Automatic classification algorithm for NOAA-AVHRR data using mixels

被引：2

作者：

Kageyama, Yoichi ^{[1
]}

Sato, Ikuma ^{[1
]}

Nishida, Makoto ^{[1
]}

机构：

[1] Akita Univ, Fac Engn & Resource Sci, Dept Comp Sci & Engn, Akita 0108502, Japan

来源：

IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET | 2007年

关键词：

NOAA; mixel; NDVI; fuxxy reasoning; edge;

D O I：

10.1109/IGARSS.2007.4423232

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

This study proposes an automatic classification algorithm for NOAA (National Oceanic and Atmospheric Administration)-AVHRR (Advanced Very High Resolution Radiometer) data using mixels. The proposed algorithm uses the properties of the NOAA-AVHRR multispectral bands, the mixels, and the NDVI (normalized difference vegetation index) to estimate the actual conditions. This study suggests that the proposed approach provides reasonable results as compared to those of maximum likelihood estimation and k-means clustering.

引用

页码：2040 / 2043

页数：4

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