Paper Citation Record · LEDGER

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas

As of 19 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 2 inbound Pith citation observations for arXiv:2411.14354.

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

pith.paper-citation-record.v1
2411.14354 v1

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T15:20:29.415268Z

measured 23 of 23 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:55:02.307764Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T22:55:02.445424Z

Reference resolution

21 of 21 outbound references displayed

verified exact8
verified fuzzy1
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch2

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation e99dc8ff-17e3-44c7-ad7e-ab15d3842364 · outbound

This paper cites doi: 10.24963/ijcai.2023/653.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.24963/ijcai.2023/653

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.347419Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e817d83-4ba5-4916-a6a7-5361a21f0d81 · outbound

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

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas FoMo: Multi-Modal, Multi-Scale and Multi-Task Remote Sensing Foundation Models for Forest Monitoring

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.356073Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 68a57dc1-834e-46fd-8e02-f7f082aa5a0d · outbound

This paper cites doi: 10.1073/pnas.2113658119.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.1073/pnas.2113658119

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.363566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47d7b775-cadf-487f-8bc5-d9d28e709beb · outbound

This paper cites doi: https://doi.org/10.1016/j.rse.2022.113402.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: https://doi.org/10.1016/j.rse.2022.113402

Reference 10

Resolution: metadata mismatch; raw_fallback, observed 2026-08-12T15:20:29.831991Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f90972cc-a816-487e-a2d2-487362cdaac5 · outbound

This paper cites OpenForest: A data catalogue for machine learning in forest monitoring.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas OpenForest: A data catalogue for machine learning in forest monitoring

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-12T15:20:29.770827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation e83e5728-bf98-44aa-99d9-a9feea2df21b · outbound

This paper cites doi: 10.1038/s41586-023-06825-8.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.1038/s41586-023-06825-8

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.388385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2181c422-9f94-481b-80f4-18d80bff3af7 · outbound

This paper cites doi: https://doi.org/10.1016/j.rse.2020.112165.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: https://doi.org/10.1016/j.rse.2020.112165

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.391558Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00f27da9-0248-4788-8d8c-5a9da7bb7244 · outbound

This paper cites Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Knowledge Transfer from Vision Foundation Models for Efficient Training of Small Task-specific Models

Reference 17

Resolution: metadata mismatch; local_arxiv, observed 2026-08-12T15:20:29.629726Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b35c24e5-3780-4ea1-9483-990b441434e7 · outbound

This paper cites an unresolved cited work.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Unresolved cited work

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.405194Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5490d6b6-20c8-42dd-b8fc-21bef4492ada · outbound

This paper cites Phil Wilkes, Simon D.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Phil Wilkes, Simon D

Reference 19

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.457207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a5b6ac5b-1279-4575-b2b7-b0c900875a23 · outbound

This paper cites X = CC ×H.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas X = CC ×H

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T15:20:29.860779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1cbd285-b859-4fb8-ae0b-d12cd6807890 · outbound

This paper cites doi: 10.1162/153244304322972667.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.1162/153244304322972667

Reference 2003

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.467114Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 91f556e5-fd69-4bae-9ac4-04430f897516 · outbound

This paper cites Isaac Corley, Caleb Robinson, Rahul Dodhia, Juan M Lavista Ferres, and Peyman Najafirad.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Isaac Corley, Caleb Robinson, Rahul Dodhia, Juan M Lavista Ferres, and Peyman Najafirad

Reference 2013

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.493675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3c810cdd-9d8c-4ad7-9a60-aafb68a14863 · outbound

This paper cites doi: 10.3390/rs70912563.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.3390/rs70912563

Reference 2015

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.446189Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 4bff7bdf-0eee-420d-8686-68ed00634260 · outbound

This paper cites Open-Canopy: Towards Very High Resolution Forest Monitoring.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Open-Canopy: Towards Very High Resolution Forest Monitoring

Reference 2016

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.370650Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fff892a-6cb7-4934-a7c8-ae17d1f91573 · outbound

This paper cites doi: 10.3390/rs12172840.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.3390/rs12172840

Reference 2020

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.483218Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a80000e4-026f-4df3-aaa7-d0135f5d7358 · outbound

This paper cites doi: 10.3390/rs13122392.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.3390/rs13122392

Reference 2021

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.517095Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 5d628a3d-cd57-4e5a-8c47-e302d1445514 · outbound

This paper cites doi: 10.1038/s41597-022-01307-4.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas doi: 10.1038/s41597-022-01307-4

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.360144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a3cb9fcf-dc23-4272-9b6c-997295320014 · outbound

This paper cites Emily Aiken, Esther Rolf, and Joshua Blumenstock.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Emily Aiken, Esther Rolf, and Joshua Blumenstock

Reference 2023

Resolution: verified exact; doi, observed 2026-08-12T15:20:29.533058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 41f399ee-71e6-44cc-9c2d-7a39ea610e63 · outbound

This paper cites an unresolved cited work.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Unresolved cited work

Reference 2024

Resolution: unresolved; raw_fallback, observed 2026-08-12T15:20:29.871523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f9b2c0fb-58ba-4ca2-9c21-17dbb291c39e · outbound

This paper cites Angela Tsao, Ikenna Nzewi, Ayodeji Jayeoba, Uzoma Ayogu, and David B.

Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas Angela Tsao, Ikenna Nzewi, Ayodeji Jayeoba, Uzoma Ayogu, and David B

Reference 4257

Resolution: unresolved; no resolver link, observed 2026-08-12T15:20:29.397902Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 71ecabdf-c343-4030-a4ec-5db2c6b8a24f · inbound

A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management cites this paper.

A Novel Large Vision Foundation Model (LVFM)-based Approach for Generating High-Resolution Canopy Height Maps in Plantations for Precision Forestry Management Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas

Reference 43

Resolution: metadata mismatch; local_arxiv, observed 2026-08-06T22:55:02.453016Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11e87d30-cec7-4679-9127-2419bed672fd · inbound

Localized, High-resolution Geographic Representations with Slepian Functions cites this paper.

Localized, High-resolution Geographic Representations with Slepian Functions Contrasting local and global modeling with machine learning and satellite data: A case study estimating tree canopy height in African savannas

Reference 2018

Resolution: unresolved; no resolver link, observed 2026-08-03T06:09:41.819542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.