Fuzzy ARTMAP算法在城市不透水面估算中的应用研究
Estimating Impervious Surfaces Using the Fuzzy ARTMAP
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摘要: 为了克服线性光谱混合分析模型的缺陷,兼顾Landsat ETM+和Quickbird遥感数据多源信息及Fuzzy ARTMAP神经网络自适应学习的优势,提出了利用Fuzzy ARTMAP方法来估算城市不透水面覆盖度(ISP)。以武汉市为例,结果表明,与线性光谱混合分析模型相比,基于Fuzzy ARTMAP神经网络方法估算结果精度较高,与实际城市不透水面覆盖度分布范围一致。Abstract: Impervious surface is a significant indictor in monitoring eco-environmental health.In linear spectral mixture analysis(LSMA) model,four endmembers are selected.Low albedo and high albedo,the factor of impervious surface are hard to obtain precisely.In order to overcome the flaw of LSMA,fuzzy ARTMAP was proposed to estimate the percent of impervious surface(ISP).The method included the multi-resource information from Landsat ETM+ and Quickbird and the superiority of auto-adapted of Fuzzy ARTMAP neural network.Taking the city of Wuhan in Hubei province as the example,the result showed that the precision of ISP estimated by fuzzy ARTMAP was higher than that of LSMA.The distribution of impervious surface obtained by fuzzy ARTMAP was consistent with the actual land surface.