Please use this identifier to cite or link to this item: http://hdl.handle.net/2122/1969
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dc.contributor.authorallBassani, C.; Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.authorallCuomo, V.; Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.authorallLanorte, V.; Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.authorallPignatti, S.; Laboratorio Aereo Ricerche Ambientali (LARA), IIA-CNR, Tor Vergata (RM), Italyen
dc.contributor.authorallTramutoli, V.; Dipartimento di Ingegneria e Fisica dell’Ambiente (DIFA), Università degli Studi della Basilicata, Potenza Italyen
dc.date.accessioned2006-12-07T14:40:01Zen
dc.date.available2006-12-07T14:40:01Zen
dc.date.issued2006-02en
dc.identifier.urihttp://hdl.handle.net/2122/1969en
dc.description.abstractThe main objective of land remotely sensed images is to derive biological, chemical and physical parameters by inverting sample sets of spectral data. For the above aim hyperspectral scanners on airborne platform are a powerful remote sensing instrument for both research and environmental applications because of their spectral resolution and the high operability of the platform. Fine spectral information by MIVIS (airborne hyperspectral scanner operating in 102 channels ranging from VIS to TIR) allows researchers to characterize atmospheric parameters and their effects on measured data which produce undesirable features on surface spectral signatures. These effects can be estimated (and remotely sensed radiances corrected) if atmospheric spectral transmittance is known at each image pixel. Usually ground-based punctual observations (atmospheric sounding balloons, sun photometers, etc.) are used to estimate the main physical parameters (like water vapor and temperature profiles) which permit us to estimate atmospheric spectral transmittance by using suitable radiative transfer model and a specific (often too strong) assumption which enable atmospheric properties measured only in very few points to be extended to the whole image. Several atmospheric gases produce observable absorption features, but only water vapor strongly varies in time and space. In this work the authors customize a self-sufficient «split-window technique» to derive (at each image pixel) atmospheric total columnar water vapor content (TWVC) using only MIVIS data collected by the fourth MIVIS spectrometer (Thermal Infrared band). MIVIS radiances have been simulated by means of MODTRAN4 radiative transfer code and the coefficients of linear regression to estimate TWVC from «split-windows» MIVIS radiances, based on 450 atmospheric water vapor profiles obtained by radiosonde data provided by NOAA\NESDIS. The method has been applied to produce maps describing the spatial variability of the water vapor columnar content along a trial scene. The procedure has been validated by means of the MIVIS data acquired over Venice and the contemporary radiosonde data. A discrepancy within 5% has been measured between the estimate of TWVC derived from the proposed self-sufficient split-window technique and the coincident radiosonde measurements. If confirmed by further analyses such a result will permit us to fully exploit MIVIS TIR capability to offer a more effective (at image pixel level) and self-sufficient (no ancillary observations required) way to obtain atmospherically corrected MIVIS radiances.en
dc.format.extent1009217 bytesen
dc.format.mimetypeapplication/pdfen
dc.language.isoEnglishen
dc.relation.ispartofseries1/49 (2006)en
dc.subjectradiative transfer codeen
dc.subjectwater vaporen
dc.subjectsplit windowsen
dc.subjectMIVISen
dc.subjectatmospheric correctionen
dc.titleAssessment of water vapor content from MIVIS TIR dataen
dc.typearticleen
dc.type.QualityControlPeer-revieweden
dc.subject.INGV04. Solid Earth::04.02. Exploration geophysics::04.02.99. General or miscellaneousen
dc.relation.referencesADLER-GOLDEN, S.M., M.W. MATTHEW, L.S. BERNSTEIN, R.Y. LEVINE, A. BERK, S.C. RICHTSMEIER, P.K. ACHARYA, G.P. ANDERSON, G. FELDE, J. GARDNER, M. HIKE, L.S. JEONG, B. PUKALL, J. MELLO, A. RATKOWSKI and H.-H. BURKE (1999): Atmospheric correction for shortwave spectral imagery based on MODTRAN4, SPIE Proc., 3753, 61-69. AIG (2001): ACORN User’s Guide, Stand Alone Version, Analytical Imaging and Geophysics (AIG), LLC, p. 64. BERK, A., L.S. BERNSTEIN and D.C. ROBERTSON (1989): MODTRAN: a moderate resolution model for LOWTRAN7, Rep. GL-TR-89-0122 (Air Force Geophys. Lab., Bedford, MA). CUOMO, V., V. TRAMUTOLI, N. PERGOLA, C. PIETRAPERTOSA and F. ROMANO, (1997): In place merging of satellite based atmospheric water vapor measurements, Int. J. Remote Sensing, 18 (17), 3649-3668. GAO, B.-C. and A.F.H. GOETZ (1990): Column atmospheric water vapor and vegetation liquid water retrievals from airborne imaging spectrometer data, J. Geophys. Res. Atmos., 95 (D4), 3549-3564. JEDLOVEC, G.J. (1990): Precipitable water estimation from high-resolution split window radiance measurements, J. Appl. Meteorol. , 29, 851-865. KLEESPIES, T.J. and L.M. MCMILLIN (1984): Physical retrieval of precipitable water using split window technique, in Preprints Conf. On Satellite Meteorology/Remote Sensing and Applications, AMS, Boston, 55-57. MENZEL, W.P. and L.E. GUMLEY (1998): MODIS Atmospheric profile retrieval - Algorithm Theoretical Basis Document, ATBD-MOD-07 (University of Wisconsin, Madison). OTTLE, C., S. OUTALHA, C. FRANCOIS and S. LEMAGUER, (1997): Estimation of total atmospheric water vapor from split-window radiance measurements, Remote Sensing Environ., 61 (3), pp.410-418. TANRÉ, D., C. DEROO, P. DUHAUT, M. HERMAN, J.J. MORCHRETTE, J. PERBOS and P.Y. DESCHAMPS (1986): Simulation of the Satellite Signal in the Solar Spectrum (5S), Users’s Guide (U.S.T. de Lille, 59655 Villeneuve d’Ascq, France: Laboratoire d’Optique Atmospherique).en
dc.description.journalTypeJCR Journalen
dc.description.fulltextopenen
dc.contributor.authorBassani, C.en
dc.contributor.authorCuomo, V.en
dc.contributor.authorLanorte, V.en
dc.contributor.authorPignatti, S.en
dc.contributor.authorTramutoli, V.en
dc.contributor.departmentIstituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.departmentIstituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.departmentIstituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italyen
dc.contributor.departmentLaboratorio Aereo Ricerche Ambientali (LARA), IIA-CNR, Tor Vergata (RM), Italyen
dc.contributor.departmentDipartimento di Ingegneria e Fisica dell’Ambiente (DIFA), Università degli Studi della Basilicata, Potenza Italyen
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.cerifentitytypePublications-
item.fulltextWith Fulltext-
item.openairetypearticle-
item.grantfulltextopen-
crisitem.author.deptIstituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy-
crisitem.author.deptDipartimento di Ingegneria e Fisica dell'Ambiente, Università della Basilicata, Potenza, Italy-
crisitem.author.deptIstituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy-
crisitem.author.deptLaboratorio Aereo Ricerche Ambientali (LARA), IIA-CNR, Tor Vergata (RM), Italy-
crisitem.author.deptDipartimento di Ingegneria e Fisica dell’Ambiente, Università degli Studi della Basilicata, Italy-
crisitem.classification.parent04. Solid Earth-
Appears in Collections:Annals of Geophysics
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