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首页> 外文学位 >Single-source surface energy balance algorithms to estimate evapotranspiration from satellite-based remotely sensed data.
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Single-source surface energy balance algorithms to estimate evapotranspiration from satellite-based remotely sensed data.

机译：单源表面能平衡算法可从基于卫星的遥感数据中估算蒸散量。

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摘要

The flow of water and energy fluxes at the Earth's surface and within the climate system is difficult to quantify. Recent advances in remote sensing technologies have provided scientists with a useful means to improve characterization of these complex processes. However, many challenges remain that limit our ability to optimize remote sensing data in determining evapotranspiration (ET) and energy fluxes. For example, periodic cloud cover limits the operational use of remotely sensed data from passive sensors in monitoring seasonal fluxes. Additionally, there are many remote sensing-based single-source surface energy balance (SEB) models, but no clear guidance on which one to use in a particular application. Two widely used models---surface energy balance algorithm for land (SEBAL) and mapping ET at high resolution with internalized calibration (METRIC)---need substantial human-intervention that limits their applicability in broad-scale studies. This dissertation addressed some of these challenges by proposing novel ways to optimize available resources within the SEB-based ET modeling framework. A simple regression-based Landsat-Moderate Resolution Imaging Spectroradiometer (MODIS) fusion model was developed to integrate Landsat spatial and MODIS temporal characteristics in calculating ET. The fusion model produced reliable estimates of seasonal ET at moderate spatial resolution while mitigating the impact that cloud cover can have on image availability. The dissertation also evaluated five commonly used remote sensing-based single-source SEB models and found the surface energy balance system (SEBS) may be the best overall model for use in humid subtropical climates. The study also determined that model accuracy varies with land cover type, for example, all models worked well for wet marsh conditions, but the SEBAL and simplified surface energy balance index (S-SEBI) models worked better than the alternatives for grass cover. A new automated approach based on exhaustive search algorithm was also developed that eliminates the need for human-intervention in SEBAL or METRIC models, which could extend the domain of these models to inexperienced users and facilitate operational applications. Future studies are recommended to incorporate ancillary data within the SEB models to account for changes in soil moisture conditions and to test the advantage of multi-model ensemble approaches for ET modeling.
机译：地球表面和气候系统内部的水和能量通量流量很难量化。遥感技术的最新进展为科学家提供了一种有用的手段，以改善这些复杂过程的特性。但是，仍然存在许多挑战，限制了我们在确定蒸散量（ET）和能量通量时优化遥感数据的能力。例如，定期的云量覆盖限制了来自无源传感器的遥感数据在监测季节性通量中的操作使用。此外，还有许多基于遥感的单源表面能平衡（SEB）模型，但没有明确指导在特定应用中使用哪种模型。两种广泛使用的模型-土地表面能量平衡算法（SEBAL）和内标定标（METRIC）高分辨率绘制ET-需要大量的人工干预，这限制了它们在大规模研究中的适用性。本文提出了在基于SEB的ET建模框架内优化可用资源的新颖方法，从而解决了其中一些挑战。建立了一个简单的基于回归的Landsat中分辨率成像光谱仪（MODIS）融合模型，以整合Landsat的空间和MODIS时间特征来计算ET。融合模型在中等空间分辨率下产生了对季节ET的可靠估计，同时减轻了云量覆盖对图像可用性的影响。论文还评估了五个常用的基于遥感的单源SEB模型，发现地表能量平衡系统（SEBS）可能是在潮湿的亚热带气候中使用的最佳整体模型。该研究还确定了模型精度随土地覆盖类型而变化，例如，所有模型在湿沼泽条件下均能很好地发挥作用，但是SEBAL和简化的表面能平衡指数（S-SEBI）模型比草皮替代方案的效果更好。还开发了一种基于穷举搜索算法的新型自动化方法，该方法无需人工干预SEBAL或METRIC模型，从而可以将这些模型的范围扩展到经验不足的用户，并简化操作应用程序。建议未来的研究将辅助数据纳入SEB模型中，以说明土壤湿度条件的变化，并测试用于ET建模的多模型集成方法的优势。

著录项

  • 作者

    Bhattarai, Nishan.;

  • 作者单位

    State University of New York College of Environmental Science and Forestry.;

  • 授予单位 State University of New York College of Environmental Science and Forestry.;
  • 学科 Remote sensing.;Geographic information science and geodesy.;Hydrologic sciences.
  • 学位 Ph.D.
  • 年度 2015
  • 页码 142 p.
  • 总页数 142
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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