择2008年和2010年徐州市城区的HJ-1A/1B多光谱遥感图像,利用线性光谱混合模型(LSMM)、多层感知器(MLP)神经网络和自组织映射(SOM)神经网络3种混合像元分解方法,基于V-I-S(植被-不透水层-土壤)模型提取城市不透水层。对3种方法的精度分析对比表明,MLP方法优于其他两种方法,能够比较清晰地反映出徐州市城市化的发展。对两个时相多光谱影像提取的不透水层信息的分析表明,徐州市近两年的发展中心已逐渐向城市边缘地带扩展,其主要原因在于经济的迅速增长和城市化进程的加速发展。

In order to promote the application of the remote sensing data of HJ-1A/1B small satellite to urbanization monitoring,the authors selected Xuzhou City as the study area and chose HJ-1A/1B multispectral remote sensing images acquired in 2008 and 2010 as the data sources.After mixed pixel decomposition,the urban impervious surfaces were extracted by Linear Spectral Mixture Model（LSMM）,Multiple Layer Perceptron（MLP） and Self-organizing Map（SOM） on the basis of V-I-S model.A comparison of the three methods through accuracy analysis shows that MLP is suitable for estimating the abundance of impervious surface area（ISA）from HJ-1 A/1B data,and ISA can clearly reflect the trends of urbanization.