http://www.cnr.it/ontology/cnr/individuo/prodotto/ID30746
Assessment of water vapor content from MIVIS TIR data (Articolo in rivista)
- Type
- Label
- Assessment of water vapor content from MIVIS TIR data (Articolo in rivista) (literal)
- Anno
- 2006-01-01T00:00:00+01:00 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Bassani Cristiana (1); Cuomo Vincenzo (1); Lanorte Vito (1); Pignatti Stefano (1,2); Tramutoli Valerio (3); (literal)
- Pagina inizio
- Pagina fine
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- Rivista
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- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- (1) Istituto di Metodologie per l'Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy;
(2) Laboratorio Aereo Ricerche Ambientali (LARA), IIA-CNR, Tor Vergata (RM), Italy;
(3) Dipartimento di Ingegneria e Fisica dell'Ambiente (DIFA), Università degli Studi della Basilicata, Potenza Italy; (literal)
- Titolo
- Assessment of water vapor content from MIVIS TIR data (literal)
- Abstract
- The 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 hyperspec-
tral scanner operating in 102 channels ranging from VIS to TIR) allows researchers to characterize atmospher-
ic parameters and their effects on measured data which produce undesirable features on surface spectral signa-
tures. These effects can be estimated (and remotely sensed radiances corrected) if atmospheric spectral trans-
mittance is known at each image pixel. Usually ground-based punctual observations (atmospheric sounding bal-
loons, sun photometers, etc.) are used to estimate the main physical parameters (like water vapor and tempera-
ture profiles) which permit us to estimate atmospheric spectral transmittance by using suitable radiative trans-
fer 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-suf-
ficient «split-window technique» to derive (at each image pixel) atmospheric total columnar water vapor con-
tent (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 pro-
duce maps describing the spatial variability of the water vapor columnar content along a trial scene. The pro-
cedure 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. (literal)
- Prodotto di
- Autore CNR
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