摘要
采用线性光谱混合分解和最大似然分类相结合的方法,对宁夏红寺堡灌区开发前1989年的土地覆被状况进行分类。分类时,以基准端元为分类特征,分类函数稳定,分类结果易于解释。研究结果表明,基于混合像元分解丰度图的最大似然分类总体精度为77.53%,比应用原始影像直接进行最大似然分类的总体精度提高了9.8%。同时,为提高分类精度,本研究对分类结果进行了分类后处理以满足实际需求。
This paper deals with the land cover classification of the Hongsipu Irrigation Area in Ningxia in 1989 based on remote sensing techniques, serving as a benchmark for the study of the development zones. Reference end - members were used as the characteristics of classification with which the classification function was stable and the results of classification were easily to explain. The results show that the overall accuracy of maximum likelihood classification based on abundance maps derived from the decomposition of mixed pixels is 77.53%. Compared with the maximum likelihood classification based on original image, the overall accuracy is raised by 9.8%. Therefore, the combination of the linear spectral mixture decomposition model and the maximum likelihood classification constitutes a good classification method. In order to improve the classification accuracy, this paper makes a post - processing on the classification results to meet the actual demand.
出处
《国土资源遥感》
CSCD
2010年第1期96-100,共5页
Remote Sensing for Land & Resources
关键词
混合像元
线性混合分解模型
最大似然分类
端元
主成分分析
Mixed - pixel
Decomposition of linear mixed model
Maximum likelihood classification
End - mem- bers
PCA
