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. Piscataway, USA, Institute of Electrical and Electronics Engineers, 116-121.
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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
|Item Type:||Book Section|
|Subjects:||T Technology > T Technology (General)
G Geography. Anthropology. Recreation > G Geography (General)
Q Science > QA Mathematics > QA76 Computer software
|Divisions :||University Structure - Pre August 2011 > School of Engineering Sciences
|Accepted Date and Publication Date:||
|Date Deposited:||14 Feb 2007|
|Last Modified:||31 Mar 2016 11:44|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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