Paper Citation Record · LEDGER

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation

As of 18 August 2026, this Paper Citation Record lists 40 of 40 outbound references and 0 inbound Pith citation observations for arXiv:2608.02315.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2608.02315 v1

Coverage vector

measured 40 of 40 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:29:32.296040Z

measured 40 of 40 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

40 of 40 outbound references displayed

verified exact0
verified fuzzy0
unresolved39
parse uncertain0
malformed identifier1
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 81d62230-cc36-4e9c-bf4a-dbf288aedcc6 · outbound

This paper cites an unresolved cited work.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Unresolved cited work

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:27.626016Z

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Observation 5cd9a0eb-994b-4ad6-be5b-e906b1c76345 · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:27.705446Z

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Observation b402cc72-4399-4d1e-b32f-536c7c8e32da · outbound

This paper cites In: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition workshops.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF conference on computer vision and pattern recog- nition workshops

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:27.760673Z

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Observation d576ebe6-35c7-4e99-af58-61a3cd690da0 · outbound

This paper cites A global multi-temporal satellite dataset for rapid flood mapping.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation A global multi-temporal satellite dataset for rapid flood mapping

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:27.909143Z

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Observation e7225dee-e54b-4700-98d1-058b283d9916 · outbound

This paper cites AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation AlphaEarth Foundations: An embedding field model for accurate and efficient global mapping from sparse label data

Reference 5

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Observation 38f8a018-69c4-4681-9ca7-281b3bc8ef90 · outbound

This paper cites In: Proceedings of the European conference on computer vision (ECCV).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the European conference on computer vision (ECCV)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.144144Z

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Observation c4edfe86-17c0-4075-94b1-e7b2a8bed67f · outbound

This paper cites Directorate Space, Security and Migration, European Commission Joint Research Centre (EC JRC) (2012–2025),https://mapping.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Directorate Space, Security and Migration, European Commission Joint Research Centre (EC JRC) (2012–2025),https://mapping

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.257270Z

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Observation 34c127f5-5616-4c73-971d-5437d475eb58 · outbound

This paper cites an unresolved cited work.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.376705Z

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Observation 84d114f6-88eb-4873-8cde-c01244f102fc · outbound

This paper cites EarthShift: a benchmark for measuring robustness to real-world distribution shifts in Earth observation.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation EarthShift: a benchmark for measuring robustness to real-world distribution shifts in Earth observation

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.484774Z

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Observation bddc565f-603e-4ca0-ad71-0e433029367e · outbound

This paper cites IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing15, 2341–2356 (2022).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing15, 2341–2356 (2022)

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.570578Z

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Observation 7964c043-3e88-4910-bf9d-ebe806f7faf1 · outbound

This paper cites OpenTopography (2021).https://doi.org/10.5270/ESA-c5d3d65.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation OpenTopography (2021).https://doi.org/10.5270/ESA-c5d3d65

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.685627Z

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Observation 7ddd469f-fcac-4470-a778-4a8be82e5d38 · outbound

This paper cites TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation TESSERA: Temporal Embeddings of Surface Spectra for Earth Representation and Analysis

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.828488Z

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Observation 8206af83-d97b-4de7-bf33-8523ed2f611b · outbound

This paper cites In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2025).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: IEEE International Geoscience and Remote Sensing Symposium (IGARSS) (2025)

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:28.990948Z

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Observation 0722d58f-81df-4fb1-862c-ec43a791fbbf · outbound

This paper cites an unresolved cited work.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.124180Z

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Unavailable: canonical work link unavailable.

Observation b2301d9c-4ab5-4677-8e51-b538280a4d1e · outbound

This paper cites International Journal of Applied Earth Observation and Geoinformation117, 103197 (2023).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation International Journal of Applied Earth Observation and Geoinformation117, 103197 (2023)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.166689Z

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Unavailable: canonical work link unavailable.

Observation 6b91a28e-969a-42b8-b481-c7dc1e66251f · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.312778Z

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Observation 7f5dced5-4297-461f-b48b-c62475c9fe0a · outbound

This paper cites an unresolved cited work.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Unresolved cited work

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.421268Z

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Observation 4c8b8b0a-3f27-4067-b853-397cba0491d5 · outbound

This paper cites Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.504105Z

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Unavailable: canonical work link unavailable.

Observation 08782732-fcdc-41f0-ae61-49ecb923da5b · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.674748Z

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Observation 0bde7021-edd2-45b1-ab69-987b6642a7d8 · outbound

This paper cites Sensors18(9), 2915 (2018).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Sensors18(9), 2915 (2018)

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.784540Z

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Unavailable: canonical work link unavailable.

Observation b3daf128-2739-435e-bec8-23bee0601f5d · outbound

This paper cites In: Proceedings of the IEEE/CVF International Conference on Computer Vision.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF International Conference on Computer Vision

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:29.918251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07b9f58c-8884-4da0-a515-f04079e78778 · outbound

This paper cites In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.022320Z

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Unavailable: canonical work link unavailable.

Observation 59a1b0e4-8708-4d43-9bbd-00f44f76f02b · outbound

This paper cites In: International Conference on Learning Representations (2019).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: International Conference on Learning Representations (2019)

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.167619Z

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Unavailable: canonical work link unavailable.

Observation 73f744ef-9142-4c7d-9a7e-c8be8ed62f85 · outbound

This paper cites Zenodo (2021).https://doi.org/10.5281/ zenodo.5205674 GEOID-Flood: Multi-Modal Flood Segmentation Benchmark 17.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Zenodo (2021).https://doi.org/10.5281/ zenodo.5205674 GEOID-Flood: Multi-Modal Flood Segmentation Benchmark 17

Reference 24

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Observation 835b0245-6fff-4b2b-b501-82e556c386a0 · outbound

This paper cites Natural Hazards and Earth System Sciences9(2), 303–314 (2009).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Natural Hazards and Earth System Sciences9(2), 303–314 (2009)

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.481617Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0895849b-03f5-4276-ab79-d2531a8c278d · outbound

This paper cites Scientific Reports11, 7249 (2021).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Scientific Reports11, 7249 (2021)

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.673460Z

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Observation 6ffb559f-1c47-44b7-bb6a-f88be7cd017c · outbound

This paper cites IEEE Access10, 96774–96787 (2022).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation IEEE Access10, 96774–96787 (2022)

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.836760Z

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Observation ca1d6da6-ff73-44c7-abf9-bd4adb8a9038 · outbound

This paper cites Big Earth Data9(3), 412–438 (2025).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Big Earth Data9(3), 412–438 (2025)

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:30.942811Z

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Unavailable: canonical work link unavailable.

Observation 541ddae2-e2b6-4ae7-949f-926377f43bbf · outbound

This paper cites Nature540(7633), 418–422 (2016).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Nature540(7633), 418–422 (2016)

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.108261Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7b59dc57-4fc3-4bd7-86f5-a9f10f8c2b66 · outbound

This paper cites Scientific Reports13(1), 20316 (2023).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Scientific Reports13(1), 20316 (2023)

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.212280Z

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Observation a51ccb08-50f3-4923-82d6-3c7b8b379eb6 · outbound

This paper cites IEEE Access9, 89644–89654 (2021).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation IEEE Access9, 89644–89654 (2021)

Reference 31

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Observation 3711cbb1-67f0-4b18-8bcb-b39f9115d6b5 · outbound

This paper cites arXiv preprint arXiv:2603.02386 (2026),https://arxiv.org/abs/2603.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation arXiv preprint arXiv:2603.02386 (2026),https://arxiv.org/abs/2603

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.479026Z

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Observation 61965204-444e-409f-8f3a-6f0827c17162 · outbound

This paper cites In: International Conference on Medical image computing and computer-assisted intervention.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation In: International Conference on Medical image computing and computer-assisted intervention

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.601990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b367de7-f410-452b-98ea-e5eb27cbba15 · outbound

This paper cites ISPRS Journal of Photogrammetry and Remote Sensing212, 440–453 (2024).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation ISPRS Journal of Photogrammetry and Remote Sensing212, 440–453 (2024)

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.748848Z

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Observation ebf401c3-aba2-4e14-9a1d-10bb7c1bd97f · outbound

This paper cites Satellite data access and processing platform,https:// www.sentinel-hub.com.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Satellite data access and processing platform,https:// www.sentinel-hub.com

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.816587Z

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Unavailable: canonical work link unavailable.

Observation 82510700-1ea7-4384-bcfb-b2ef8dede263 · outbound

This paper cites International Journal of Remote Sensing37(13), 2990–3004 (2016).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation International Journal of Remote Sensing37(13), 2990–3004 (2016)

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.900808Z

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Observation 46333318-aad6-4ed0-97fe-2926dd7465e5 · outbound

This paper cites IEEE Geoscience and Re- mote Sensing Magazine11(3), 98–106 (2023).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation IEEE Geoscience and Re- mote Sensing Magazine11(3), 98–106 (2023)

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:31.988559Z

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Unavailable: canonical work link unavailable.

Observation dcdcb8a9-601d-4514-a055-babea5f195e7 · outbound

This paper cites Remote Sensing of Environment322, 114694 (2025).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation Remote Sensing of Environment322, 114694 (2025)

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:32.079747Z

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Unavailable: canonical work link unavailable.

Observation 49340392-ba7a-456e-afc7-2a0d2e9251c5 · outbound

This paper cites arXiv preprint arXiv:2403.15356 (2024).

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation arXiv preprint arXiv:2403.15356 (2024)

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:32.183930Z

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Observation ed96279d-73fb-4465-a0af-899895c1bc4c · outbound

This paper cites International Journal of Applied Earth Observation and Geoinformation116, 103132 (2023) 18 G.

GEOID-Flood: A Large-Scale Multi-Modal Benchmark Dataset for Flood Segmentation International Journal of Applied Earth Observation and Geoinformation116, 103132 (2023) 18 G

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-04T09:29:32.296040Z

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Pith citing papers

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