Paper Citation Record · LEDGER

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

As of 17 August 2026, this Paper Citation Record lists 100 of 168 outbound references and 32 inbound Pith citation observations for arXiv:2412.04204.

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

pith.paper-citation-record.v1
2412.04204 v2

Coverage vector

measured 100 of 168 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T21:42:47.350932Z

measured 132 of 132 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:49:31.245108Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 168 outbound references displayed

verified exact2
verified fuzzy0
unresolved98
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

6
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation f830e55f-3c15-4484-a6f5-80924ac684d3 · outbound

This paper cites Towards a foundation model for geospatial artificial intelligence (vision paper).

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Towards a foundation model for geospatial artificial intelligence (vision paper)

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.926758Z

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Observation 11d75354-ef58-4b18-a98b-8662c833d4fe · outbound

This paper cites Toward foundation models for earth monitoring: Proposal for a climate change benchmark, 2021.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Toward foundation models for earth monitoring: Proposal for a climate change benchmark, 2021

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.932223Z

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Observation 55380c3a-f885-4a2e-9c4d-826bf14f445b · outbound

This paper cites van Rijn, Holger H.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models van Rijn, Holger H

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.937045Z

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Observation 085ccef3-382c-4299-9dc2-73981cb7cc3e · outbound

This paper cites When geoscience meets foundation models: Towards general geoscience artificial intelligence system, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models When geoscience meets foundation models: Towards general geoscience artificial intelligence system, 2024

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.941969Z

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Observation 98a22b09-2bc7-4683-89c6-c24075cdab13 · outbound

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

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Eurosat: A novel dataset and deep learning benchmark for land use and land cover classification

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.946661Z

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Observation 1984a650-b3bd-4bb9-92db-5eef7260acf8 · outbound

This paper cites Mtp: Advancing remote sensing foundation model via multi-task pretraining, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Mtp: Advancing remote sensing foundation model via multi-task pretraining, 2024

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.951377Z

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Observation 2ddc9b50-f02e-4899-aa7e-c26c08048167 · outbound

This paper cites On the opportunities and challenges of foundation models for geospatial artificial intelligence, 2023.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models On the opportunities and challenges of foundation models for geospatial artificial intelligence, 2023

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.956383Z

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Observation 819a308f-5d9d-47d8-9f07-2d18b5a38b3b · outbound

This paper cites Mission critical – satellite data is a distinct modality in machine learning, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Mission critical – satellite data is a distinct modality in machine learning, 2024

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.961388Z

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Observation 394b81b4-9927-47cb-b102-c0fdde0b7eeb · outbound

This paper cites Phileo bench: Evaluating geo-spatial foundation models, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Phileo bench: Evaluating geo-spatial foundation models, 2024

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.965859Z

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Observation 307f5e3b-4f09-4c4c-ba74-7e565b497270 · outbound

This paper cites Geo-bench: Toward foundation models for earth monitoring, 2023.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Geo-bench: Toward foundation models for earth monitoring, 2023

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.970175Z

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Observation d026a43e-4f75-40e0-8876-92560a84e61a · outbound

This paper cites Lobell, and Stefano Ermon.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Lobell, and Stefano Ermon

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.974562Z

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Observation ee5ea06a-c2e5-424a-a756-9c8990522a94 · outbound

This paper cites FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.978892Z

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Observation 14337b3b-376c-40be-be80-7e07becd8816 · outbound

This paper cites On the Generalizability of Foundation Models for Crop Type Mapping.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models On the Generalizability of Foundation Models for Crop Type Mapping

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.983851Z

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Observation c74c1009-2994-4164-8e43-95a63b95fbf3 · outbound

This paper cites an unresolved cited work.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Unresolved cited work

Reference 14

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Observation 9938c1d2-e694-4a5b-b73a-8a516d0aadab · outbound

This paper cites Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, and Trevor Darrell.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Reed, Ritwik Gupta, Shufan Li, Sarah Brockman, Christopher Funk, Brian Clipp, Kurt Keutzer, Salvatore Candido, Matt Uyttendaele, and Trevor Darrell

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.993266Z

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Observation 0f2c398c-b466-4392-aa9f-b5b6f573658b · outbound

This paper cites SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models SatlasPretrain: A Large-Scale Dataset for Remote Sensing Image Understanding

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:46.997585Z

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Observation e008ec94-e2fe-4225-bdc6-3c541f44f650 · outbound

This paper cites Specialized foundation models struggle to beat supervised baselines, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Specialized foundation models struggle to beat supervised baselines, 2024

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:47.003231Z

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Observation 46c8930f-a576-4be1-b637-3929da5a5803 · outbound

This paper cites Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in african savannas, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in african savannas, 2024

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:47.007483Z

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Observation 1ab52f08-eb1e-4396-88ce-3f1b1dfed770 · outbound

This paper cites Earthnets: Empowering ai in earth observation, 2024.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Earthnets: Empowering ai in earth observation, 2024

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T21:42:47.011777Z

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Observation 45f99de1-12ee-4846-ba36-06b5807f27c4 · outbound

This paper cites There are no data like more data: Datasets for deep learning in earth observation.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models There are no data like more data: Datasets for deep learning in earth observation

Reference 20

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Observation d7c6955b-af0f-4287-ac4f-b2d65dc330f9 · outbound

This paper cites Bag-of-visual-words and spatial extensions for land-use classification.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Bag-of-visual-words and spatial extensions for land-use classification

Reference 21

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Observation 0d18c4f8-87a5-4b1f-97d7-c32c010ca33b · outbound

This paper cites Structural high-resolution satellite image indexing.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Structural high-resolution satellite image indexing

Reference 22

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Observation 813cdc7d-61e7-41b4-b48a-a2e061dbc287 · outbound

This paper cites Satellite image classification via two-layer sparse coding with biased image representation.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Satellite image classification via two-layer sparse coding with biased image representation

Reference 23

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Observation 7a9331f7-531e-4a52-830f-c23d678b0753 · outbound

This paper cites Aerial scene parsing: From tile-level scene classification to pixel-wise semantic labeling, 2022.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Aerial scene parsing: From tile-level scene classification to pixel-wise semantic labeling, 2022

Reference 24

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Observation e9240dfa-979c-4729-9901-2f4159b33d43 · outbound

This paper cites On creating benchmark dataset for aerial image interpretation: Reviews, guidances and million-aid.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models On creating benchmark dataset for aerial image interpretation: Reviews, guidances and million-aid

Reference 25

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Observation 192a137a-daad-4f38-987d-71c3ac519a60 · outbound

This paper cites Bigearthnet: A large-scale benchmark archive for remote sensing image understanding.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Bigearthnet: A large-scale benchmark archive for remote sensing image understanding

Reference 26

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Observation e1201d9f-11db-4c8c-a3cd-73cd70147810 · outbound

This paper cites Bigearthnet-mm: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval [software and data sets].

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Bigearthnet-mm: A large-scale, multimodal, multilabel benchmark archive for remote sensing image classification and retrieval [software and data sets]

Reference 27

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Observation 0eb3dd1f-8bc8-4704-9d87-e649854175d3 · outbound

This paper cites Liu, Andrew Y.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Liu, Andrew Y

Reference 28

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Observation fabfcfe8-614b-4390-9e9e-e56889f42ddc · outbound

This paper cites Kluger, Sherrie Wang, and David B.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Kluger, Sherrie Wang, and David B

Reference 29

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Observation 4c1f1858-6377-4b02-bd16-7b5a0fca781f · outbound

This paper cites Brazildam: A benchmark dataset for tailings dam detection.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Brazildam: A benchmark dataset for tailings dam detection

Reference 30

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Observation 789088c3-a1ce-4cfc-b0fc-0ba4f80a5c3a · outbound

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Unresolved cited work

Reference 31

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Observation 5738009c-1f13-4c92-8ec5-4701ef2ff034 · outbound

This paper cites Functional map of the world.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Functional map of the world

Reference 32

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This paper cites Object detection in optical remote sensing images: A survey and a new benchmark.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Object detection in optical remote sensing images: A survey and a new benchmark

Reference 33

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Object Detection in Aerial Images: A Large-Scale Benchmark and Challenges

Reference 34

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models isaid: A large-scale dataset for instance segmentation in aerial images

Reference 35

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models xview3-sar: Detecting dark fishing activity using synthetic aperture radar imagery, 2022

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Opensarship: A dataset dedicated to sentinel-1 ship interpretation

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Ship detection in sar images based on an improved faster r-cnn

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Small-object detection in remote sensing images with end-to-end edge-enhanced gan and object detector network

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Vehicle detection in aerial imagery: A small target detection benchmark

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Learning spatial context: Using stuff to find things

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models The isprs benchmark on urban object classification and 3d building reconstruction

Reference 42

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Loveda: A remote sensing land-cover dataset for domain adaptive semantic segmentation, 2022

Reference 43

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Enabling country-scale land cover mapping with meter- resolution satellite imagery

Reference 44

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Deepglobe 2018: A challenge to parse the earth through satellite images

Reference 45

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models FLAIR : a country-scale land cover semantic segmentation dataset from multi- source optical imagery

Reference 46

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Cloud detection algorithm comparison and validation for operational landsat data products

Reference 47

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Cloud-net: An end-to-end cloud detection algorithm for landsat 8 imagery

Reference 48

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Deep learning based cloud detection for medium and high resolution remote sensing images of different sensors

Reference 49

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models High-Resolution Building and Road Detection from Sentinel-2

Reference 50

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Bacastow

Reference 51

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This paper cites Semantic segmentation of crop type in africa: A novel dataset and analysis of deep learning methods.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Semantic segmentation of crop type in africa: A novel dataset and analysis of deep learning methods

Reference 52

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Multi-modal temporal attention models for crop mapping from satellite time series

Reference 53

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Unsupervised Image Regression for Heterogeneous Change Detection

Reference 54

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Dynamicearthnet: Daily multi-spectral satellite dataset for semantic change segmentation

Reference 55

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models A spatial-temporal attention-based method and a new dataset for remote sensing image change detection

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models xbd: A dataset for assessing building damage from satellite imagery, 2019

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Creating xbd: A dataset for assessing building damage from satellite imagery

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Asymmet- ric siamese networks for semantic change detection in aerial images

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Satbird: a dataset for bird species distribution modeling using remote sensing and citizen science data

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models David Neelin, David Randall, Sara Shamekh, Mark A Taylor, Nathan Urban, Janni Yuval, Guang Zhang, and Michael Pritchard

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Biomassters: A benchmark dataset for forest biomass estimation using multi-modal satellite time-series

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models 3dcd: A new dataset for 2d and 3d change detection using deep learning techniques

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Learning transferable visual models from natural language supervision, 2021

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Visual instruction tuning

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Laion-5b: An open large-scale dataset for training next generation image-text models

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Unresolved cited work

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Self-supervised Learning in Remote Sensing: A Review

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models An empirical study of remote sensing pretraining

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Ssl4eo-l: Datasets and foundation models for landsat imagery

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Albrecht, and Xiao Xiang Zhu

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Masked autoencoders are scalable vision learners

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models data2vec: A general framework for self-supervised learning in speech, vision and language

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Emerging Properties in Self-Supervised Vision Transformers

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Momentum contrast for unsupervised visual representation learning

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models One for all: Toward unified foundation models for earth vision, 2024

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models A Billion-scale Foundation Model for Remote Sensing Images

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Cmid: A unified self-supervised learning framework for remote sensing image understanding

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Ringmo: A remote sensing foundation model with masked image modeling.IEEE Transactions on Geoscience and Remote Sensing , 2022

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Berg, Wan-Yen Lo, Piotr Dollár, and Ross Girshick

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models CtxMIM: Context-Enhanced Masked Image Modeling for Remote Sensing Image Understanding

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This paper cites Towards geospatial foundation models via continual pretraining, 2023.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Towards geospatial foundation models via continual pretraining, 2023

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Bridging remote sensors with multisensor geospatial foundation models, 2024

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery

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This paper cites Rethinking transformers pre-training for multi-spectral satellite imagery, 2024.

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Cross-scale mae: A tale of multiscale exploitation in remote sensing

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Unresolved cited work

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This paper cites Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing.

PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Feature Guided Masked Autoencoder for Self-supervised Learning in Remote Sensing

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Spradlin, Jordan A

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models S2mae: A spatial-spectral pretraining foundation model for spectral remote sensing data

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PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models Omnisat: Self-supervised modality fusion for earth observation, 2024

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Observation 421d63ad-955b-47ac-9ee6-bde72e1d50e8 · inbound

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation cites this paper.

SHRUG-FM: Reliability-Aware Foundation Models for Earth Observation PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-17T22:22:09.035345Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9464b6f9-1e5d-4106-b310-99262a4fec35 · inbound

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training cites this paper.

MMEarth-Bench: Global Model Adaptation via Multimodal Test-Time Training PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-03T04:01:57.190388Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1ad6199e-44c7-47d4-bbb3-c5efdd5e5cdf · inbound

Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications cites this paper.

Cryo-Bench: Benchmarking Foundation Models for Cryosphere Applications PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-02T19:38:14.434552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a860a28f-b40e-4d2a-a575-22ddc47f798a · inbound

The Lov\'{a}sz Local Lemma: Foundations and Applications cites this paper.

The Lov\'{a}sz Local Lemma: Foundations and Applications PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-07-15T13:23:57.354325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3545b1c8-3f65-4abc-9296-53a013d5ad03 · inbound

How to Embed Matters: Evaluation of EO Embedding Design Choices cites this paper.

How to Embed Matters: Evaluation of EO Embedding Design Choices PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-05-15T13:45:52.242611Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c7da4b06-8024-4d2c-93db-752bf821676c · inbound

NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing cites this paper.

NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-07-15T11:59:49.461107Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 13c763be-e78d-4e71-82c5-3263aba4cb6b · inbound

NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing cites this paper.

NeSy-Route: A Neuro-Symbolic Benchmark for Constrained Route Planning in Remote Sensing PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T18:07:48.363410Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 71f90e10-d49d-4c26-905c-eda25a4becdb · inbound

Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Data cites this paper.

Location Is All You Need: Continuous Spatiotemporal Neural Representations of Earth Observation Data PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-05-11T00:20:52.322488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation fae846a4-5458-4f3a-9304-2ad873a855c6 · inbound

Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data cites this paper.

Low-Rank Adaptation of Geospatial Foundation Models for Wildfire Mapping Using Sentinel-2 Data PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-09T06:25:48.801210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 8bca9f29-8a05-402c-8f78-509a653f9ef3 · inbound

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation cites this paper.

LithoBench: Benchmarking Large Multimodal Models for Remote-Sensing Lithology Interpretation PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:00:56.154282Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 99530bea-e428-4990-94fe-2b0281aea3b0 · inbound

No One Knows the State of the Art in Geospatial Foundation Models cites this paper.

No One Knows the State of the Art in Geospatial Foundation Models PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:19:28.534901Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c4e5e73f-f35e-4f9e-94d3-883dc5327681 · inbound

Does Your Wildfire Prediction Model Actually Work, or Just Score Well? cites this paper.

Does Your Wildfire Prediction Model Actually Work, or Just Score Well? PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:49:00.932759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 976acc12-a762-43c8-aac6-72b01c609d55 · inbound

Does Your Wildfire Prediction Model Actually Work, or Just Score Well? cites this paper.

Does Your Wildfire Prediction Model Actually Work, or Just Score Well? PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-25T06:05:26.467831Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 156b2557-14ea-44c0-bd50-269f8bfc8109 · inbound

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals cites this paper.

SDGBiasBench: Benchmarking and Mitigating Vision--Language Models' Biases in Sustainable Development Goals PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 39

Resolution: metadata mismatch; arxiv_id, observed 2026-05-22T07:31:13.896374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 804bd64d-8b21-4954-b888-09cb3e46f183 · inbound

GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models cites this paper.

GeoNatureAgent Benchmark: Benchmarking LLM Agents for Environmental Geospatial Analysis Across Frontier and Open-Weight Foundation Models PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-06-27T07:20:41.314253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a27366c7-b62f-40d8-80d5-69eb207eff05 · inbound

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation cites this paper.

UniverSat: Resolution- and Modality-Agnostic Transformers for Earth Observation PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-04T10:29:44.820592Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 25db0167-a8d8-4f64-b633-ab77ae206568 · inbound

Benchmarking Geospatial Foundation Models for Agriculture Applications cites this paper.

Benchmarking Geospatial Foundation Models for Agriculture Applications PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-06-30T07:54:22.248378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 3fbbcef4-c7e9-4c86-a9ac-8fb4c5a9bfbc · inbound

Uncertainty-aware tree height change regression cites this paper.

Uncertainty-aware tree height change regression PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T14:37:03.052385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 5a746dc7-950b-4a94-820f-cd87f8a286e1 · inbound

Moonstone: A Multimodal Foundation Model and Benchmark for Lunar Remote Sensing cites this paper.

Moonstone: A Multimodal Foundation Model and Benchmark for Lunar Remote Sensing PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 17

Resolution: unresolved; no resolver link, observed 2026-07-12T00:58:54.755765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3a5bb998-7238-496e-8c46-d5b7c553368f · inbound

Scalable and Trustworthy Earth Observation Foundation Models cites this paper.

Scalable and Trustworthy Earth Observation Foundation Models PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 23

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T19:07:35.360695Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 63008182-45bf-4884-966b-206a2736df3f · inbound

Treatment Geometry and Causal Identification with Earth Observation Data cites this paper.

Treatment Geometry and Causal Identification with Earth Observation Data PANGAEA: A Global and Inclusive Benchmark for Geospatial Foundation Models

Reference 2013

Resolution: unresolved; no resolver link, observed 2026-08-01T11:23:47.457553Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.