Paper Citation Record · LEDGER

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model

As of 18 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2508.11739.

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

pith.paper-citation-record.v1
2508.11739 v1

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:53:36.374974Z

measured 37 of 37 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-26T09:20:16.017739Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T09:59:44.671845Z

Reference resolution

36 of 36 outbound references displayed

verified exact0
verified fuzzy29
unresolved7
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bf7e7e75-723d-4016-9139-086ffb7db315 · outbound

This paper cites A foundation model for the earth system.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model A foundation model for the earth system

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:45.699336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a057aa72-dffb-4ae0-8f17-d239fc39f549 · outbound

This paper cites Random forests.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Random forests

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:45.384578Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 49588923-f606-4384-801a-d318959f73c3 · outbound

This paper cites Brown, Michal R.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Brown, Michal R

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:45.025696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9168d1ba-1376-4f27-86e9-3bf7e1474705 · outbound

This paper cites Artificial neural networks for land-cover classification and mapping.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Artificial neural networks for land-cover classification and mapping

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:44.707604Z

Source-reported events for the cited work

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Observation 723e0a6f-022b-4f2d-8895-b10cce87a41d · outbound

This paper cites Global land cover classifications at 8 km spatial resolution: The use of training data derived from landsat imagery in decision tree classifiers.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Global land cover classifications at 8 km spatial resolution: The use of training data derived from landsat imagery in decision tree classifiers

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:44.383424Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 14ee7ab2-0d50-4f35-b069-1d80ab823eca · outbound

This paper cites Bert: Pre-training of deep bidirectional transformers for language understanding.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Bert: Pre-training of deep bidirectional transformers for language understanding

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-05T19:53:32.402493Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6772dbe9-5a41-4bee-bb42-352bfd9c7ace · outbound

This paper cites Geovex: Geospatial vectors with hexagonal convolutional autoencoders.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Geovex: Geospatial vectors with hexagonal convolutional autoencoders

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:44.010957Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1eea75e8-ff43-4689-b3ad-8e4936c50b8b · outbound

This paper cites Decision tree classification of land cover from remotely sensed data.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Decision tree classification of land cover from remotely sensed data

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:43.679260Z

Source-reported events for the cited work

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Observation c789ee09-c142-430a-8fbd-e391cd4c185e · outbound

This paper cites Random forests for land cover classification.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Random forests for land cover classification

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:43.385734Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b4eb1c66-d5d5-42ed-be18-0a844352c5ea · outbound

This paper cites Google satellite embedding v1, 2025.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Google satellite embedding v1, 2025

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:43.032283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 501ae407-d7fd-4bc3-bf72-03975405369b · outbound

This paper cites Satellite Embedding V1, 2025.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Satellite Embedding V1, 2025

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:42.723938Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b3daffe6-3249-4197-b16a-e17aca07d2a4 · outbound

This paper cites The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model The Elements of Statistical Learning: Data Mining, Inference, and Prediction

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:42.529822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8b326a87-e194-47c0-987a-bb73d338288e · outbound

This paper cites Artificial neural network classification using a minimal training set- comparison to conventional supervised classification.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Artificial neural network classification using a minimal training set- comparison to conventional supervised classification

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:42.281155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation b8cb6db5-5c87-4191-b69c-d3f76f7d7c83 · outbound

This paper cites An assessment of support vector machines for land cover classification.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model An assessment of support vector machines for land cover classification

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:41.954487Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 707de96b-42b8-4737-964e-715f08034cbf · outbound

This paper cites TerraMind: Large-Scale Generative Multimodality for Earth Observation.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model TerraMind: Large-Scale Generative Multimodality for Earth Observation

Reference 15

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Source-reported events for the cited work

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Observation 24c8bad6-da64-4bf0-bfb3-0e71ea1f5199 · outbound

This paper cites Tile2vec: Unsupervised representation learning for spatially distributed data.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Tile2vec: Unsupervised representation learning for spatially distributed data

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:41.728767Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 40dd5308-555c-4c18-9366-1e83642d4409 · outbound

This paper cites Lightgbm: A highly efficient gradient boosting decision tree.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Lightgbm: A highly efficient gradient boosting decision tree

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:41.350029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e869ae13-95dd-4fd5-9f61-961bec527b31 · outbound

This paper cites Satclip: Global, general-purpose location embeddings with satellite imagery.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Satclip: Global, general-purpose location embeddings with satellite imagery

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:40.984100Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2e21dacd-a374-4eae-8438-aaae725bbf17 · outbound

This paper cites Landfire technical documentation.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Landfire technical documentation

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:40.576595Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2f2b1c93-546c-48d7-bbce-57ae966d3ca7 · outbound

This paper cites 2020 existing vegetation type layer, landfire 2.0.0, u.s.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model 2020 existing vegetation type layer, landfire 2.0.0, u.s

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:40.262155Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 1fc6e954-332f-431f-9275-363516c91970 · outbound

This paper cites On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model On the Opportunities and Challenges of Foundation Models for Geospatial Artificial Intelligence

Reference 21

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Source-reported events for the cited work

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Observation dec8216c-e296-42c6-b5f5-b9796cfa2b48 · outbound

This paper cites Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Multi-Scale Representation Learning for Spatial Feature Distributions using Grid Cells

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-05T19:53:34.548273Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 83d8e0c1-8eac-4d95-b4d3-83b0af6ca2cf · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Efficient Estimation of Word Representations in Vector Space

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-05T19:53:34.706059Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d51a268c-bf17-4d3c-b676-12dd243efd30 · outbound

This paper cites Random forest classifier for remote sensing classification.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Random forest classifier for remote sensing classification

Reference 24

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 555a95cd-683f-4d57-a4a6-dd236d7265af · outbound

This paper cites Support vector machines for classification in remote sensing.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Support vector machines for classification in remote sensing

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:39.479858Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2ee89d03-1b97-48bc-a1c9-ca8809311047 · outbound

This paper cites Pedregosa, G.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Pedregosa, G

Reference 26

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Source-reported events for the cited work

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Observation 95a97246-c7e5-4750-a583-f6a927ea9f29 · outbound

This paper cites Glove: Global vectors for word representation.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Glove: Global vectors for word representation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:39.159469Z

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No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 2c12f96c-a093-44c0-ac26-4fb5b316e142 · outbound

This paper cites Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:38.834949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6e105195-24bb-4c50-91d9-61063af3f1b9 · outbound

This paper cites Landfire: a nationally consistent vegetation, wildland fire, and fuel assessment.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Landfire: a nationally consistent vegetation, wildland fire, and fuel assessment

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:38.557868Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f1661d74-0f58-4be2-9994-ae145f6e9cab · outbound

This paper cites Self-supervised vision transformers for land-cover segmentation and classification.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Self-supervised vision transformers for land-cover segmentation and classification

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:38.344459Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d784f5ad-ff21-40b7-9fce-c7427ff2c1a8 · outbound

This paper cites Training deep convolutional neural networks for land–cover classification of high-resolution imagery.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Training deep convolutional neural networks for land–cover classification of high-resolution imagery

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:38.060794Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bf878366-3f0b-4db0-a704-a54d3638d94d · outbound

This paper cites EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks

Reference 32

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Source-reported events for the cited work

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Observation 28c7d91c-1b75-4a96-8a39-d9986500e282 · outbound

This paper cites Hex2vec: Context-aware embedding h3 hexagons with openstreetmap tags.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Hex2vec: Context-aware embedding h3 hexagons with openstreetmap tags

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:37.710637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e326e051-1144-4224-9e04-07ea3140b0b5 · outbound

This paper cites From itdl to place2vec: Reasoning about place type similarity and relatedness by learning embeddings from augmented spatial contexts.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model From itdl to place2vec: Reasoning about place type similarity and relatedness by learning embeddings from augmented spatial contexts

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:37.327291Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bab6f6dd-921a-4496-821d-1a07d4b89c40 · outbound

This paper cites Extended vision transformer (exvit) for land use and land cover classification: A multimodal deep learning framework.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Extended vision transformer (exvit) for land use and land cover classification: A multimodal deep learning framework

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:36.941294Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8bdf5343-2c98-47a7-b5cc-5a2ec618aa96 · outbound

This paper cites Urban land use and land cover classification using novel deep learning models based on high spatial resolution satellite imagery.

Scalable Geospatial Data Generation Using AlphaEarth Foundations Model Urban land use and land cover classification using novel deep learning models based on high spatial resolution satellite imagery

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-05T19:53:36.660252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Pith citing papers

Observation 9817871b-d40f-40fb-80ef-fad05d880acf · inbound

Hedgementation = Hedgerow Segmentation: A Remote Sensing Benchmark cites this paper.

Hedgementation = Hedgerow Segmentation: A Remote Sensing Benchmark Scalable Geospatial Data Generation Using AlphaEarth Foundations Model

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-07-04T09:59:44.673598Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.