Cloud classification using support vector machines

Author

Azimi-Sadjadi, M.R. ; Zekavat, S.A.

Author_Institution

Dept. of Electr. & Comput. Eng., Colorado State Univ., Fort Collins, CO, USA

Volume

2

fYear

2000

fDate

2000

Firstpage

669

Abstract

Cloud classification from GOES 8 (Geostationary Operational Environmental Satellite) imagery data is performed using the infrared (IR) channel only. For each block of the image, first and second order statistics are extracted and used to train and test a classifier. In this paper, cloud classification is performed using a support vector machine (SVM) classifier. This scheme, which is typically used to solve two-class problems, has been extended to classify ten different cloud and no-cloud areas. Preliminary results indicate the promise of this method for meteorological applications

Keywords

atmospheric techniques; clouds; geophysical signal processing; geophysics computing; image classification; GOES 8; atmosphere; classifier; cloud; cloud classification; computing; image classification; image processing; infrared; measurement technique; meteorology; optical imaging; satellite remote sensing; support vector machine; Brightness; Clouds; Data mining; Feature extraction; Meteorology; Neural networks; Risk management; Satellites; Support vector machine classification; Support vector machines;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium, 2000. Proceedings. IGARSS 2000. IEEE 2000 International

Conference_Location

Honolulu, HI

Print_ISBN

0-7803-6359-0

Type

conf

DOI

10.1109/IGARSS.2000.861666

Filename

861666