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: 1927872
• 负责人: Anna Liljedahl
• 金额: $ 88.14万
• 依托单位: University of Alaska Fairbanks Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-11-01 至 2020-10-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1927872&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.

NSF的10个大创意之一是导航新北极（NNA）。 NNA项目应对北极快速变化的融合科学挑战。需要进行北极研究，以告知国家，较大地区和全球的经济，安全和弹性。 NNA赋予从本地量表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，并整合了知识的共同生产。该奖项实现了这一目标的一部分。Permafrost是连续两年保持冻结的基础。它发生在北半球陆地表面的大约四分之一之下。在遥远的北部，永久冻土在整个景观中连续，并在其上几米中包含大量冰。近几十年来，在整个北极的多个位置都观察到了永久冻土的解冻，但尚未描述完整冻土降解的完全范围。这是因为很难直接测量多年冻土。但是，可以从特征地面特征推断出多年冻土的存在和健康。例如，可以通过存在30米宽的冰对边缘多边形从详细的卫星图像中检测到多年冻土。重要的是要检测具有融化多年冻土的区域，以确定取决于稳固基础的基础设施的挑战。该项目正在开发永久冻土发现网关，这是一个在线平台，使公众更容易访问和发现。公众包括行业，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对遥感技术的研究生和博士后的培训。五名早期职业研究人员是主要研究人员。 K-12教育社区正在收到虚拟资源，以帮助他们与永久冻土发现网关互动。此外，Art Gallery的合作艺术展览，交互式数字故事和在线地球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人民能够与整个北极的多年冻土知识互动。该项目在北极变化方面为美国，较大地区和全球的经济，安全和韧性提供了信息。该项目的主要目标是开发支持网络基础设施，从高分辨率卫星图像利用信息。这种方法正在促进对整个北极的多年冻土降解的理解。 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.该项目正在生产一个网络基础设施框架，其中还包括现有的北极地图产品。该框架以及敬业的用户社区，允许研究人员更好地量化北极的多年冻土降解的空间范围。还评估了潜在的控制（天气，地形，植被，土壤特性）在多年冻土降解上也正在评估。永久冻土发现门户有助于确保信息访问更广泛的研究社区，并鼓励围绕北极永久冻土知识的新伙伴关系。该奖项反映了NSF的法定任务，并被认为是值得通过基金会的知识分子的评估来支持的，并具有更广泛的影响。

项目成果

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

The Arctic Nearshore Turbidity Algorithm (ANTA) - A multi sensor turbidity algorithm for Arctic nearshore environments

• DOI: 10.1016/j.srs.2021.100036
• 发表时间: 2021-11
• 期刊: Science of Remote Sensing
• 作者: Konstantin P. Klein;H. Lantuit;B. Heim;D. Doxaran;B. Juhls;Ingmar Nitze;Daniela M. R. Walch;A. Poste;J. Søreide

An Object-Based Approach for Mapping Tundra Ice-Wedge Polygon Troughs from Very High Spatial Resolution Optical Satellite Imagery

• DOI: 10.3390/rs13040558
• 发表时间: 2021-02
• 期刊: Remote. Sens.
• 作者: C. Witharana;Md Abul Ehsan Bhuiyan;A. Liljedahl;M. Kanevskiy;T. Jorgenson;B. Jones;R. Daanen;H. Epstein;C. Griffin;K. Kent;Melissa K. Ward Jones

AUTOMATED RECOGNITION OF PERMAFROST DISTURBANCES USING HIGH-SPATIAL RESOLUTION SATELLITE IMAGERY AND DEEP LEARNING MODELS

使用高分辨率卫星图像和深度学习模型自动识别永久冻土扰动

• DOI: 10.5194/isprs-archives-xlvi-m-2-2022-203-2022
• 发表时间: 2022
• 期刊: Remote Sensing and Spatial Information Sciences
• 作者: Udawalpola, M. R.;Witharana, C.;Hasan, A.;Liljedahl, A.;Ward Jones, M.;Jones, B.
• 通讯作者: Jones, B.

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