The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Mapping land-cover modifications over large areas: A comparison of machine learning algorithms
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Citations
Cites
The Elements of Statistical Learning
Hastie, T., Tibshirani, R., & Friedman, J. (2009) · Springer Series in Statistics · doi:10.1007/978-0-387-84858-7 · Cited by 25,970
The Elements of Statistical Learning
Hastie, T., Friedman, J., & Tibshirani, R. (2001) · Springer Series in Statistics · doi:10.1007/978-0-387-21606-5 · Cited by 24,162
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Ryzin, J. V., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1986) · Journal of the American Statistical Association · doi:10.2307/2288003 · Cited by 20,825
The Elements of Statistical Learning: Data Mining, Inference, and Prediction
John Lu, Z. Q. (2010) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.2010.00646_6.x · Cited by 12,390
Assessing the Accuracy of Remotely Sensed Data: Principles and Practices
Congalton, R., & Green, K. (1998) · Mapping Science · doi:10.1201/9781420048568 · Cited by 3,424
CLASSIFICATION AND REGRESSION TREES: A POWERFUL YET SIMPLE TECHNIQUE FOR ECOLOGICAL DATA ANALYSIS
De'ath, G., & Fabricius, K. E. (2000) · Ecology · doi:10.1890/0012-9658(2000)081[3178:cartap]2.0.co;2 · Cited by 3,167
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Image-Based Atmospheric Corrections - Revisited and Improved
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Chambers, J., Hastie, T., & Pregibon, D. (1990) · Compstat · doi:10.1007/978-3-642-50096-1_48 · Cited by 1,742
Cited by
Implementation of machine-learning classification in remote sensing: an applied review
Maxwell, A. E., Warner, T. A., & Fang, F. (2018) · International Journal of Remote Sensing · doi:10.1080/01431161.2018.1433343 · Cited by 2,057
Schneider, A. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2012.06.006 · Cited by 443
Modeling Species Distribution and Change Using Random Forest
Evans, J. S., Murphy, M. A., Holden, Z. A., & Cushman, S. A. (2011) · Predictive Species and Habitat Modeling in Landscape Ecology · doi:10.1007/978-1-4419-7390-0_8 · Cited by 364
Slow Feature Analysis for Change Detection in Multispectral Imagery
Wu, C., Du, B., & Zhang, L. (2014) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2013.2266673 · Cited by 349
Zhang, H. K., & Roy, D. P. (2017) · Remote Sensing of Environment · doi:10.1016/j.rse.2017.05.024 · Cited by 346
Metadata
- Authors
- Rogan, J., Franklin, J., Stow, D., Miller, J., Woodcock, C., & Roberts, D.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2008-05
- Volume
- 112
- Issue
- 5
- Pages
- 2272-2283
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W1978034823
- Cited by
- 267
- References
- 59
- FWCI
- 32.01
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
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Cite CoChat for the checks on this page, and the paper for its own findings.
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- CoChat. (2026). Citation check: Mapping land-cover modifications over large areas: A comparison of machine learning algorithms. https://app.cochat.ai/papers/10.1016/j.rse.2007.10.004
- The paper
- Rogan, J., Franklin, J., Stow, D., Miller, J., Woodcock, C., & Roberts, D. (2008). Mapping land-cover modifications over large areas: A comparison of machine learning algorithms. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2007.10.004
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.
