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.
Full text not available from this repository.
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
|Date Deposited:||14 Feb 2007|
|Last Modified:||02 Mar 2012 11:26|
|Publisher:||Institute of Electrical and Electronics Engineers|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
Actions (login required)