The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis
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.
Integrity signals
Registry
Cites
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.
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
Greedy function approximation: A gradient boosting machine
Friedman, J. H. (2001) · The Annals of Statistics · doi:10.1214/aos/1013203451 · Cited by 30,731
Cited by
Vegetation Dynamics in Yellowstone’s Northern Range: 1985 to 1999
Savage, S. L., & Lawrence, R. L. (2010) · Photogrammetric Engineering & Remote Sensing · doi:10.14358/pers.76.5.547 · Cited by 16
Self-citation
Metadata
- Authors
- Lawrence, R.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2004-04-15
- Volume
- 90
- Issue
- 3
- Pages
- 331-336
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2158770403
- Cited by
- 310
- References
- 1
- FWCI
- 33.17
- Type
- journal article
- Language
- en
- Open access
- closed
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: Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis. https://app.cochat.ai/papers/10.1016/j.rse.2004.01.007
- The paper
- Lawrence, R. (2004). Classification of remotely sensed imagery using stochastic gradient boosting as a refinement of classification tree analysis. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2004.01.007
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.
