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The estimation and scaling of land-surface fluxes of latent and sensible heat with remotely sensed data over a grassland site.

机译:利用草地上的遥感数据估算潜热和显热的地表通量。

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摘要

The overall topic of the research described 10 this dissertation was the partitioning of available energy at the Earth's surface into sensible and latent heat flux, with an emphasis on the development of techniques which utilize remotely sensed data. One of the major objectives was; to investigate the modification of existing techniques, developed over agricultural surfaces, to "natural" ecosystems (i.e., non-agricultural vegetation types with variable and incomplete canopy cover). Ground-based measurements of surface fluxes, vegetation cover, and surface and root-zone soil moisture from the First ISLSCP (International Land Surface Climatology Program) Field Experiment (FIFE) were used to examine the factors controlling the partitioning of energy at ground stations with contrasting surface characteristics. Utilizing helicopter-based and satellite-based data acquired directly over ground-based flux stations at the FIFE experimental area, relatively simple algorithms were developed for estimating the soil heat flux and sensible heat flux from remotely sensed data. The root mean square error (RMSE) between the sensible heat flux computed with the remotely sensed data and the sensible heat flux measured at the ground stations was 33 Wm⁻². These algorithms were then applied on a pixel-by-pixel basis to data from a Landsat-TM (Thematic Mapper) scene acquired over the FIFE site on August 15, 1987 to produce spatially distributed surface energy-balance components for the FIFE site. A methodology for quantifying the effect of spatial scaling on parameters derived from remotely sensed data was presented. As an example of the utility of this approach, NDVI values for the FIFE experimental area were computed with input data of variable spatial resolution. The differences in the values of NDVI computed at different spatial resolutions were accurately predicted by an equation which quantified those differences in terms of variability in input observations.
机译:研究的总体主题描述了10本文是将地球表面的可用能量划分为感热通量和潜热通量,并着重于利用遥感数据的技术的发展。主要目标之一是;研究将在农业表面开发的现有技术修改为“自然”生态系统(即,具有不同且不完整的树冠覆盖的非农业植被类型)。第一个ISLSCP(国际陆地表面气候计划)野外试验(FIFE)通过地面对地面通量,植被覆盖以及地面和根部土壤水分进行了测量,以检查控制地面站能量分配的因素。对比鲜明的表面特性。利用直接从FIFE实验区的地面通量站获取的基于直升机和基于卫星的数据,开发了相对简单的算法,用于根据遥感数据估算土壤热通量和感热通量。用遥感数据计算出的感热通量与地面站测得的感热通量的均方根误差(RMSE)为33Wm²²。然后将这些算法逐像素应用于来自1987年8月15日在FIFE站点上获取的Landsat-TM(主题映射器)场景的数据,以生成FIFE站点在空间上分布的表面能平衡分量。提出了一种量化空间缩放对从遥感数据中得出的参数的影响的方法。作为此方法实用程序的一个示例,使用可变空间分辨率的输入数据计算了FIFE实验区域的NDVI值。通过等式可以准确预测在不同空间分辨率下计算出的NDVI值的差异,该公式可以量化输入观测值中的差异。

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    Humes Karen Sue.;

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  • 年度 1992
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