融入空间信息的湿地信息提取技术

以安徽省湿地为对象,采用TM影像,在去噪声处理和主成分分析的基础上,以一种基于光谱和空间信息相结合的分类方法,对研究区的湿地信息进行了提取。结果表明:以主成分分析法对数据进行处理发现,前4个主成分的累积贡献率为99.5%,可代表原始数据的绝大部分信息; 结合空间信息的提取方法对各类型湿地的平均提取精度可达84.6%,有效地改善了“麻点”现象,而采用光谱信息的平均提取精度仅为69.3%。

Wetland information extraction technology integrated by spatial information

The wetlands in Anhui province were taken as research object, a method of classification based on spectral and spatial information was applied to extract wetland information in the study area, based on the TM image removed noise and principal component analysis. The results indicated that the accumulated contribution rate of the first four principal components was 99.5%, which could represent most of the original data information. The average classification accuracy of wetland information extraction technology integrated by spatial information was 84.6%, while the average classification accuracy of maximum likelihood method was only 69.3%. The wetland classification method of combining spatial information could effectively weaken the noises and improve a certain extent classification. This study has certain reference value on the other related research of wetland remote sensing information extraction based on spatial information.