Enhanced Mapping of Supraglacial Lakes Through Dual-attention Deep Neural Network
Authors: 
Haoran Wang, Jiawei Wei, Xiaoyong Gao, Dexuan Sha, Yiyun Luo, Junliu YangAuthors Info & Claims
Haoran Wang, Jiawei Wei, Xiaoyong Gao, Dexuan Sha, Yiyun Luo, Junliu YangAuthors Info & ClaimsArticle No.: 17, Pages 1 - 4
Abstract
Supraglacial lakes in the Arctic undergo seasonal and glacial-activity-induced changes, providing profound insights into ice dynamics and climate changes in these sensitive regions. However, the morphological complexity of these lakes, compounded by the environmental obstructions like clouds and slush fields, poses significant challenges to accurate lake detection. The 31st ACM SIGSPATIAL 2023 initiated a competition, GISCUP 2023, focusing on supraglacial lake detection based on multipart, multi-temporal satellite imagery. This paper, distinguished as the 3rd place winner, introduces a pioneering dual-attention U-net algorithm. This approach synergizes deep learning with spectral and spatial knowledge, ensuring a streamlined pipeline structure that upholds methodological soundness and yields satisfying results.
References
[1]
Prajjwal K. Panday, Henry Bulley, Umesh Haritashya and Bardan Ghimire Supraglacial Lake Classification in the Everest Region of Nepal Himalaya. Springer Netherlands, Dordrecht, 2011.
[2]
M. Krawczynski, M. Behn, Sarah Das and I. Joughin. 2007. Constraints on melt-water flux through the West Greenland ice-sheet: modeling of hydro- fracture drainage of supraglacial lakes. In Proceedings of the AGU Fall Meeting 0474.
[3]
Jennifer F. Arthur, Chris Stokes, Stewart S. R. Jamieson, J. Rachel Carr and Amber A. Leeson. Recent understanding of Antarctic supraglacial lakes using satellite remote sensing. Progress in Physical Geography: Earth and Environment, 44, 6 (2020), 837--869.
[4]
A. Malin. Johansson and Ian. A. Brown. Adaptive Classification of Supra-Glacial Lakes on the West Greenland Ice Sheet. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 6, 4 (2013), 1998--2007.
[5]
Di Jiang, Xinwu Li, Ke Zhang, Sebastián Marinsek, Wen Hong and Yirong Wu. Automatic Supraglacial Lake Extraction in Greenland Using Sentinel-1 SAR Images and Attention-Based U-Net. Remote Sensing, 14, 19 (2022), 4999.
[6]
Ronneberger, Olaf, Philipp Fischer and Thomas Brox. 2015. U-Net: Convolutional Networks for Biomedical Image Segmentation. In Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 234--241.
[7]
Sanghyun Woo, Jongchan Park, Joon-Young Lee and In So Kweon. 2018. CBAM: Convolutional Block Attention Module. In Proceedings of the Computer Vision - ECCV 2018, 3--19.
[8]
Nabila Abraham and Naimul Mefraz Khan. 2019. A Novel Focal Tversky Loss Function With Improved Attention U-Net for Lesion Segmentation. In Proceedings of the 2019 IEEE 16th International Symposium on Biomedical Imaging 683--687.
Index Terms
- Enhanced Mapping of Supraglacial Lakes Through Dual-attention Deep Neural Network
Recommendations
Exploring GeoAI Methods for Supraglacial Lake Mapping on Greenland Ice Sheet
SIGSPATIAL '23: Proceedings of the 31st ACM International Conference on Advances in Geographic Information SystemsThe ACM SIGSPATIAL Cup 2023 proposed the challenge to identify and map supraglacial lakes in Greenland in satellite imagery. The peculiarities of supraglacial lakes pose a hard problem for semantic segmentation and object detection tasks because the ...
A novel application of DUCK-Net for extracting supraglacial lakes in Greenland
SIGSPATIAL '23: Proceedings of the 31st ACM International Conference on Advances in Geographic Information SystemsThis paper presents a new application of the DUCK-Net convolutional neural network for image segmentation to identify supraglacial lakes on the Greenland ice sheet. The model presented was created as part of the 12th SIGSPATIAL Cup Competition and ...
Geo-knowledge-informed Deep Learning for Auto-identification of Supraglacial Lakes on the Greenland Ice Sheet from Satellite Imagery
SIGSPATIAL '23: Proceedings of the 31st ACM International Conference on Advances in Geographic Information SystemsMelting glaciers are indicators of global climate change. The formation and dynamics of supraglacial lakes on the Greenland's ice sheet, which appear during the summer melt season, are of particular interest due to their impact on ice dynamics. Detecting ...
Comments
Information & Contributors
Information
Published In
November 2023
686 pages
ISBN:9798400701689
DOI:10.1145/3589132
- General Chairs:
- Maria Luisa Damiani,
- Matthias Renz,
- Program Chairs:
- Ahmed Eldawy,
- Peer Kröger,
- Mario A Nascimento
Copyright © 2023 ACM.
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].
Sponsors
Publisher
Association for Computing Machinery
New York, NY, United States
Publication History
Published: 22 December 2023
Check for updates
Author Tags
Qualifiers
- Short-paper
Conference
SIGSPATIAL '23
Sponsor:
SIGSPATIAL '23: 31st ACM International Conference on Advances in Geographic Information Systems
November 13 - 16, 2023
Hamburg, Germany
Acceptance Rates
Overall Acceptance Rate 257 of 1,238 submissions, 21%
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 62Total Downloads
- Downloads (Last 12 months)50
- Downloads (Last 6 weeks)1
Reflects downloads up to 27 Jan 2025
Other Metrics
Citations
View Options
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in