Multi-spectral and multitemporal MODIS remote sensing imagery classification based on MNF transform and grayscale morphological filter in Sanjiang plain

被引：0

作者：

Liu, Hanli ^{[1
]}

Pei, Tao ^{[2
]}

Zhou, Chenghu ^{[2
]}

Zhu, Axing ^{[2
]}

机构：

[1] College of Automobile and Traffic Engineering, Wuhan University of Science and Technology, 947 Heping Road, Wuhan 430081, China

[2] State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural, Chinese Academy of Sciences, Beijing 100101, China

来源：

Wuhan Daxue Xuebao (Xinxi Kexue Ban)/Geomatics and Information Science of Wuhan University | 2011年 / 36卷 / 02期

关键词：

Data handling - Image classification - Bandpass filters - Land use - Radiometers;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

By analyzing spectral characteristics and phenological characteristics of remote sensing images, we select multi-temporal NDVI data along with other useful bands for data processing. By performing an enhanced Lee filter and MNF transform on the data, the features of different land use types has been enhanced. Then, a morphological filtering is conducted on the data to extract dry land. Finally, we separate wetland and paddy field by a SOM neural network clustering. As a result, the accuracy of land use type classification has been improved.

引用

页码：153 / 156

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