Remote sensed high resolution images for cartographic updating (Contributo in atti di convegno)

Type
Label
  • Remote sensed high resolution images for cartographic updating (Contributo in atti di convegno) (literal)
Anno
  • 2003-01-01T00:00:00+01:00 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
  • 10.1109/DFUA.2003.1219998 (literal)
Alternative label
  • C. Tarantino, A, D'Addabbo, G. Pasquariello, P. Blonda, G. Satalino, L. Castellana (2003)
    Remote sensed high resolution images for cartographic updating
    in 2nd GRSS/ISPRS Joint Workshop on Remote Sensing and Data Fusion over Urban areas, Berlino (Germania)
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • C. Tarantino, A, D'Addabbo, G. Pasquariello, P. Blonda, G. Satalino, L. Castellana (literal)
Pagina inizio
  • 249 (literal)
Pagina fine
  • 252 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
  • 2ND GRSS/ISPRS JOINT WORKSHOP ON REMOTE SENSING AND DATA FUSION OVER URBAN AREAS (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • ISSIA-CNR (literal)
Titolo
  • Remote sensed high resolution images for cartographic updating (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
  • 0-7803-7719-2 (literal)
Abstract
  • Problems related to rapid transformation of land-use have reached a significant impact level. Photo interpretation by human experts has been the major data source for disasters' monitoring and urban planning applications. However, images collected from a sensor which combines reasonably good spectral and spatial resolution images acquired by IKONOS II satellite and a RGB-HIS transformation technique have been considered to merge spectral and spatial information. Then, textural information, which characterizes urban area, has been extracted with the use of an appropriate filter for edge extraction. An MLP classifier has been trained to produce a labeled image with great accuracy in test even if a limited training set has been used. For a photo interpreter, the results reveal a good feasibility of the classified image for monitoring the presence of changes in urban areas, useful for cartographic updating. (literal)
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