2 Search Results for "Arundel, Samantha T."

Document
DOI: 10.4230/LIPIcs.GIScience.2025.18
U-Prithvi: Integrating a Foundation Model and U-Net for Enhanced Flood Inundation Mapping

Authors: Vit Kostejn, Yamil Essus, Jenna Abrahamson, and Ranga Raju Vatsavai

Published in: LIPIcs, Volume 346, 13th International Conference on Geographic Information Science (GIScience 2025)

Abstract
In recent years, large pre-trained models, commonly referred to as foundation models, have become increasingly popular for various tasks leveraging transfer learning. This trend has expanded to remote sensing, where transformer-based foundation models such as Prithvi, msGFM, and SatSwinMAE have been utilized for a range of applications. While these transformer-based models, particularly the Prithvi model, exhibit strong generalization capabilities, they have limitations on capturing fine-grained details compared to convolutional neural network architectures like U-Net in segmentation tasks. In this paper, we propose a novel architecture, U-Prithvi, which combines the strengths of the Prithvi transformer with those of U-Net. We introduce a RandomHalfMaskLayer to ensure balanced learning from both models during training. Our approach is evaluated on the Sen1Floods11 dataset for flood inundation mapping, and experimental results demonstrate better performance of U-Prithvi over both individual models, achieving improved performance on out-of-sample data. While this principle is illustrated using the Prithvi model, it is easily adaptable to other foundation models.
Cite as

Vit Kostejn, Yamil Essus, Jenna Abrahamson, and Ranga Raju Vatsavai. U-Prithvi: Integrating a Foundation Model and U-Net for Enhanced Flood Inundation Mapping. In 13th International Conference on Geographic Information Science (GIScience 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 346, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kostejn_et_al:LIPIcs.GIScience.2025.18,
  author =	{Kostejn, Vit and Essus, Yamil and Abrahamson, Jenna and Vatsavai, Ranga Raju},
  title =	{{U-Prithvi: Integrating a Foundation Model and U-Net for Enhanced Flood Inundation Mapping}},
  booktitle =	{13th International Conference on Geographic Information Science (GIScience 2025)},
  pages =	{18:1--18:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-378-2},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{346},
  editor =	{Sila-Nowicka, Katarzyna and Moore, Antoni and O'Sullivan, David and Adams, Benjamin and Gahegan, Mark},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GIScience.2025.18},
  URN =		{urn:nbn:de:0030-drops-238479},
  doi =		{10.4230/LIPIcs.GIScience.2025.18},
  annote =	{Keywords: GeoAI, flood mapping, foundation model, U-Net, Prithvi}
}
Document
Short Paper
DOI: 10.4230/LIPIcs.GISCIENCE.2018.59
The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms (Short Paper)

Authors: Gaurav Sinha, Samantha T. Arundel, Torsten Hahmann, E. Lynn Usery, Kathleen Stewart, and David M. Mark

Published in: LIPIcs, Volume 114, 10th International Conference on Geographic Information Science (GIScience 2018)

Abstract
The landform reference ontology (LFRO) formalizes ontological distinctions underlying naïve geographic cognition and reasoning about landforms. The LFRO taxonomy is currently based only on form-based distinctions. In this significantly revised version, several new categories have been added to explicate ontological distinctions related to material-spatial dependence and physical support. Nuances of common natural language landform terms and implications for their mapping are discussed.
Cite as

Gaurav Sinha, Samantha T. Arundel, Torsten Hahmann, E. Lynn Usery, Kathleen Stewart, and David M. Mark. The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms (Short Paper). In 10th International Conference on Geographic Information Science (GIScience 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 114, pp. 59:1-59:7, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2018)

Copy BibTex To Clipboard

@InProceedings{sinha_et_al:LIPIcs.GISCIENCE.2018.59,
  author =	{Sinha, Gaurav and Arundel, Samantha T. and Hahmann, Torsten and Usery, E. Lynn and Stewart, Kathleen and Mark, David M.},
  title =	{{The Landform Reference Ontology (LFRO): A Foundation for Exploring Linguistic and Geospatial Conceptualization of Landforms}},
  booktitle =	{10th International Conference on Geographic Information Science (GIScience 2018)},
  pages =	{59:1--59:7},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-083-5},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{114},
  editor =	{Winter, Stephan and Griffin, Amy and Sester, Monika},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.GISCIENCE.2018.59},
  URN =		{urn:nbn:de:0030-drops-93873},
  doi =		{10.4230/LIPIcs.GISCIENCE.2018.59},
  annote =	{Keywords: landform, reference ontology, terrain reasoning, dependence, support}
}
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