NNA Track 1: Collaborative Research: The Permafrost Discovery Gateway: Navigating the new Arctic tundra through Big Data, artificial intelligence, and cyberinfrastructure

NNA 轨道 1：协作研究：永久冻土发现网关：通过大数据、人工智能和网络基础设施导航新的北极苔原

• 批准号: 2052107
• 负责人: Anna Liljedahl
• 金额: $ 72.18万
• 依托单位: Woodwell Climate Research Center, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-28 至 2024-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2052107&HistoricalAwards=false
• 关键词: NNA; Track; Collaborative; Research; Permafrost

Navigating the New Arctic (NNA) is one of NSF's 10 Big Ideas. NNA projects address convergence scientific challenges in the rapidly changing Arctic. The Arctic research is needed to inform the economy, security and resilience of the Nation, the larger region and the globe. NNA empowers new research partnerships from local to international scales, diversifies the next generation of Arctic researchers, and integrates the co-production of knowledge. This award fulfills part of that aim.Permafrost is ground that remains frozen for at least two consecutive years. It occurs under approximately one fourth of the northern hemisphere's land surface. In the far north, the permafrost is continuous across the landscape and contains large amounts of ice in its upper few meters. Thawing of permafrost has been observed at several locations across the Arctic in recent decades, yet the complete extent of permafrost degradation is not yet described. This is because it is difficult to directly measure permafrost. However, the presence and health of permafrost can be inferred from characteristic ground surface features. For example, permafrost can be detected from detailed satellite images through the presence of 30-meter-wide ice-wedge polygons. It is important to detect areas with thawing permafrost to identify challenges for infrastructure that depend on a foundation of solid ground. This project is developing the Permafrost Discovery Gateway, an online platform that makes permafrost information more accessible and discoverable by the public. The public includes industry, non-profit organizations, and people living and working in the Arctic. Future workforce development includes the training of graduate students and postdocs in remote sensing technology. Five early career researchers are the lead investigators. The K-12 education community are receiving virtual resources to help them interact with the Permafrost Discovery Gateway. In addition, a collaborative art exhibition, an interactive digital story, and an online Earth as Art gallery are displaying Arctic landscapes to the general public. These tools enable diverse peoples of different technical backgrounds to interact with permafrost knowledge across the entire Arctic. This project informs the economy, security, and resilience of the U.S., the larger region, and the globe with respect to Arctic change. The main goal of this project is to develop supporting cyberinfrastructure to harness information from high-resolution satellite imagery. This approach is advancing the understanding of permafrost degradation across the entire Arctic. This project is: (1) utilizing existing Big Imagery, (2) refining and developing new automated remote sensing classification tools based on machine and deep learning techniques, (3) applying the mapping tools to Arctic satellite imagery, (4) making permafrost map products and tools publicly accessible, and (5) enabling discovery through visualization and analysis tools designed with users of the Permafrost Discovery Gateway. The project is producing a cyberinfrastructure framework that also includes existing Arctic map products. This framework, along with an engaged user community, is allowing researchers to better quantify the spatial extent of permafrost degradation across the Arctic. Potential controls (weather, topography, vegetation, soil properties) on permafrost degradation are also being evaluated. The Permafrost Discovery Gateway helps ensure information access to the broader research community and encourage new partnerships around knowledge of Arctic permafrost.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.

导航新北极（NNA）是美国国家科学基金会的十大构想之一。NNA项目解决快速变化的北极地区的融合科学挑战。北极研究需要为国家、更大地区和全球的经济、安全和复原力提供信息。NNA支持从地方到国际规模的新研究伙伴关系，使下一代北极研究人员多样化，并整合知识的共同生产。这个奖项部分实现了这一目标。永久冻土是指至少连续两年保持冻结状态的土地。它发生在北半球大约四分之一的陆地表面之下。在遥远的北方，永久冻土层是连续的，在其上部的几米处含有大量的冰。近几十年来，在北极的几个地点已经观察到永久冻土的融化，但永久冻土退化的完整程度尚未得到描述。这是因为很难直接测量永久冻土。然而，冻土的存在和健康状况可以从地表特征推断出来。例如，通过30米宽的冰楔多边形，可以从详细的卫星图像中探测到永久冻土。探测永久冻土融化的地区，以确定依赖于坚实地基的基础设施面临的挑战，这一点很重要。该项目正在开发永久冻土发现门户，这是一个在线平台，使公众更容易获取和发现永久冻土信息。公众包括工业界、非营利组织以及在北极生活和工作的人们。未来的劳动力发展包括培养遥感技术方面的研究生和博士后。五名早期的职业研究人员是主要调查人员。K-12教育社区正在接收虚拟资源，以帮助他们与永久冻土发现网关进行互动。此外，一个合作艺术展、一个互动数字故事和一个在线地球艺术画廊正在向公众展示北极景观。这些工具使具有不同技术背景的不同民族能够与整个北极地区的永久冻土知识进行互动。该项目向美国、更大地区和全球通报有关北极变化的经济、安全和复原力。该项目的主要目标是开发支持网络基础设施，以利用高分辨率卫星图像中的信息。这种方法正在推进对整个北极地区永久冻土退化的理解。该项目是：(1)利用现有的大图像，(2)基于机器和深度学习技术改进和开发新的自动化遥感分类工具，(3)将绘图工具应用于北极卫星图像，(4)使永久冻土地图产品和工具可公开访问，(5)通过与永久冻土发现网关用户一起设计的可视化和分析工具实现发现。该项目正在创建一个网络基础设施框架，其中还包括现有的北极地图产品。这一框架，以及参与其中的用户社区，使研究人员能够更好地量化整个北极永久冻土退化的空间范围。对永久冻土退化的潜在控制（天气、地形、植被、土壤性质）也正在进行评估。永久冻土发现门户有助于确保更广泛的研究界获得信息，并鼓励围绕北极永久冻土知识建立新的伙伴关系。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Ice-wedge polygon detection in satellite imagery from pan-Arctic regions, Permafrost Discovery Gateway, 2001-2021

泛北极地区卫星图像中的冰楔多边形检测，永久冻土发现网关，2001-2021 年

• DOI: 10.18739/a2kw57k57
• 发表时间: 2023
• 期刊: NSF Arctic Data Center
• 作者: Witharana, Chandi;Udawalpola, Mahendra R.;Perera, Amal S.;Hasan, Amit;Manos, Elias;Liljedahl, Anna;Kanevskiy, Mikhail;Jorgenson, M. Torre;Daanen, Ronald;Jones, Benjamin
• 通讯作者: Jones, Benjamin

Permafrost Monitoring from Space

• DOI: 10.1007/s10712-023-09770-3
• 发表时间: 2023-03
• 期刊: Surveys in Geophysics
• 影响因子: 4.6
• 作者: A. Bartsch;T. Strozzi;Ingmar Nitze

Integrating local environmental observations and remote sensing to better understand the life cycle of a thermokarst lake in Arctic Alaska

结合当地环境观测和遥感，更好地了解阿拉斯加北极热岩溶湖的生命周期

• DOI: 10.1080/15230430.2023.2195518
• 发表时间: 2023
• 期刊: and Alpine Research
• 作者: Jones, Benjamin M.;Schaeffer Tessier, Susan;Tessier, Tim;Brubaker, Michael;Brook, Mike;Schaeffer, Jackie;Ward Jones, Melissa K.;Grosse, Guido;Nitze, Ingmar;Rettelbach, Tabea
• 通讯作者: Rettelbach, Tabea

Developing and Testing a Deep Learning Approach for Mapping Retrogressive Thaw Slumps

• DOI: 10.3390/rs13214294
• 发表时间: 2021-10
• 期刊: Remote. Sens.
• 作者: Ingmar Nitze;Konrad Heidler;S. Barth;G. Grosse

A Quantitative Graph-Based Approach to Monitoring Ice-Wedge Trough Dynamics in Polygonal Permafrost Landscapes

• DOI: 10.3390/rs13163098
• 发表时间: 2021-08
• 期刊: Remote. Sens.
• 作者: Tabea Rettelbach;M. Langer;Ingmar Nitze;B. Jones;V. Helm;J. Freytag;G. Grosse