Utilizing Machine Learning and Anomaly Detection to Detect Skewed SWESARR Data and Understand How Snow Water Equivalent Changes Spatially-Reference-Cited by-同舟云学术

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Utilizing Machine Learning and Anomaly Detection to Detect Skewed SWESARR Data and Understand How Snow Water Equivalent Changes Spatially

Published:2024-07-07 Issue: Volume: Page:1878-1882
ISSN:
Container-title:IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium
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Author:

Jain Aditya¹,Joseph Alicia²,Himmele Gabriela³,Pinder Nicholas⁴,Ofekeze Evi²,Vuyovich Carrie²,Espada Kari⁵,Conway Joy⁶,Miller Ryan⁷

Affiliation:

1. The Harker School

2. NASA Goddard Space Flight Center

3. West Virginia University

4. University of South Florida

5. Virginia Space Grant Consortium

6. Plum Point Middle School

7. Arlington Tech Arlington Public Schools

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10640349/10640352/10641193.pdf?arnumber=10641193

Reference8 articles.

1. NASA's snowex campaign: Observing seasonal snow in a forested environment

2. Performance of Swesarr's Multi-Frequency Dual-Polarimetry Synthetic Aperture Radar During Nasa'S Snowex Airborne Campaign

3. Forecasting Time Series Albedo Using NARnet Based on EEMD Decomposition

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