Download presentation
Presentation is loading. Please wait.
Published byAudrey Parker Modified over 7 years ago
1
Remote sensing of snow in visible and near-infrared wavelengths
3/28/2012 Remote sensing of snow in visible and near-infrared wavelengths Jeff Dozier – UCSB NASA Snow Remote Sensing Workshop Boulder, August 2013 ESM 236: Remote sensing of snow
2
Different concepts in different parts of spectrum
Visible, near-infrared, and infrared Independent scattering Weak polarization Scalar radiative transfer Penetration near surface only ~0.3 m in blue, few mm in NIR and IR Small dielectric contrast between ice and water Microwave and millimeter wave Extinction per unit volume Polarized signal Vector radiative transfer Large penetration in dry snow, many m Effects of microstructure and stratigraphy Small penetration in wet snow Large dielectric contrast between ice and water
3
Optical properties of ice & water — visible and near-infrared wavelengths
(Warren, Applied Optics, 1982) wavelength, m
4
N=n+ik, Index of refraction (complex)
dx I0 I
5
Basic scattering properties of a single grain
Mie theory, based on N and x=2r/ — single-scattering albedo g — asymmetry parameter Qext— extinction efficiency
6
Snow is a collection of scattering grains
7
Snow spectral reflectance and absorption coefficient of ice
8
Spectra with 7 MODIS “land” bands (500m resolution, global daily coverage)
9
Landsat Thematic Mapper (TM, on Landsats 4,5,7)
30 m spatial resolution 185 km FOV 16 day repeat pass Landsat 8 launched in February 2013
10
Landsat snow-cloud discrimination
Bands (V,nIR,swIR) Bands (visible) Benefit of shortwave-infrared Landsat snow-cloud discrimination
11
MODIS: similar bands, wider swath (2300 km), bigger pixels (500 m), daily coverage
12
Snow cover from MODIS
13
Comparison of MODIS (500m) and Landsat (30m) fSCA
32 scenes with coincident MODIS and Landsat images Average RMSE = 7.8% Range from 2% to 12%
14
Cloudy, 20%-80% depending on where/when
Similar presentations
© 2025 SlidePlayer.com. Inc.
All rights reserved.