Paper Citation Record · LEDGER

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection

As of 11 August 2026, this Paper Citation Record lists 30 of 30 outbound references and 0 inbound Pith citation observations for arXiv:2506.11544.

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

pith.paper-citation-record.v1
2506.11544 v1

Coverage vector

measured 30 of 30 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:09:22.045744Z

measured 30 of 30 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

30 of 30 outbound references displayed

verified exact1
verified fuzzy17
unresolved12
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation a7659ba3-e110-4084-b170-a97fbdcfd6c0 · outbound

This paper cites A transformer-based siamese network for change detection.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection A transformer-based siamese network for change detection

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:25.995946Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 513f6407-89ed-4110-9eca-fbb8eae83643 · outbound

This paper cites End-to- end object detection with transformers.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection End-to- end object detection with transformers

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:25.576057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c9409b81-49bf-464d-9596-005da1f59fe0 · outbound

This paper cites Remote sensing im- age change detection with transformers.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Remote sensing im- age change detection with transformers

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:25.170701Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation db7dcca5-5350-4180-bc86-7dab5ee28377 · outbound

This paper cites Semantic decoupled representation learning for re- mote sensing image change detection.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Semantic decoupled representation learning for re- mote sensing image change detection

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.953418Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 883539ae-b1a7-4221-92bd-47067f76f8a3 · outbound

This paper cites A simple framework for contrastive learning of visual representations.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection A simple framework for contrastive learning of visual representations

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:19.654430Z

Source-reported events for the cited work

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Observation 3785c3b1-ee6c-4cd9-87a7-6b9ba929f02e · outbound

This paper cites Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Satmae: Pre-training transformers for tem- poral and multi-spectral satellite imagery

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.836019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 30f56fc1-e7a9-4236-b539-0cb78b0c472b · outbound

This paper cites A Change Detection Reality Check.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection A Change Detection Reality Check

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:19.911142Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4eb5210-1b42-4b8b-a23c-0318c74f94d6 · outbound

This paper cites an unresolved cited work.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Unresolved cited work

Reference 8

Resolution: unresolved; raw_fallback, observed 2026-08-07T04:09:24.687313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7f34212c-e498-4cb3-822d-e02d00b27c42 · outbound

This paper cites Fully convolutional siamese networks for change detection.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Fully convolutional siamese networks for change detection

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.522978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation cd6b2f74-3b8e-4a55-90a4-f981c7b8ba52 · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.172070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 841a635e-ba0d-464a-b610-6bf0412f9935 · outbound

This paper cites Changer: Feature inter- action is what you need for change detection.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Changer: Feature inter- action is what you need for change detection

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.367592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fc040dc1-91b5-43ae-8084-a2d56f99c139 · outbound

This paper cites A simple, strong baseline for building damage detection on the xBD dataset.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection A simple, strong baseline for building damage detection on the xBD dataset

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.413478Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 20ada27c-bf64-43d8-9358-0a9b1577e045 · outbound

This paper cites Creating xbd: A dataset for assessing building damage from satellite imagery.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Creating xbd: A dataset for assessing building damage from satellite imagery

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.224358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d24f6860-6a87-4dbf-bebe-809bb6bf8538 · outbound

This paper cites Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Continuous Urban Change Detection from Satellite Image Time Series with Temporal Feature Refinement and Multi-Task Integration

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-08-07T04:09:22.243792Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 91704b2c-c423-4481-bcec-cdf2146bb0ce · outbound

This paper cites Masked autoencoders are scalable vision learners.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Masked autoencoders are scalable vision learners

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.708964Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a394a5-c59e-4f24-94f5-9a86a47c80af · outbound

This paper cites Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.797849Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5cc2afdb-5bfe-4ae4-a9d2-4fd59bb97311 · outbound

This paper cites Supervised contrastive learning.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Supervised contrastive learning

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.871991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3df6ab7-22c6-40d5-aaa8-6bb12a33090a · outbound

This paper cites Vision Foundation Models in Remote Sensing: A Survey.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Vision Foundation Models in Remote Sensing: A Survey

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:20.959735Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b69209a4-6211-4afe-9145-6feff263adeb · outbound

This paper cites Change- aware sampling and contrastive learning for satellite images.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Change- aware sampling and contrastive learning for satellite images

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:24.013347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation a72ac654-70fb-404f-b2c7-c2ad1c2f2335 · outbound

This paper cites Seasonal contrast: Un- supervised pre-training from uncurated remote sensing data.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Seasonal contrast: Un- supervised pre-training from uncurated remote sensing data

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:23.839455Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f180ed0a-1c2b-474d-87d9-cc325d1c27d2 · outbound

This paper cites PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:21.220635Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9bdd4ee-27d1-40fe-b83b-c5ccbfeb0a83 · outbound

This paper cites Pytorch: An im- perative style, high-performance deep learning library.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Pytorch: An im- perative style, high-performance deep learning library

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:23.659545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e5dae930-dece-4689-adab-93911710aa4b · outbound

This paper cites Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Scale-mae: A scale-aware masked autoencoder for multiscale geospatial representation learning

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:23.460741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2c2e7ccc-1cef-42b6-8e14-735da08a41c9 · outbound

This paper cites Ravæn: unsupervised change detection of extreme events using ml on-board satel- lites.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Ravæn: unsupervised change detection of extreme events using ml on-board satel- lites

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:23.301801Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f3670b2e-bde3-44ed-8d75-a4d33201e43c · outbound

This paper cites Recent Advances in Autoencoder-Based Representation Learning.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Recent Advances in Autoencoder-Based Representation Learning

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:21.594578Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f81213d4-161b-4e35-b38b-f7794b5eb38f · outbound

This paper cites Foundation Models for Remote Sensing and Earth Observation: A Survey.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Foundation Models for Remote Sensing and Earth Observation: A Survey

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T04:09:21.710035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c349212d-891a-4f68-9359-6767e57aea15 · outbound

This paper cites Neural plasticity-inspired foundation model for observing the earth crossing modalities.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Neural plasticity-inspired foundation model for observing the earth crossing modalities

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:23.125226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8a9f45f4-524b-4ea5-80a7-7a87a20963ef · outbound

This paper cites Unsupervised flood detection on sar time series us- ing variational autoencoder.International Journal of Applied Earth Observation and Geoinformation , 126:103635, 2024.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Unsupervised flood detection on sar time series us- ing variational autoencoder.International Journal of Applied Earth Observation and Geoinformation , 126:103635, 2024

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:22.859907Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3514d7f4-1a0e-4308-97b6-ce751ddd7031 · outbound

This paper cites Building damage assessment for rapid dis- aster response with a deep object-based semantic change de- tection framework: From natural disasters to man-made dis- asters.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Building damage assessment for rapid dis- aster response with a deep object-based semantic change de- tection framework: From natural disasters to man-made dis- asters

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:22.666536Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 27886750-ddd2-4898-82f3-f0e8819ba4db · outbound

This paper cites Towards trans- ferable building damage assessment via unsupervised single- temporal change adaptation.

Leveraging Satellite Image Time Series for Accurate Extreme Event Detection Towards trans- ferable building damage assessment via unsupervised single- temporal change adaptation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T04:09:22.452901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Pith citing papers

No inbound Pith citation observations are available.