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  5. Assessment of water vapor content from MIVIS TIR data
 
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Assessment of water vapor content from MIVIS TIR data

Author(s)
Bassani, C.  
Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy  
Cuomo, V.  
Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy  
Lanorte, V.  
Istituto di Metodologie per l’Analisi Ambientale (IMAA), CNR, Tito Scalo (PZ), Italy  
Pignatti, S.  
Laboratorio Aereo Ricerche Ambientali (LARA), IIA-CNR, Tor Vergata (RM), Italy  
Tramutoli, V.  
Dipartimento di Ingegneria e Fisica dell’Ambiente (DIFA), Università degli Studi della Basilicata, Potenza Italy  
Date Issued
February 2006
Issue/vol(year)
1/49 (2006)
Language
English
Subjects
04. Solid Earth::04.02. Exploration geophysics::04.02.99. General or miscellaneous  
URI
https://www.earth-prints.org/handle/2122/1969
Subjects

radiative transfer co...

water vapor

split windows

MIVIS

atmospheric correctio...

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 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.
References
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(5S), Users’s Guide (U.S.T. de Lille, 59655 Villeneuve
d’Ascq, France: Laboratoire d’Optique Atmospherique).
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