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Optical Remote Sensing for Monitoring Evolution of Ablation Season Mountain Snow Cover

机译:光学遥感监测消融季节高山积雪的演变

摘要

The investigations contained in this body of work detail a viable proof-of-concept model for monitoring seasonal snow pack propensity for melt release based on time-variant snow surface optical and thermal properties. The model has been called the Near Surface Moisture Index- (Snow) (NSMI). The NSMI was developed based on time-variant snow surface optical and thermal properties. This research achieved three primary objectives: 1).development of theoretical foundation and surface moisture sensitive algorithm used to track both surface melt and pack discharge potential; 2.) time-dependent phases of coupling and decoupling between snow surface properties and melt discharge were characterized through analysis of long-term surface and sub-surface state variables; 3.) and sensitivity of optical satellite systems specifically, EOS TERRA-MODIS, to melting were was examined through radiative transfer simulations. Simulated at-sensor radiance was produced for various grain size changes to determine MODIS capacity to track melt onset. MODIS wavelengths greater than 667nm were sensitive to large changes in grain sizes, particularly bands with coarse spatial resolution (1000m). Longer wavelengths showed greater sensitivity to small changes in smaller grains than to small changes in larger grains. Shorter wavelengths at 500m spatial resolution appeared less effective overall for monitoring changes in grain size. NMSI feature space using Normalized Difference Snow Index (NDSI) on the abscissa and brightness temperature (Tb) on the ordinate was simulated. Simulated NDSI as a function of grain radius saturated approximately around 400-450 μm. ASTER derived NSMI demonstrated behavior consistent with simulations with deviations due to topography, vegetation, and regional heterogeneity. We examined NSMI performance during an entire melt season through tracking phases of coupling between snow surface properties and propensity for melt using two ground-base approaches; one with higher snow surface spectral information and low temporal resolution, the other with high temporal resolution and coarse spectral information. Phases of decoupling exhibited within ground-based time varying simulated NSMI were regulated by the temporal resolution specified to construct the feature space. Coarser temporal intervals on surface optical/thermal variables correlated the NSMI feature space various components of surface radiative variability. Coarser temporal optical and thermal resolution will tend to reduce variability within the NSMI feature space due to specific snowfall events.
机译:这项工作中包含的调查详细说明了一个可行的概念验证模型,该模型可根据随时间变化的雪表面光学和热特性来监测季节性积雪的融雪释放倾向。该模型被称为近表面水分指数(雪)(NSMI)。 NSMI是根据时变雪表面的光学和热学性质开发的。这项研究达到了三个主要目的:1)。开发可追踪表面融化和堆积放电潜能的理论基础和表面湿度敏感算法; 2.)通过分析长期的表面和亚表面状态变量,表征了雪表面特性与融雪排放之间耦合和解耦的时间相关阶段; 3.)通过辐射传输模拟检查了光学卫星系统,特别是EOS TERRA-MODIS,对融化的敏感性。针对各种晶粒尺寸变化产生了模拟的传感器辐射,以确定MODIS追踪熔体开始的能力。大于667nm的MODIS波长对晶粒尺寸的大变化敏感,特别是具有较粗的空间分辨率(1000m)的波段。较长的波长显示出对较小晶粒的细微变化比对较大晶粒的细微变化更敏感。在500m空间分辨率下,较短的波长对于监测晶粒尺寸的变化总体而言似乎不太有效。使用横坐标上的归一化差异雪指数(NDSI)和纵坐标上的亮度温度(Tb)来模拟NMSI特征空间。模拟的NDSI作为晶粒半径的函数,大约在400-450μm左右饱和。 ASTER得出的NSMI表现出的行为与模拟一致,但由于地形,植被和区域异质性而产生偏差。我们通过跟踪雪表面特性和融化倾向之间的耦合阶段,使用两种地基方法检查了整个融化季节的NSMI性能。一个具有较高的雪面光谱信息和较低的时间分辨率,另一个具有较高的时间分辨率和较粗糙的光谱信息。通过指定构造要素空间的时间分辨率来调节基于地面的时变模拟NSMI中显示的解耦阶段。表面光学/热变量上较粗的时间间隔与NSMI特征空间的表面辐射变异性的各个组成部分相关。由于特定的降雪事件,较粗的时间光学和热分辨率将趋于减少NSMI特征空间内的可变性。

著录项

  • 作者

    Lampkin Derrick Julius;

  • 作者单位
  • 年度 2005
  • 总页数
  • 原文格式 PDF
  • 正文语种 EN
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