Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 543

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System

Open access
Lefsky, Michael A.·2010·Geophysical Research Letters

Abstract

The value of lidar derives from its ability to map ecosystem vertical structure which can be used to estimate aboveground carbon storage. Spaceborne lidar sensors collect data along transects and gain value for the global change science community when combined with data sources that have complete horizontal coverage. Data sources and methods for this type of analysis require evaluation. In this work we use image segmentation of 500 m Moderate Resolution Imaging Spectroradiometer (MODIS) data to produce a global map of 4.4 million forest patches. Where a Geoscience Laser Altimeter System (GLAS) transect intersects a patch, its height is calculated from the GLAS observations directly. Regression analysis is then used to estimate the heights of those patches without GLAS observations. Regression goodness‐of‐fit statistics indicate moderately strong relationships for predicting the 90th percentile patch height, with a mean RMSE of 5.9 m and mean correlation (R 2) of 0.67.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1029/2010gl043622

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 543

Metadata

Authors
Lefsky, M. A.
Venue
Geophysical Research Letters
Published
2010-08
Volume
37
Issue
15
ISSN
  • 0094-8276 (ISSN-L)
  • 1944-8007
OpenAlex
W1566532634
Cited by
543
References
1
FWCI
33.18
Type
journal article
Language
en
Open access
bronze

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System. https://app.cochat.ai/papers/10.1029/2010gl043622
The paper
Lefsky, M. A. (2010). A global forest canopy height map from the Moderate Resolution Imaging Spectroradiometer and the Geoscience Laser Altimeter System. Geophysical Research Letters. https://doi.org/10.1029/2010gl043622

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.