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A neural network approach to cloud classification from multi-temporal satellite imagery

Lewis, H.G., Cote, S. and Tatnall, A.R.L. (1995) A neural network approach to cloud classification from multi-temporal satellite imagery In Fourth International Conference on Artificial Neural Networks. Institute of Electrical and Electronics Engineers., pp. 116-121.

Record type: Conference or Workshop Item (Paper)

Abstract

In response both to the general lack of automatic methods to analyse the increasing amount of satellite data, and to the availability of multi-temporal information at high temporal resolution (e.g. Meteosat, 30 minutes), a new artificial neural network (ANN) method for classifying clouds has been developed. A recently developed cloud tracking method, utilising a Hopfield neural network, is used to acquire new dynamic cloud parameters from satellite image sequences. These parameters are analysed, and their contribution towards accurate classification is discussed

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More information

Published date: 1995
Venue - Dates: Fourth International Conference on Artificial Neural Networks, 1995-06-26 - 1995-06-28

Identifiers

Local EPrints ID: 23742
URI: http://eprints.soton.ac.uk/id/eprint/23742
ISBN: 0852966415
PURE UUID: 839177a8-7164-4d3b-85c6-a6143661e5b6

Catalogue record

Date deposited: 14 Feb 2007
Last modified: 17 Jul 2017 16:16

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