What's New: Past Year

Resources feed

  1. Visualizing Glacier/Ocean Change

    21 May 2024 | Contributor(s):: Sophie Goliber, John Erich Christian

    A simple 1-D glacier model to teach students about glacier/ocean changes.

  2. Evaluating Machine Learning and Statistical Models for Greenland Bed Topography

    15 May 2024 | Contributor(s):: Homayra Alam, Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Jianwu Wang, Sikan Li, Mathieu Morlighem, Omar Faruque

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bed topography in Greenland using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for understanding ice sheet...

  3. Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography

    15 May 2024 | Contributor(s):: Homayra Alam, Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Sikan Li, Mathieu Morlighem, Omar Faruque, Jianwu Wang

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  4. REU_Final_Presentation

    15 May 2024 | Contributor(s):: Homayra Alam, Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Omar Faruque, Sikan Li, Mathieu Morlighem

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  5. Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography

    15 May 2024 | Contributor(s):: Homayra Alam, Jianwu Wang, Tartela Tabassum, Katherine Yi, Angelina Dewar, Jason Lu, Ray Chen, Omar Faruque, Mathieu Morlighem, Sikan LI

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  6. Discovery of multi-domain spatiotemporal associations

    26 Apr 2024 | Contributor(s):: Prathamesh Walkikar, Lei Shi, Bayu Adhi Tama, Vandana Janeja

    This paper focuses on the discovery of unusual spatiotemporal associations across multiple phenomena from distinct application domains in a spatial neighborhood where each phenomenon is represented by anomalies from the domain. Such an approach can facilitate the discovery of interesting links...

  7. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science

    23 Apr 2024 | Contributor(s):: Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel

    Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE,...

  8. Metrics for the Quality and Consistency of Ice Layer Annotations

    23 Apr 2024 | Contributor(s):: Naomi Tack, Bayu Adhi Tama, Atefah Jebeli, Vandana P. Janeja, Don Engel, Rebecca Williams

    Naomi Tack, Bayu Adhi Tama, Atefeh Jebeli, Vandana P. Janeja, Don Engel, and Rebecca Williams. 2023. Metrics for the Quality and Consistency of Ice Layer Annotations. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA....

  9. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams

    23 Apr 2024 | Contributor(s):: Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, Don Engel

    Naomi Tack, Rebecca Williams, Nicholas Holschuh, Sharad Sharma, and Don Engel. 2023. Visualizing the Greenland Ice Sheet in VR using Immersive Fence Diagrams. In Practice and Experience in Advanced Research Computing, ACM, Portland OR USA, 429–432. DOI:...

  10. Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.

    23 Apr 2024 | Contributor(s):: Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel

    Tack, Naomi, Holschuh, Nicholas, Sharma, Sharad, Williams, Rebecca, and Engel, Don. “Initial Development of a WebXR Platform for Ice Penetrating Radar Data, to Improve our Understanding of Polar Ice Sheets.” Poster at the AGU23 meeting, IN43B-0627, December 2023 

  11. AskICE-D: A querying tool for the ICE-D project

    15 Feb 2024 | Contributor(s):: Joseph P Tulenko, Greg Balco, jason briner, Sophie Goliber

    A tool that helps users build and send SQL queries to the ICE-D database and dynamically returns the query results.

  12. THEPORE

    06 Feb 2024 | Contributor(s):: Gilda Maria Currenti, Rosalba Napoli, Santina Chiara Stissi

    THEPORE (THErmo-POro-Elastic solutions) is an open source software to perform forward and inverse modelling of the ground displacements induced by thermo-poro-elastic sources. The software, implemented in the MATLAB environment, offers a library of analytical and semi-analytical solutions to...

  13. Ice Sheet Simulation Compliance Checker

    19 Jan 2024 | Contributor(s):: Renette Jones-Ivey, sophie nowicki, Sophie Goliber

    Checks the compliance of a simulation dataset according criteria for ISMIP6

  14. proxy VIIRS polar observations from Aqua/Terra MODIS data (bands: I5, M12-16)

    23 Nov 2023 | Contributor(s):: Dimitry Sushon

    This example dataset from 11/14/2023 was produced from Aqua/Terra L1 MODIS observations over the Antarctic coast and over Siberia/Arctic Ocean.The input granules were processed with a VIIRS L1 Generator application to apply bow-tie effect and re-project the data from MODIS to VIIRS spatial...

  15. GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation

    16 Oct 2023 | Contributor(s):: Emma MacKie

    GStatSim is a Python package specifically designed for geostatistical interpolation and simulation. These tools are part of our ongoing effort to develop and adapt open-access geostatistical functions.

  16. Code Demos for "Regression on Ice" Lecture Notes

    10 Oct 2023 | Contributor(s):: Noah J Bergam

    Notebooks with visualizations of some basic regression / machine learning concepts for glaciology

  17. Lava Extrusion Geometry Dataset

    02 Oct 2023 | Contributor(s):: Amy Myers, Claire Ellen Harnett, Eoghan Holohan, Thomas Walter, Michael Heap

    This dataset aims to collate data of the geometry of viscous lava extrusions. The dataset contains 323 entries of extrusion height, width, and magma composition listed for all entries.Further information (where available) includes spine length, a second diameter measurement, extrusion...

  18. Regression on Ice: Function approximation for the mathematically-inclined glaciologist

    17 Sep 2023 | Contributor(s):: Noah J Bergam

    Modern satellite-based analysis of the ice sheets presents a profound statistical-geometric problem: how do we make sense of scattered, noisy measurements of vast, steadily evolving surfaces like the Greenland and Antarctic ice sheets? In these lecture notes, I attempt to provide the...