EAGER: Extending Greenland glacier observations using newly-discovered aerial photographs

EAGER：利用新发现的航空照片扩大格陵兰冰川观测范围

• 批准号: 2135018
• 负责人: Leigh Stearns
• 金额: $ 29.99万
• 依托单位: University of Kansas Center for Research Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2135018&HistoricalAwards=false
• 关键词: EAGER; Extending; Greenland; glacier; observations

Three military airborne campaigns (USAF: 1940s-1960s, USCG: 1970s, USN: 1970s-1980s) acquired tens of thousands of aerial photographs of Greenland. These recently-located photographs can yield insight into ice-sheet wide glacier behavior prior to satellite observations but have not yet been digitized or used for science. Currently, lack of ice sheet-wide observations prior to the 1980s limits our ability to model the long-term evolution of outlet glacier dynamics. The research team will digitize historic images from the 1940s to 1980s, render glacier surface elevations and terminus positions for the perimeter of Greenland, and estimate surface velocities where the data permits. By providing glacier information further back in time, this new historical dataset can be used to improve constraints needed to model glacier dynamics which will further advance accuracy in predictive models of glacier response to climate change. The workflow and products will be available in a public repository for the community to access and a tutorial will be designed to help researchers repeat the process for other historical images. The earliest ice sheet-wide surface elevation maps were produced using data from the 1980s. This project will extend the historical record by including Greenland-wide glacier images from the 1940s and 1970s and from the 1950s and 1960s for a large number of outlet glaciers. The methodology includes: digitizing the air photo film negatives, geolocating the photo centers using a combination of military flight index maps and field notes, and processing the images using structure-from-motion (SfM) photogrammetry techniques to generate surface elevations. The real-world coordinates are manually extracted localized peaks from present-day elevations of stable terrain (e.g., exposed bedrock). This methodology has been successfully carried out using historical air photos from Antarctica. Upon the completion of this project, the raw digital data and rendered products with accuracy estimates will be made accessible for public distribution. By extending the temporal scale of Greenland outlet glacier dynamics, this new historical dataset can improve constraints used in modeling glacier dynamics which will further advance accuracy in predictive models of glacier response to climate change. Raw data and derived products, including surface elevation, orthorectified images, and velocities, will be archived at the Arctic Data Center and results will be shared with QGreenland and GHub to expand the audience. A tutorial will also be designed to allow others to reproduce the results and apply the methodology to other historical datasets.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.

三场军事空降运动（USAF：1940年代1960年代，USCG：1970年代，USN：1970S-1980年代）收购了格陵兰岛成千上万的航空照片。这些最近置于的照片可以在卫星观测之前深入了解冰片宽冰川行为，但尚未将其数字化或用于科学。目前，在1980年代之前缺乏冰盖范围的观察结果限制了我们建模出口冰川动力学长期演变的能力。研究团队将数字化1940年代至1980年代的历史图像，使冰川表面高程和格陵兰周围的末端位置以及数据允许的估计表面速度。通过向更及时地提供冰川信息，该新的历史数据集可用于改善建模冰川动态所需的约束，这将进一步提高冰川响应对气候变化的预测模型的准确性。该工作流程和产品将在公共存储库中供社区访问，并将旨在帮助研究人员重复其他历史图像的过程。最早使用1980年代的数据生成了最早的冰盖表面高程图。该项目将通过包括1940年代和1970年代以及1950年代和1960年代的格陵兰范围冰川图像的历史记录来扩展历史记录。该方法包括：数字化空气照片薄膜负面，使用军事飞行指数图和现场音符的组合将照片中心进行地重新分配，并使用结构 - 运动（SFM）摄影技术来处理图像以产生表面高度。实际坐标是从稳定地形（例如，裸露的基岩）的当今高程中手动提取的局部峰。该方法已通过来自南极洲的历史空气照片成功地进行了。该项目完成后，将使原始数字数据和渲染的产品具有准确的估算，以进行公共分销。通过扩展格陵兰出口冰川动力学的时间尺度，该新的历史数据集可以改善用于建模冰川动力学的约束，这将进一步提高对气候变化冰川响应的预测模型的准确性。原始数据和衍生产品，包括表面高程，矫形图像和速度，将在北极数据中心存档，结果将与Qgreenland和Ghub共享，以扩大受众群体。教程还将旨在允许其他人重现结果并将方法应用于其他历史数据集。该奖项反映了NSF的法定任务，并使用基金会的知识分子优点和更广泛的影响评估标准，被认为值得通过评估来提供支持。