Collaborative Proposal: EarthCube Integration: ICEBERG: Imagery Cyberinfrastructure and Extensible Building-Blocks to Enhance Research in the Geosciences

合作提案：EarthCube 集成：ICEBERG：图像网络基础设施和可扩展构建模块，以加强地球科学研究

• 批准号: 1740595
• 负责人: Heather Lynch
• 金额: $ 63.22万
• 依托单位: SUNY at Stony Brook
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-10-01 至 2022-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1740595&HistoricalAwards=false
• 关键词: Collaborative; Proposal; EarthCube; Integration; ICEBERG

Satellite imagery is rapidly transforming the way we see the planet, including our ability to study the most remote parts of the Arctic and Antarctic. Satellite imagery can help us map networks of rivers, study changes in the flow and thickness of glaciers, identify rock and soil types, and even find animals like penguins and seals. Because the availability of imagery in polar areas has increased rapidly over the last decade, we are now faced with a challenge: To move from small pilot-studies to pan-Arctic or pan-Antarctic analyses of geological and biological processes requires new infrastructures that link scientists, satellite imagery, and fast computing. The project, called ICEBERG - Imagery Cyberinfrastructure and Extensible Building-Blocks to Enhance Research in the Geosciences, aims to build the cyberinfrastructure required to make the most of satellite imagery for geosciences, starting with researchers working in polar areas, and then branching out to the larger community. The Broader Impacts of this proposal include the training of undergraduate and graduate students, as well as young investigators and female scientists. Moreover, the scientific findings enabled by this proposed cyberinfrastructure will have immediate benefits for our ability to predict the future dynamics of the polar regions, and critical to the management of Arctic and Antarctic resources. Polar geosciences stands at the precipice of a revolution, one enabled by the confluence of cutting edge analytical tools, petabytes of high-resolution imagery, and an ever growing array of high performance computing resources. With these tools at hand, we can look beyond incremental improvements in our understanding of the polar regions. Near-real time datasets of geological and biological importance at the continental scale are within our reach if we create those critical cyberinfrastructure components that allow the geosciences community to exploit existing assets and establish a common workflow for reproducible imagery-enabled science. The research objective of this proposal is to understand the biological, geological, and hydrological functioning of the polar regions at spatial scales heretofore beyond the reach of individual PIs, and to develop tools for imagery-enabled science that can be applied globally. The resulting cyberinfrastructure, which we call ICEBERG - Imagery Cyberinfrastructure and Extensible Building-Blocks to Enhance Research in the Geosciences, is an extensible system for coupling open-source image analysis tools with the use of high performance and distributed computing (HPDC) for imagery-enabled geoscience research. We propose a project to (1) develop open source image classification tools tailored to high-resolution satellite imagery of the Arctic and Antarctic to be used on HPDC resources, (2) create easy-to-use interfaces to facilitate the development and testing of algorithms for application specific geoscience requirements, (3) apply these tools through use cases that span the biological, hydrological, and geoscience needs of the polar community, (4) transfer these tools to the larger non-polar community.

卫星图像正在迅速改变我们看待地球的方式，包括我们研究北极和南极最偏远地区的能力。卫星图像可以帮助我们绘制河流网络，研究冰川流量和厚度的变化，识别岩石和土壤类型，甚至可以找到企鹅和海豹等动物。由于极地地区图像的可用性在过去十年中迅速增加，我们现在面临着一个挑战：从小型试点研究转向对地质和生物过程的泛北极或泛南极分析，需要将科学家、卫星图像和快速计算联系起来的新基础设施。这个项目被称为“冰山”——图像网络基础设施和可扩展的构建模块，以加强地球科学研究，旨在建立网络基础设施，以充分利用地球科学的卫星图像，从极地地区的研究人员开始，然后扩展到更大的社区。这项提议的更广泛影响包括培养本科生和研究生，以及年轻的研究人员和女科学家。此外，这一提议的网络基础设施所带来的科学发现将对我们预测极地地区未来动态的能力产生直接的好处，对北极和南极资源的管理至关重要。极地地球科学正处于一场革命的边缘，这场革命是由尖端分析工具、pb级高分辨率图像和不断增长的高性能计算资源的融合而实现的。有了这些工具，我们对极地地区的了解就可以超越渐进式的改进。如果我们能够创建这些关键的网络基础设施组件，使地球科学界能够利用现有资产，并为可复制的图像支持科学建立一个共同的工作流程，那么大陆尺度上的地质和生物重要性的近实时数据集就触手可及。本提案的研究目标是了解迄今为止单个pi无法达到的空间尺度上极地地区的生物、地质和水文功能，并开发可应用于全球的图像科学工具。由此产生的网络基础设施，我们称之为ICEBERG -图像网络基础设施和可扩展的构建模块，以加强地球科学研究，是一个可扩展的系统，用于将开源图像分析工具与高性能分布式计算（HPDC）相结合，用于图像支持的地球科学研究。我们提出了一个项目：(1)开发针对北极和南极高分辨率卫星图像的开源图像分类工具，用于HPDC资源；(2)创建易于使用的界面，以促进针对特定应用的地球科学要求的算法的开发和测试；(3)通过跨越极地社区的生物、水文和地球科学需求的用例应用这些工具。(4)将这些工具转移到更大的非极性社区。

项目成果

Comparing Workflow Application Designs for High Resolution Satellite Image Analysis

• DOI: 10.1016/j.future.2021.04.023
• 发表时间: 2020-10
• 期刊: ArXiv
• 作者: Aymen Al-Saadi;Ioannis Paraskevakos;B. Gonçalves;H. Lynch;S. Jha;M. Turilli

SealNet: A fully-automated pack-ice seal detection pipeline for sub-meter satellite imagery

• DOI: 10.1016/j.rse.2019.111617
• 发表时间: 2020-03-15
• 期刊: REMOTE SENSING OF ENVIRONMENT
• 影响因子: 13.5
• 作者: Goncalves, B. C.;Spitzbart, B.;Lynch, H. J.
• 通讯作者: Lynch, H. J.

SealNet 2.0: Human-Level Fully-Automated Pack-Ice Seal Detection in Very-High-Resolution Satellite Imagery with CNN Model Ensembles

• DOI: 10.3390/rs14225655
• 发表时间: 2022-11
• 期刊: Remote. Sens.
• 作者: B. Gonçalves;M. Wethington;H. Lynch

Fine-Scale Sea Ice Segmentation for High-Resolution Satellite Imagery with Weakly-Supervised CNNs

• DOI: 10.3390/rs13183562
• 发表时间: 2021-09
• 期刊: Remote. Sens.
• 作者: B. Gonçalves;H. Lynch