RII Track-4: PermaSense: Investigating Permafrost Landscapes in Transition Using Multidimensional Remote Sensing, Data Fusion, and Machine Learning Techniques

RII Track-4：PermaSense：利用多维遥感、数据融合和机器学习技术研究转型中的永久冻土景观

• 批准号: 1929170
• 负责人: Benjamin Jones
• 金额: $ 29.53万
• 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: 2019-12-01 至 2023-11-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1929170&HistoricalAwards=false
• 关键词: RII; Track; PermaSense; Investigating; Permafrost

Permafrost underlies around 25% of the Northern Hemisphere terrestrial landscape. Its degradation is impacting northern landscapes and societies. With an increase in the number of remote sensing platforms since the early 2000s, the ability to detect and measure permafrost-region disturbances over large areas has become more feasible. This research, a project we call PermaSense, will provide funding to increase the research capacity of a non-tenure track Research Assistant Faculty member and an early career post-doctoral researcher through extended visits, training, and collaboration at the University of Connecticut (UConn) Department of Natural Resources & the Environment (DNRE). PermaSense will allow the PI and postdoc to build upon their permafrost-region field and remote sensing research program by acquiring new data fusion and machine learning techniques. PermaSense products are directly relevant to the State of Alaska and the nation. The skills and knowledge transfer gained during this project will increase the capacity of permafrost research and remote sensing at the University of Alaska Fairbanks. The research addresses several of the Interagency Arctic Research Policy Committee (IARPC) performance elements related to permafrost, terrestrial ecosystems, coastal resilience, and environmental intelligence as specified in the FY2017-2021 Arctic Research Plan.Permafrost is defined as ground that remains at or below 0 degrees Celsius for at least two consecutive years. Disturbance and warming of near-surface permafrost may lead to widespread terrain instability in ice-rich permafrost regions, impacting ecosystems, hydrology, infrastructure, society, and soil-carbon dynamics. Remote sensing is an important resource for observing, documenting, and better understanding landscape change from local to pan-Arctic scales. However, no one remote sensing tool is particularly suited for detecting and observing the suite of landscape change scenarios associated with transitioning permafrost. PermaSense will investigate myriad land surface changes occurring in permafrost regions using multidimensional remote sensing, data fusion, and machine learning techniques. PermaSense will enhance methodological developments and adaptations to unseal faster, deeper and more accurately analyze large volumes of multidimensional remote-sensing data to address the guiding research question: How extensive is contemporary permafrost degradation in the Arctic and Subarctic? We will conduct an analysis of multidimensional remote sensing observations at four representative permafrost-region study areas that capture the variability in the lateral extent of permafrost. The inherent differences in ecology, climate, landscape history, and their role in transitioning permafrost regions will be tested using common approaches across all sites as well as value-added products available for particular regions. PermaSense will develop an online resource and toolset that will provide spatially and temporally scalable information on permafrost region disturbances and a tool for local planning activities, the scientific community, and regional decision-makers tasked with responding to permafrost regions in transition.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.

多年冻土是约25％的北半球陆地景观。它的退化影响了北部的景观和社会。自2000年代初以来，随着遥感平台数量的增加，检测和测量大区域的多年冻土区域干扰的能力变得更加可行。这项研究是一个称为Permasense的项目，将提供资金，以通过扩展访问，培训和康涅狄格大学（UCONN）自然资源与环境学系（DNRE）（DNRE）的扩展访问，培训和合作，以提高非特征轨道研究助理教师和早期职业生涯后的研究后研究能力。 Permasense将允许PI和PostDoc通过获取新的数据融合和机器学习技术来建立其永久冻土区域和遥感研究计划。 Permasense产品与阿拉斯加及国家的状况直接相关。在该项目中获得的技能和知识转移将增加阿拉斯加Fairbanks大学的永久冻土研究和遥感能力的能力。该研究涉及与多年冻土，陆地生态系统，沿海弹性和环境智能有关的几个机构间北极研究政策委员会（IARPC）的绩效要素，如2017-2021北极研究计划所指定的。PermaFrost被定义为至少在0 degrees Celsius for Deprees Celsius dist Cuntrees Celsius twe Cotecectius cotecect twe Coles cotecececect的少于或低于0。近地面多年冻土的干扰和变暖可能会导致冰块多的多年冻土区域的广泛地形不稳定，从而影响生态系统，水文，基础设施，社会和土壤碳动态。遥感是观察，记录和更好地理解从本地变为泛量表的景观变化的重要资源。但是，没有一种遥感工具特别适合于检测和观察与过渡性永久冻土相关的景观变化方案。 Permasense将使用多维遥感，数据融合和机器学习技术研究在多年冻土区域中发生的无数土地变化。 Permasense将增强方法论发展和适应性，以更快，更深入，更准确地分析大量多维遥感数据，以解决指导研究问题：北极和亚北极和亚北极和亚北极的当代多年冻土降解有多广泛？我们将在四个代表性的多年冻土区域研究区域对多维遥感观测值进行分析，这些观测值捕获了多年冻土横向范围内的可变性。生态学，气候，景观历史及其在过渡多年冻土区域中的作用的固有差异将使用所有地点的通用方法以及可用于特定地区的增值产品进行测试。 Permasense将开发一种在线资源和工具集，该奖学金将提供有关永久冻土区域干扰的空间和时间可扩展的信息，以及用于本地计划活动，科学界和区域决策者的工具，负责响应过渡过程中的永久冻土区域。该奖项颁发了NSF的法定任务，反映了通过评估基金会的范围和宽广的范围，并且已被认为是通过基金会的范围来审查的。

项目成果

Orthomosaic Image and Digital Surface Model for the Navigating the New Arctic, Ice-rich Permafrost Systems (IRPS) field sites, Prudhoe Bay Oilfields, northern Alaska, 29 August 2021

用于导航新北极、富含冰的永久冻土系统 (IRPS) 现场的正射图像和数字表面模型，阿拉斯加北部普拉德霍湾油田，2021 年 8 月 29 日

• DOI: 10.18739/a24t6f50k
• 发表时间: 2024
• 期刊: NSF Arctic Data Center
• 作者: Jones, Benjamin

Post-fire stabilization of thaw-affected permafrost terrain in northern Alaska

阿拉斯加北部受解冻影响的永久冻土地形的火灾后稳定

• DOI: 10.1038/s41598-024-58998-5
• 发表时间: 2024
• 期刊: Scientific Reports
• 影响因子: 4.6
• 作者: Jones, Benjamin M.;Kanevskiy, Mikhail Z.;Shur, Yuri;Gaglioti, Benjamin V.;Jorgenson, M. Torre;Ward Jones, Melissa K.;Veremeeva, Alexandra;Miller, Eric A.;Jandt, Randi
• 通讯作者: Jandt, Randi

Rapid transformation of tundra ecosystems from ice-wedge degradation

冰楔退化导致苔原生态系统快速转变

• DOI: 10.1016/j.gloplacha.2022.103921
• 发表时间: 2022
• 期刊: Global and Planetary Change
• 影响因子: 3.9
• 作者: Jorgenson, M.T.;Kanevskiy, M.Z.;Jorgenson, J.C.;Liljedahl, A.;Shur, Y.;Epstein, H.;Kent, K.;Griffin, C.G.;Daanen, R.;Boldenow, M.
• 通讯作者: Boldenow, M.

Multi-Dimensional Remote Sensing Analysis Documents Beaver-Induced Permafrost Degradation, Seward Peninsula, Alaska

• DOI: 10.3390/rs13234863
• 发表时间: 2021-12-01
• 期刊: REMOTE SENSING
• 影响因子: 5
• 作者: Jones, Benjamin M.;Tape, Ken D.;Miller, Charles E.
• 通讯作者: Miller, Charles E.

Post-drainage vegetation, microtopography and organic matter in Arctic drained lake basins

• DOI: 10.1088/1748-9326/ad2eeb
• 发表时间: 2024-04-01
• 期刊: ENVIRONMENTAL RESEARCH LETTERS
• 影响因子: 6.7
• 作者: Wolter，Juliane;Jones，Benjamin M.;Grosse，Guido
• 通讯作者: Grosse，Guido