REU Site: Interdisciplinary Geospatial Approaches to Watershed Science

REU 网站:流域科学的跨学科地理空间方法

基本信息

  • 批准号:
    1757705
  • 负责人:
  • 金额:
    $ 29.6万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Continuing Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-05-15 至 2022-04-30
  • 项目状态:
    已结题

项目摘要

As students in environmental fields enter the workforce they will confront, at some scale, many of the "grand challenges" that face humankind (e.g., access to clean water, production of sufficient food, adaptation to change climate). Solutions to such problems require a willingness to embrace alternative and innovative approaches rooted in multiple disciplines, as well as an appreciation for diverse perspectives. Students participating in this REU will engage in research focused on the sustainable provision of clean water and food in a Midwest agricultural watershed. The watershed has been the focus of intense investigation over the past two decades that examines carbon, nutrient, and sediment transport, crop productivity, agricultural economics, governance and social priorities. Students will use team-based approaches to build on this ongoing research to examine issues critical to societies across the nation. Their research will be interdisciplinary, team-based and innovative. We anticipate students participating in this REU will better appreciate team-based approaches to science and analytical methods relevant to their future careers.The primary objective of this REU site program is to prepare students for complex problem-solving and interdisciplinary research. Students from all fields, and particularly environmental fields, will face real-world problems that are complex, ill-defined, multifaceted and ever changing. Solutions to such problems require a willingness to embrace alternative and innovative approaches rooted in multiple disciplines, as well as an appreciation for diverse perspectives (National Academy of Engineering 2016). Students participating in this REU will engage in research focused on the sustainable provision of clean water and food in a Midwest agricultural watershed. This watershed has been the focus of intense investigation over the past two decades. The watershed, available infrastructure, and ongoing research provide an exemplary case study through which students will engage in team-based approaches to solving complex questions about natural and human systems that are coupled, complex and adaptive. Interdisciplinary team based approaches to science will be developed from hypothesis generation, through data collection, and onto data analysis and interpretation. Throughout this process students will be exposed to cutting edge geospatial technologies and analytical techniques to better prepare them to apply analytical methods to a variety of topics and STEM related careers.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
随着环境领域的学生进入劳动力市场,他们将在一定程度上面临人类面临的许多“重大挑战”(例如,获得清洁水、生产充足的粮食、适应气候变化)。 要解决这些问题,就需要愿意接受植根于多学科的替代和创新办法,并欣赏不同的观点。参加该REU的学生将从事专注于中西部农业流域清洁水和食物可持续供应的研究。在过去的二十年里,该流域一直是密集调查的焦点,调查了碳,养分和沉积物运输,作物生产力,农业经济,治理和社会优先事项。学生将使用团队为基础的方法,建立在这个正在进行的研究,以检查对全国各地的社会至关重要的问题。他们的研究将是跨学科的,基于团队的和创新的。我们预计参加这个REU的学生将更好地欣赏以团队为基础的方法,以科学和分析方法,与他们未来的职业生涯。这个REU网站程序的主要目标是为学生准备复杂的问题解决和跨学科的研究。来自各个领域的学生,特别是环境领域的学生,将面临复杂,不明确,多方面和不断变化的现实问题。这些问题的解决方案需要愿意接受植根于多个学科的替代和创新方法,以及对不同观点的欣赏(美国国家工程院2016年)。参加该REU的学生将从事专注于中西部农业流域清洁水和食物可持续供应的研究。这个分水岭在过去二十年里一直是密集调查的焦点。分水岭,现有的基础设施和正在进行的研究提供了一个示范性的案例研究,通过该研究,学生将参与以团队为基础的方法来解决有关耦合,复杂和适应性的自然和人类系统的复杂问题。基于跨学科团队的科学方法将从假设生成,通过数据收集,到数据分析和解释。在整个过程中,学生将接触到最前沿的地理空间技术和分析技术,以更好地准备他们将分析方法应用于各种主题和STEM相关的职业。该奖项反映了NSF的法定使命,并被认为值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估来支持。

项目成果

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Marc Linderman其他文献

Comparing laboratory and airborne hyperspectral data for the estimation and mapping of topsoil organic carbon: Feature selection coupled with random forest
  • DOI:
    https://doi.org/10.1016/j.still.2020.104589
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
  • 作者:
    Yongsheng Hong;Songchao Chen;Yiyun Chen;Marc Linderman;Abdul M.Mouazen;Yaolin Liu;Long Guo;Lei Yu;Yanfang Liu;Hang Cheng;Yi Liu
  • 通讯作者:
    Yi Liu
Comparing laboratory and airborne hyperspectral data for the estimation and mapping of topsoil organic carbon: Feature selection coupled with random forest
比较实验室和机载高光谱数据以估计和绘制表土有机碳:特征选择与随机森林相结合
  • DOI:
    10.1016/j.still.2020.104589
  • 发表时间:
    2020-05
  • 期刊:
  • 影响因子:
    6.5
  • 作者:
    Yongsheng Hong;Songchao Chen;Yiyun Chen;Marc Linderman;Abdul M.Mouazen;Yaolin Liu;Long Guo;Lei Yu;Yanfang Liu;Hang Cheng;Yi Liu
  • 通讯作者:
    Yi Liu
Exploring the potential of airborne hyperspectral image for estimating topsoil organic carbon: Effects of fractional-order derivative and optimal band combination algorithm
  • DOI:
    ARTN 114228
  • 发表时间:
    2020
  • 期刊:
  • 影响因子:
    6.1
  • 作者:
    Yongsheng Hong;Long Guo;Songchao Chen;Marc Linderman;Abdul M.Mouazen;Lei Yu;Yiyun Chen;Yaolin Liu;Yanfang Liu;Hang Cheng;Yi Liu
  • 通讯作者:
    Yi Liu

Marc Linderman的其他文献

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{{ truncateString('Marc Linderman', 18)}}的其他基金

Visit to the Three Gorges Dam Region in Support of NSF Proposal Development; Yiehang, China; Summer, 2006
访问三峡坝区,支持 NSF 提案制定;
  • 批准号:
    0630394
  • 财政年份:
    2006
  • 资助金额:
    $ 29.6万
  • 项目类别:
    Standard Grant
International Research Fellowship: Application of Global Biophysical Fields Derived from Large-Swath Remote Sensing Data to the Detection and Categorization of Land-Cover Change
国际研究奖学金:大幅遥感数据得出的全球生物物理场在土地覆盖变化检测和分类中的应用
  • 批准号:
    0301307
  • 财政年份:
    2003
  • 资助金额:
    $ 29.6万
  • 项目类别:
    Fellowship

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