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: 2126468
• 负责人: Kirsteen Tinto
• 金额: $ 34.38万
• 依托单位: Columbia University
• 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=2126468&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.

地球的极地冰盖在地质时代塑造海平面上起着至关重要的作用，但是对当代气候变化的冰原反应仍然高度不确定。四十年的太空传播观察结果揭示了通过测量的海拔，重力和冰流变化的变化，冰盖质量损失的最新加速。但是，使用这些卫星观测来预测未来的行为仍然很困难。机载雷达声音测量值提供了限制冰盖表面动态的潜力，因为它们可以在冰格范围内绘制地下参数。但是，多个组织收集了五十年的雷达数据，这些组织部署了一系列系统，这些系统在数据策略和处理方法下分布，导致孤立的研究导致较低的效率和增加科学的时间。开放的极地雷达团队占南极雷达声音数据的83％，几乎完整的格陵兰岛和极地海冰覆盖范围。这些数据集将以通用格式放置，并通过通用界面通过最终用户驱动过程为科学家提供通用工具。开放极性雷达有可能在多个尺度上大大改善冰片模型。这可以从根本上提高对冰片崩溃过程的理解，修改对过去的冰上动态的理解，并迅速改善海平面上升估计。改进的海平面项目将导致更好的缓解策略，从而减少沿海洪水的危险和成本。雷达软件和服务将是其他雷达问题（包括行星应用）的常见。共享工具将有助于和利用Earthcube生态系统，从而解决解决数据共享和图像分析研究中其他挑战的解决方案。开放极性雷达将有助于对本科生和研究生和博士后的多学科培训。首席调查人员将在特定于学科的会议上与科学家进行年度培训研讨会和黑客马拉松以及活动，以收集反馈并提高Cryosphere Sciences社区的雷达能力。该项目还将在夏季研究经验中包括代表性不足的社区。开放的极性雷达项目将建立一个软件生态系统，以巩固极地雷达软件和服务，并在社区驱动的过程中标准化和可搜索的相关数据集标准化和可搜索。目标受众是放射性研究领域的科学家，AI数据科学家，以及各种卫星，机载和地面冰渗透的辐射数据背后的软件和数据工程师，这些数据收集了冰盖，山地冰川，海冰和行星冰冷的身体。极性雷达声音数据是一个很大程度上未开发的资源，因为与分散处理和手动解释相关的挑战阻止了范围范围内的雷达数据的先进应用。这项工作启动了一个不断增长的数据库，其中包括地球物理图像的AI培训数据，使传统摄影的计算机视觉技术能够通往该领域，直到最近才依靠人类从地球地下图像中提取含义。为了使分享数据进行科学创新，该项目提议：（1）将每个机构从每个机构合并到一个开源软件套件中，（2）升级当前的开放极性服务器，以满足可访问和可重复使用的（公平的）原理和多型机构需求的可访问和可重复使用的（公平的）需求，并通过将各种数据纳入噪声（3）质量（3）的质量（3） 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 engineer 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 precious of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.