The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.
A unified vegetation index for quantifying the terrestrial biosphere
Open accessAbstract
Machine learning generalizes vegetation indices to better quantify the terrestrial biosphere.
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Citations
Cites
Red and photographic infrared linear combinations for monitoring vegetation
Tucker, C. J. (1979) · Remote Sensing of Environment · doi:10.1016/0034-4257(79)90013-0 · Cited by 11,754
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond
Schölkopf, B., & Smola, A. J. (2001) · The MIT Press eBooks · doi:10.7551/mitpress/4175.001.0001 · Cited by 11,703
Overview of the radiometric and biophysical performance of the MODIS vegetation indices
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., & Ferreira, L. G. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00096-2 · Cited by 9,869
Monitoring Vegetation Systems in the Great Plains with Erts
Rouse, J. W., Haas, R. H., Schell, J., & Deering, D. W. (1973) · NASA STI Repository (National Aeronautics and Space Administration) · Cited by 6,835
Kernel Methods for Pattern Analysis
Shawe-Taylor, J., & Cristianini, N. (2004) · Cambridge University Press eBooks · doi:10.1017/cbo9780511809682 · Cited by 6,587
MONTEITH, J. (1965) · PubMed · Cited by 5,169
Reichstein, M., Falge, E., Baldocchi, D., Papale, D., Aubinet, M., Berbigier, P., Bernhofer, C., Buchmann, N., Gilmanov, T., Granier, A., et al. (2005) · Global Change Biology · doi:10.1111/j.1365-2486.2005.001002.x · Cited by 3,810
Self-citationMeasuring and testing dependence by correlation of distances
Székely, G. J., Rizzo, M. L., & Bakirov, N. K. (2007) · The Annals of Statistics · doi:10.1214/009053607000000505 · Cited by 2,684
Haboudane, D. (2004) · Remote Sensing of Environment · doi:10.1016/j.rse.2003.12.013 · Cited by 2,608
BALDOCCHI, D. D. (2003) · Global Change Biology · doi:10.1046/j.1365-2486.2003.00629.x · Cited by 2,594
Cited by
Optical vegetation indices for monitoring terrestrial ecosystems globally
Zeng, Y., Hao, D., Huete, A., Dechant, B., Berry, J., Chen, J. M., Joiner, J., Frankenberg, C., Bond-Lamberty, B., Ryu, Y., et al. (2022) · Nature Reviews Earth & Environment · doi:10.1038/s43017-022-00298-5 · Cited by 837
Satellite observations document trends consistent with a boreal forest biome shift
Berner, L. T., & Goetz, S. J. (2022) · Global Change Biology · doi:10.1111/gcb.16121 · Cited by 182
Kang, Y., Bassiouni, M., Gaber, M., Lu, X., & Keenan, T. F. (2025) · Earth System Science Data · doi:10.5194/essd-17-3009-2025 · Cited by 22
Metadata
- Authors
- Camps-Valls, G., Campos-Taberner, M., Moreno-Martínez, Á., Walther, S., Duveiller, G., Cescatti, A., Mahecha, M. D., Muñoz-Marí, J., García-Haro, F. J., Guanter, L., Jung, M., Gamon, J. A., Reichstein, M., & Running, S. W.
- Venue
- Science Advances
- Published
- 2021-02-26
- Volume
- 7
- Issue
- 9
- ISSN
- 2375-2548 (ISSN-L)
- OpenAlex
- W3130461578
- Cited by
- 782
- References
- 49
- FWCI
- 42.94
- Type
- journal article
- Language
- en
- Open access
- gold
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- CoChat. (2026). Citation check: A unified vegetation index for quantifying the terrestrial biosphere. https://app.cochat.ai/papers/10.1126/sciadv.abc7447
- The paper
- Camps-Valls, G., Campos-Taberner, M., Moreno-Martínez, Á., Walther, S., Duveiller, G., Cescatti, A., Mahecha, M. D., Muñoz-Marí, J., García-Haro, F. J., Guanter, L., Jung, M., Gamon, J. A., Reichstein, M., & Running, S. W. (2021). A unified vegetation index for quantifying the terrestrial biosphere. Science Advances. https://doi.org/10.1126/sciadv.abc7447
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.
