Please use this identifier to cite or link to this item:
Statistical Atmospheric Parameter Retrieval Largely Benefits from Spatial-Spectral Image Compression
Full metadata record
DC FieldValueLanguage
dc.contributor.authorGarcía Sobrino, Joaquínes_ES
dc.contributor.authorSerra-Sagristà, Joanes_ES
dc.contributor.authorLaparra, Valeroes_ES
dc.contributor.authorCalbet, Xavieres_ES
dc.contributor.authorCamps-Valls, Gustaues_ES
dc.identifier.citationIEEE Transactions on Geoscience and Remote Sensing. 2017, 55(4), p. 2213-2224es_ES
dc.description.abstractThe Infrared Atmospheric Sounding Interferometer (IASI) is flying on board of the Metop satellite series, which is part of the EUMETSAT Polar System (EPS). Products obtained from IASI data represent a significant improvement in the accuracy and quality of the measurements used for meteorological models. Notably, IASI collects rich spectral information to derive temperature and moisture profiles –among other relevant trace gases–, essential for atmospheric forecasts and for the understanding of weather. Here, we investigate the impact of near-lossless and lossy compression on IASI L1C data when statistical retrieval algorithms are later applied. We search for those compression ratios that yield a positive impact on the accuracy of the statistical retrievals. The compression techniques help reduce certain amount of noise on the original data and, at the same time, incorporate spatial-spectral feature relations in an indirect way without increasing the computational complexity. We observed that compressing images, at relatively low bitrates, improves results in predicting temperature and dew point temperature, and we advocate that some amount of compression prior to model inversion is beneficial. This research can benefit the development of current and upcoming retrieval chains in infrared sounding and hyperspectral sensors.es_ES
dc.publisherInstitute of Electrical and Electronics Engineerses_ES
dc.rightsLicencia CC: Reconocimiento–NoComercial–SinObraDerivada CC BY-NC-NDes_ES
dc.subjectInfrared Atmospheric Sounding Interferometeres_ES
dc.subjectStatistical retrievales_ES
dc.subjectKernel Methodses_ES
dc.subjectNear-Lossless Compressiones_ES
dc.subjectLossy Compressiones_ES
dc.subjectJPEG 2000es_ES
dc.subjectSpectral Transformses_ES
dc.titleStatistical Atmospheric Parameter Retrieval Largely Benefits from Spatial-Spectral Image Compressiones_ES
Appears in Collections:Artículos científicos 2015-2018

Files in This Item:
  File Description SizeFormat 
1,32 MBAdobe PDFThumbnail
Show simple item record

Items in Arcimis are protected by Creative Commons License, unless otherwise indicated.

Arcimis Repository
Nota Legal Contacto y sugerencias