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。
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.
出处
《武汉大学学报（信息科学版）》
EI
CSCD
北大核心
2012年第10期1236-1239,共4页
Geomatics and Information Science of Wuhan University
基金
国家973计划资助项目(2009CB723905
2011CB707105)
国家自然科学基金资助项目(40771139
40523005)
中央高校基本科研业务费专项资金资助项目
