Collaborative Research: EarthCube Capabilities: Open Polar Radar (OPoRa) Software and Service

合作研究：EarthCube 功能：开放极地雷达 (OPoRa) 软件和服务

• 批准号: 2126503
• 负责人: John Paden
• 金额: $ 67.11万
• 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: 2021-09-01 至 2024-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2126503&HistoricalAwards=false
• 关键词: Collaborative; Research; EarthCube; Capabilities; Open

Earth’s polar ice sheets play a critical role in shaping sea level over geological time, yet ice-sheet response to contemporary climate change remains highly uncertain. Forty years of spaceborne observations reveal the recent acceleration in mass loss of the ice sheets through measured change in elevation, gravity, and ice-flow variation. It remains difficult, however, to use these satellite observations to predict future behavior. Airborne radar sounder measurements offer the potential to constrain ice-sheet surface dynamics because they can map out subsurface parameters on an ice-sheet-wide scale. However, five decades of radar data collection by multiple organizations deploying a range of systems with data distributed under inconsistent data policies and processing methods leads to siloed research resulting in lower efficiency and increased time to science. The Open Polar Radar team accounts for 83% of Antarctica radar sounder data and nearly complete Greenland and polar sea-ice coverage. These datasets will be placed in common formats and made available through a common interface with a common set of tools for scientists via an end-user driven process. Open Polar Radar has the potential to vastly improve ice-sheet models at multiple scales. This could radically improve the understanding of the ice-sheet collapse processes, revise the understanding of past ice-sheet dynamics, and rapidly improve sea-level rise estimates. Improved sea-level projections will lead to better mitigation strategies that could reduce the dangers and costs of coastal flooding. The radar software and services will be common to other sounding radar problems, including planetary applications. The shared tools will contribute to and leverage the EarthCube ecosystem leading to solutions to other challenges in data sharing and image analytics research. Open Polar Radar will contribute to the multidisciplinary training of undergraduate and graduate students and postdocs. The principal investigators will engage scientists with annual training workshops and hackathons and activities at discipline-specific meetings to gather feedback and to advance the radar capabilities of the cryospheric sciences community. The project will also include under-represented communities in summer research experiences.The Open Polar Radar project will establish a software ecosystem to consolidate polar radar software and services and make the associated datasets standardized and searchable – all in a community driven process. The target audiences are radioglaciology domain scientists, AI data scientists, and the software and data engineers behind the various satellite, airborne, and ground-based ice penetrating radar data collected over ice sheets, mountain glaciers, sea ice, and planetary icy bodies. Polar radar sounder data are a largely untapped resource, because the challenges associated with decentralized processing and manual interpretation prevent advanced applications of radar data on an ice-sheet-wide scale. This work starts a growing database of AI training data for geophysical imagery, enabling computer vision techniques common for traditional photography to a field that has, until very recently, relied on humans to extract meaning from images of Earth’s subsurface. To enable sharing data for scientific innovation, this project proposes to: (1) Merge data processing chains from each institution into one open-source software suite, (2) Upgrade the current Open Polar Server to meet Findable Accessible Interoperable and Reusable (FAIR) principles and multi-institution needs as well as incorporate a number of new data layers, (3) Enhance the quality of all data products by employing the shared tools for noise removal and image enhancement driven by science applications and AI model needs, (4) Demonstrate several use cases including the application of combined AI and physical models for tracking englacial features to validate results in two regions that are intersections of multiple data providers’ coverage.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.

地球的极地冰盖在形成地质时期的海平面方面发挥着关键作用，但冰盖对当代气候变化的反应仍然非常不确定。40年的空间观测揭示了最近通过测量海拔、重力和冰流变化的变化来加速冰盖的质量损失。然而，利用这些卫星观测来预测未来的行为仍然很困难。机载雷达探测器测量提供了限制冰盖表面动态的潜力，因为它们可以绘制出冰盖范围内的地下参数。然而，50年来，多个组织部署了一系列系统来收集雷达数据，这些系统的数据分布在不一致的数据政策和处理方法下，导致孤立的研究，从而降低了效率，增加了科学研究的时间。开放极地雷达团队占南极洲雷达探测器数据的83%，几乎覆盖了格陵兰岛和极地海冰。这些数据集将以通用格式放置，并通过最终用户驱动的过程，通过一个具有一套通用工具的通用界面提供给科学家。开放式极地雷达有可能在多个尺度上极大地改进冰盖模型。这可以从根本上提高对冰盖崩塌过程的理解，修改对过去冰盖动力学的理解，并迅速提高对海平面上升的估计。改进海平面预测将导致更好的减灾战略，从而减少沿海洪水的危险和成本。该雷达软件和服务将与其他探测雷达问题通用，包括行星应用。共享工具将有助于并利用EarthCube生态系统，从而解决数据共享和图像分析研究中的其他挑战。 开放极地雷达将有助于本科生、研究生和博士后的多学科培训。主要研究人员将让科学家参加年度培训讲习班和黑客马拉松以及特定学科会议上的活动，以收集反馈并提高冰冻圈科学界的雷达能力。开放极地雷达项目将建立一个软件生态系统，以整合极地雷达软件和服务，并使相关数据集标准化和可搜索-所有这些都在社区驱动的过程中进行。目标受众是放射性冰川学领域的科学家，人工智能数据科学家，以及在冰盖，山地冰川，海冰和行星冰体上收集的各种卫星，机载和地面冰穿透雷达数据背后的软件和数据工程师。极地雷达探测器数据在很大程度上是一种尚未开发的资源，因为分散处理和人工判读带来的挑战阻碍了雷达数据在整个冰盖范围内的高级应用。这项工作启动了一个不断增长的用于地球物理图像的人工智能训练数据库，使传统摄影中常见的计算机视觉技术能够应用于一个直到最近还依赖人类从地球地下图像中提取意义的领域。为实现科学创新数据共享，该项目建议：（1）将每个机构的数据处理链合并到一个开源软件套件中，（2）升级当前的Open Polar服务器，以满足可查找、可互操作和可重用（FAIR）原则和多机构需求，并纳入一些新的数据层，（3）通过使用共享工具来提高所有数据产品的质量，以科学应用和人工智能模型需求为驱动力进行降噪和图像增强，（四）演示几个用例，包括将人工智能和物理模型相结合，用于跟踪冰川特征，以验证两种情况下的结果该奖项反映了NSF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。