Estimation of Liquid Water Content of Snow Surface by Spectral Reflectance

被引:15
作者
Eppanapelli, Lavan Kumar [1 ]
Lintzen, Nina [2 ]
Casselgren, Johan [1 ]
Wahlin, Johan [3 ]
机构
[1] Lulea Univ Technol, Div Fluid & Expt Mech, S-97187 Lulea, Sweden
[2] Lulea Univ Technol, Div Min & Geotech Engn, S-97187 Lulea, Sweden
[3] Norwegian Univ Sci & Technol, Dept Civil & Transport Engn, NO-7491 Trondheim, Norway
关键词
PHASE FUNCTION; INDEX NDWI; WET SNOW; VEGETATION; FEATURES; SAR;
D O I
10.1061/(ASCE)CR.1943-5495.0000158
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
This study measures the spectral reflectance from snow with known liquid water content (LWC) in a climate chamber using two optical sensors, a near-infrared (NIR) spectrometer and a Road eye sensor. The spectrometer measures the backscattered radiation in the wavelength range of 920-1,650nm. The Road eye sensor was developed to monitor and classify winter roads based on reflected intensity measurements at wavelengths of 980, 1,310, and 1,550 nm. Results of the study suggest that the spectral reflectance from snow is inversely proportional to the LWC in snow. Based on the effect of LWC on the spectral reflectance, three optimum wavelength bands are selected in which snow with different LWCs is clearly distinguishable. A widely used remote sensing index known as the normalized difference water index (NDWI) is used to develop a method to estimate the surface LWC for a given snow pack. The derived NDWI values with respect to the known LWC in snow show that the NDWI is sensitive to the LWC in snow and that the NDWI and LWC are directly proportional. Based on this information, the NDWI is used to estimate the surface LWC in snow from measurements on a ski track using the Road eye sensor. The findings suggest that the presented method can be applied to estimate the surface LWC in order to classify snow conditions potentially for ski track and piste applications. (C) 2018 American Society of Civil Engineers.
引用
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页数:7
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