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    Optical Remote Sensing Of Snow On Sea Ice: Ground Measurements, Satellite Data Analysis, And Radiative Transfer Modeling

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    Author
    Zhou, Xiaobing
    Chair
    Li, Shusun
    Committee
    Stamnes, Knut
    Sharpton, Buck
    Jeffries, Martin O.
    Echelmeyer, Keith
    Keyword
    Geophysics
    Hydrologic sciences
    Remote sensing
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/11122/8638
    Abstract
    The successful launch of the Terra satellite on December 18, 1999 opened a new era of earth observation from space. This thesis is motivated by the need for validation and promotion of the use of snow and sea ice products derived from MODIS, one of the main sensors aboard the Terra and Aqua satellites. Three cruises were made in the Southern Ocean, in the Ross, Amundsen and Bellingshausen seas. Measurements of all-wave albedo, spectral albedo, BRDF, snow surface temperature, snow grain size, and snow stratification etc. were carried out on pack ice floes and landfast ice. In situ measurements were also carried out concurrently with MODIS. The effect of snow physical parameters on the radiative quantities such as all-wave albedo, spectral albedo and bidirectional reflectance are studied using statistical techniques and radiative transfer modeling, including single scattering and multiple scattering. The whole thesis consists of six major parts. The first part (chapter 1) is a review of the present research work on the optical remote sensing of snow. The second part (chapter 2) describes the instrumentation and data-collection of ground measurements of all-wave albedo, spectral albedo and bidirectional reflectance distribution function (BRDF) of snow and sea ice in the visible-near-infrared (VNIR) domain in Western Antarctica. The third part (chapter 3) contains a detailed multivariate correlation and regression analysis of the measured radiative quantities with snow physical parameters such as snow density, surface temperature, single and composite grain size and number density. The fourth part (chapter 4) describes the validation of MODIS satellite data acquired concurrently with the ground measurements. The radiances collected by the MODIS sensor are converted to ground snow surface reflectances by removing the atmospheric effect using a radiative transfer algorithm (6S). Ground measured reflectance is corrected for ice concentration at the subpixel level so that the in situ and space-borne measured reflectance data are comparable. The fifth part (chapter 5) investigates the single scattering properties (extinction optical depth, single albedo, and the phase function or asymmetry factor) of snow grains (single or composite), which were calculated using the geometrical optical method. A computer code, GOMsnow, is developed and is tested against benchmark results obtained from an exact Mie scattering code (MIE0) and a Monte Carlo code. The sixth part (chapter 6) describes radiative transfer modeling of spectral albedo using a multi-layer snow model with a multiple scattering algorithm (DISORT). The effect of snow stratification on the spectral albedo is explored. The vertical heterogeneity of the snow grain-size and snow mass density is investigated. It is found that optical remote sensing of snow physical parameters from satellite measurements should take the vertical variation of snow physical parameters into account. The albedo of near-infrared bands is more sensitive to the grain-size at the very top snow layer (<5cm), while the albedo of the visible bands is sensitive to the grain-size of a much thicker snow layer. Snow parameters (grain-size, for instance) retrieved with near-infrared channels only represent the very top snow layer (most probably 1--3 cm). Multi-band measurements from visible to near-infrared have the potential to retrieve the vertical profile of snow parameters up to a snow depth limited by the maximum penetration depth of blue light.
    Description
    Dissertation (Ph.D.) University of Alaska Fairbanks, 2002
    Date
    2002
    Type
    Dissertation
    Collections
    Geosciences

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