Classification of clouds in the Japan Sea area using NOAA AVHRR satellite images and self-organizing map

Author

Kubo, Mamoru ; Muramoto, Ken-ichiro

Author_Institution

Kanazawa Univ., Kanazawa

fYear

2007

fDate

23-28 July 2007

Firstpage

2056

Lastpage

2059

Abstract

This paper introduces a method for cloud classification using NOAA AVHRR satellite images. AVHRR (Advanced Very High Resolution Radiometer) data consists of five-channel multi-spectral images. To reduce the dimensionality of the data, principal component analysis (PCA) is calculated for each channel separately. The most significant principal component values are then composed into an image feature vector. Finally, the feature vectors are clustered using self-organizing map (SOM). This method is applied for the study of winter season clouds in the Japan Sea area.

Keywords

artificial satellites; atmospheric techniques; clouds; geophysical signal processing; image classification; pattern clustering; principal component analysis; radiometers; self-organising feature maps; Advanced Very High Resolution Radiometer; Japan sea; NOAA AVHRR satellite image; PCA; cloud classification; data dimensionality reduction; five channel multispectral image; image feature vector clustering; principal component analysis; self organizing map; Bandwidth; Clouds; Clustering methods; Electronic mail; Image databases; Image resolution; Infrared imaging; Multispectral imaging; Principal component analysis; Satellite broadcasting; AVHRR; Satellite images; image clustering; principal component analysis; self-organizing map;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International

Conference_Location

Barcelona

Print_ISBN

978-1-4244-1211-2

Electronic_ISBN

978-1-4244-1212-9

Type

conf

DOI

10.1109/IGARSS.2007.4423236

Filename

4423236