Cloud detection and classification from multi-spectral satellite data

dc.contributor.authorCosta, Maria João
dc.contributor.authorBortoli, Daniele
dc.date.accessioned2012-11-14T16:13:48Z
dc.date.available2012-11-14T16:13:48Z
dc.date.issued2009
dc.description.abstractClouds are the major factor regulating the Earth radiation budget, therefore their detection and characterization is of major importance. Cloud detection and classification is a requirement in order to allow for accurate studies of cloud microphysical and optical properties, as well as subsequent assessment of their radiative effects. In the present work, a method for the detection and classification of clouds, over the Iberian Peninsula, is presented. The methodology developed relies on the use of Meteosat-8 satellite images in different spectral bands combined to form different color composites, which are then analyzed, in an unsupervised way. The results show that more features are distinguished in the cloud mask, with respect to the use of traditional methods.por
dc.identifier.authoremailmjcosta@uevora.pt
dc.identifier.authoremaildb@uevora.pt
dc.identifier.citationCosta, M. J. and D. Bortoli, "Cloud detection and classification from multi-spectral satellite data", Proc. SPIE 7475, Remote Sensing of Clouds and the Atmosphere XIV, 747514 (September 29, 2009); doi:10.1117/12.830220por
dc.identifier.doi10.1117/12.830220
dc.identifier.scientificarea244por
dc.identifier.sharewithFIS - Artigos em Livros de Actas/Proceedingspor
dc.identifier.urihttp://hdl.handle.net/10174/5594
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherSPIE - International Society for optics and Photonicspor
dc.rightsrestrictedAccesspor
dc.subjectCloudspor
dc.subjectSatellitepor
dc.titleCloud detection and classification from multi-spectral satellite datapor
dc.typearticlepor

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
2009_Costa_Bortoli_SPIE.pdf
Size:
3.54 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
3.89 KB
Format:
Item-specific license agreed upon to submission
Description: