Leveraging Domain Adaptation for Low-Resource Geospatial Machine Learning

• URL: http://arxiv.org/abs/2107.04983v1
• Date: Sun, 11 Jul 2021 06:47:20 GMT
• Title: Leveraging Domain Adaptation for Low-Resource Geospatial Machine Learning
• Authors: Jack Lynch and Sam Wookey
• Abstract summary: Many labeled geospatial datasets are specific to certain regions, instruments, or extreme weather events. We investigate the application of modern domain-adaptation to multiple proposed geospatial benchmarks.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Machine learning in remote sensing has matured alongside a proliferation in availability and resolution of geospatial imagery, but its utility is bottlenecked by the need for labeled data. What's more, many labeled geospatial datasets are specific to certain regions, instruments, or extreme weather events. We investigate the application of modern domain-adaptation to multiple proposed geospatial benchmarks, uncovering unique challenges and proposing solutions to them.

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