Name:CIS (GISELA)
Description:Classification of Satellite Images with neural networks
Abstract:Remote sensing is a very used technique to obtain data of the Earth surface without making contact with it. In general, data is gathered through airbone platforms or artificial satellites. These catch the signals emitted by the objects in the surface producing a spectral company/signature, which makes those objects distinguishable from others.<BR/>Remote sensing has provided the information necessary to realise the study in different areas like: cartography, GIS, environment management, local development and urbanism, public agriculture, work and service, telecommunication, transport, etc.<BR/>The processing of satellite images in the department of GIS-UTPL has been a frequent problem because the response times are very slow and this leads to unnecessary expenditure of resources both material and human. For this reason we propose to develop a solution based on distributed environments which will improve response times and optimize resources demand that the analysis of satellite images based on neural networks. The results of this application will be used by 100 researchers from the UTPL working the area of earth sciences.
Created:2011-05-06
Last updated:2011-05-06
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