Interpretation of snow properties from imaging spectrometry
Interpretation of snow properties from imaging spectrometry
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DOI：
10.1016/j.rse.2007.07.029
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发表时间：
2009-09-01
影响因子：
13.5
通讯作者：
Painter, Thomas H.
中科院分区：
文献类型：
--
作者：
Dozier, Jeff;Green, Robert O.;Painter, Thomas H.
雪是自然界中最多彩的物质之一，但雪反射系数的大部分变化发生在0.8微米以外，而不是在可见光谱中。在这些波长中，反射率随着雪粒的演化和长大而急剧下降，而在可见光光谱中，雪的反射率被灰尘、藻类和煤烟等污染物降解。从成像光谱仪数据中，我们可以估计表层雪的粒度，从而得出光谱和宽带反照率。我们还可以估计每个像素被雪覆盖的比例，表层的液态水含量，以及吸收杂质造成的辐射强迫的量。对积雪覆盖面积和反照率的估计大大改进了空间分布的融雪模型的性能，该模型将净太阳辐射作为输入值，在入射太阳辐射高和温度低的地点和时间最显著。成像光谱仪数据的经验使积雪比例和反照率估计得以扩展到多光谱传感器，特别是MODIS，即中分辨率成像光谱仪。(C)2009 Elsevier Inc.保留所有权利。
Snow is among the most "colorful" materials in nature, but most of the variability in snow reflectance occurs beyond 0.8 mu m rather than in the visible spectrum. In these wavelengths, reflectance decreases dramatically as the snow grains evolve and grow, whereas in the visible spectrum snow reflectance is degraded by contaminants such as dust, algae, and soot. From imaging spectrometer data, we can estimate the grain size of the snow in the surface layer, and thereby derive spectral and broadband albedo. We can also estimate the fraction of each pixel that is covered by snow, the liquid water content in the surface layer, and the amount of radiative forcing caused by absorbing impurities. Estimates of fractional snow-covered area and albedo dramatically improve the performance of spatially distributed snowmelt models that include net solar radiation as an input value, most significantly in locations and at times where incident solar radiation is high and temperatures low. Experience with imaging spectrometer data has allowed extension of the fractional snow-cover and albedo estimates to multispectral sensors, particularly MODIS, the Moderate-Resolution Imaging Spectroradiometer. (C) 2009 Elsevier Inc. All rights reserved.