Elements: Making Ice Penetrating Radar More Accessible: A tool for finding, downloading and visualizing georeferenced radargrams within the QGIS ecosystem
Elements: Making Ice Penetrating Radar More Accessible: A tool for finding, downloading and visualizing georeferenced radargrams within the QGIS ecosystem
批准号:
2209726
负责人:
Laura Lindzey
金额:
$33.07万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-07-15 至 2025-06-30
中文摘要
冰穿透雷达是研究人员用来研究冰盖和冰川的主要工具之一。通过雷达,可以看到冰的横截面,揭示冰下岩石的内部层和形状。 除此之外,这对于计算极地冰盖中有多少潜在的海平面变化以及冰盖在变暖的世界中可能有多稳定非常重要。这种类型的数据在逻辑上具有挑战性,收集成本也很高。从历史上看,个别研究小组获得了收集这些数据集的资金,然后数据大部分留在该机构内。最近有一个推动,使越来越多的数据公开可用,使相同的数据集被多个研究小组使用。然而,由于没有集中的索引,仍然很难弄清楚哪些数据可用。此外,每个小组以不同的格式发布数据,这为其使用造成了额外的障碍。该项目通过提供一个统一的工具来发现冰穿透雷达数据已经存在的地方,然后允许研究人员下载和可视化数据,从而解决了数据重用的这两个挑战。它被集成到研究界许多人已经使用的开源绘图软件中,并使非专家能够探索这些数据集。这对早期职业研究人员和跨学科工作尤其有价值。仅美国就花费了数千万美元用于直接赠款,以获取和分析极地冰层穿透雷达数据,甚至更多用于相关的基础设施和支持成本。不幸的是,这些数据中有许多没有公开发布,即使是已经发布的数据也不容易获得。在弄清楚如何定位、下载和查看数据方面涉及到大量的技术工作。该项目正在开发一种工具,既能降低使用这些数据的门槛,又能改善现有用户的工作流程。Quantitica和QGreenland已迅速成为极地研究界不可或缺的工具,使研究人员可以随时获得各种数据集。然而,冰层穿透雷达是目前不受支持的一个主要数据类别-可以看到现有勘测线的位置,以及根据其数据解释的冰层厚度图,但不容易看到雷达图本身与所有其他信息的联系。这种能力很重要,因为雷达图中包含的视觉信息远远多于简单地解释的基底高程或冰厚。该项目正在开发软件,使研究人员能够查看雷达图图像和解释的表面和基础地平线的背景下,现有的地图视图数据集在Quanetica和QGreenland。数据层显示了所有已知的冰层穿透雷达调查的位置,并根据可用性进行了颜色编码。此层支持数据发现和浏览。插件本身与数据层交互,首先下载选定的数据,然后用光标沿着雷达图和沿着地图视图同时移动,使雷达图沿着可视化,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进行评估,被认为值得支持的搜索.
英文摘要
Ice penetrating radar is one of the primary tools that researchers use to study ice sheets and glaciers. With radar, it is possible to see a cross-section of the ice, revealing internal layers and the shape of the rocks under the ice. Among other things, this is important for calculating how much potential sea level change is locked up in the polar ice sheets, and how stable the ice sheets are likely to be in a warming world. This type of data is logistically challenging and expensive to collect. Historically, individual research groups have obtained funding to collect these data sets, and then the data largely stayed within that institution. There has been a recent push to make more and more data openly available, enabling the same datasets to be used by multiple research groups. However, it is still difficult to figure out what data is available because there is no centralized index. Additionally, each group releases data in a different format, which creates an additional hurdle to its use. This project addresses both of those challenges to data reuse by providing a unified tool for discovering where ice penetrating radar data already exists, then allowing the researcher to download and visualize the data. It is integrated into open-source mapping software that many in the research community already use, and makes it possible for non-experts to explore these datasets. This is particularly valuable for early-career researchers and for enabling interdisciplinary work.The US alone has spent many tens of millions of dollars on direct grants to enable the acquisition and analysis of polar ice penetrating radar data, and even more on the associated infrastructure and support costs. Unfortunately, much of these data is not publicly released, and even the data that has been released is not easily accessible. There is significant technical work involved in figuring out how to locate, download and view the data. This project is developing a tool that will both lower the barrier to entry for using this data and improve the workflows of existing users. Quantarctica and QGreenland have rapidly become indispensable tools for the polar research community, making diverse data sets readily available to researchers. However, ice penetrating radar is a major category of data that is not currently supported – it is possible to see the locations of existing survey lines, and the ice thickness maps that have been interpreted from their data, but it is not readily possible to see the radargrams themselves in context with all of the other information. This capability is important because there is far more visual information contained in a radargram than simply its interpreted basal elevation or ice thickness. This project is developing software that will enable researchers to to view radargram images and interpreted surface and basal horizons in context with the existing map-view datasets in Quantarctica and QGreenland. A data layer shows the locations of all known ice penetrating radar surveys, color-coded based on availability. This layer enables data discovery and browsing. The plugin itself interacts with the data layer, first to download selected data, then to visualize the radargrams along with a cursor that moves simultaneously along the radargram and along the map view, making it straightforward to determine the precise geolocation of radar features.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.
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国内基金
海外基金
Scalable Learning and Optimization: High-dimensional Models and Online Decision-Making Strategies for Big Data Analysis
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项目类别:合作创新研究团队
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批准年份:2024
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负责人:姚韬
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依托单位: