The DOI matches its Crossref record; 33 of the 33 references it cites were found in a registry or an index.
High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm
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
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Classification and Regression by randomForest
Liaw, A. I., & Wiener, M. C. (2007) · Cited by 18,594
Wrappers for feature subset selection
Kohavi, R., & John, G. H. (1997) · Artificial Intelligence · doi:10.1016/s0004-3702(97)00043-x · Cited by 8,947
Random forest classifier for remote sensing classification
Pal, M. (2005) · International Journal of Remote Sensing · doi:10.1080/01431160412331269698 · Cited by 3,283
Random Forests for land cover classification
Gislason, P. O., Benediktsson, J. A., & Sveinsson, J. R. (2006) · Pattern Recognition Letters · doi:10.1016/j.patrec.2005.08.011 · Cited by 2,244
Prasad, A. M., Iverson, L. R., & Liaw, A. (2006) · Ecosystems · doi:10.1007/s10021-005-0054-1 · Cited by 1,987
Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics
Thenkabail, P. S., Smith, R. B., & De Pauw, E. (2000) · Remote Sensing of Environment · doi:10.1016/s0034-4257(99)00067-x · Cited by 1,313
Investigation of the random forest framework for classification of hyperspectral data
Ham, J., Chen, Y., Crawford, M. M., & Ghosh, J. (2005) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2004.842481 · Cited by 1,276
Remote sensing: The quantitative approach
Davis, S. M., Landgrebe, D. A., Phillips, T. L., et al. (1978) · Infoscience (Ecole Polytechnique Fédérale de Lausanne) · Cited by 1,261
Cited by
Generating 3D city models without elevation data
Biljecki, F., Ledoux, H., & Stoter, J. (2017) · Computers, Environment and Urban Systems · doi:10.1016/j.compenvurbsys.2017.01.001 · Cited by 165
Shao, Z., & Zhang, L. (2016) · Sensors · doi:10.3390/s16060834 · Cited by 105
Rasam, S., Talebkeikhah, F., Talebkeikhah, M., Salimi, A., & Moraveji, M. K. (2021) · International Journal of Environmental & Analytical Chemistry · doi:10.1080/03067319.2019.1700973 · Cited by 29
Noviello, M., Cafarelli, B., Calculli, C., Sarris, A., & Mairota, P. (2018) · Applied Geography · doi:10.1016/j.apgeog.2018.04.005 · Cited by 22
Metadata
- Authors
- Mutanga, O., Adam, E., & Cho, M. A.
- Venue
- International Journal of Applied Earth Observation and Geoinformation
- Publisher
- Elsevier BV
- Published
- 2012-08
- Volume
- 18
- Pages
- 399-406
- ISSN
- 0303-2434 (ISSN-L)
- 1569-8432
- OpenAlex
- W2018627383
- Cited by
- 854
- References
- 33
- FWCI
- 18.64
- 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: High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm. https://app.cochat.ai/papers/10.1016/j.jag.2012.03.012
- The paper
- Mutanga, O., Adam, E., & Cho, M. A. (2012). High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm. International Journal of Applied Earth Observation and Geoinformation. https://doi.org/10.1016/j.jag.2012.03.012
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.
