Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Validation of an Analytical Snow BRDF Model Using PARASOL Multi-Angular and Multispectral Observations

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Kokhanovsky, A.A. ; Inst. of Environ. Phys., Univ. of Bremen, Bremen, Germany ; Breon, F.-M.

We describe a two-parameter model for the reflectance of snow and test it against multispectral and multi-angular observations. The first parameter of the model is proportional to the effective snow grain size. The second parameter accounts for the impact of soot and other pollutants on snow absorption. The model is analytical and is easily inverted against a set of multispectral observations. To test the ability of the model to reproduce snow reflectance, we use a multispectral and multidirectional set of measurements acquired by the POLDER-3 instrument onboard the Polarization and Anisotropy of Reflectances for Atmospheric Sciences coupled with Observations from a Lidar (PARASOL) satellite. We selected pure snow targets over Greenland and Antarctica. The model reproduces the main features of the snow angular reflectance: 1) the snow reflectance generally decreases toward longer wavelengths, 2) the reflectance has maximum in the forward scattering direction at large view zenith angles, and 3) the reflectance variations in the perpendicular plane are small compared to those observed in the principal plane. The coefficient of correlation between the results of simulations and the measurements exceeds 85% in most of cases.

Published in:

Geoscience and Remote Sensing Letters, IEEE  (Volume:9 ,  Issue: 5 )