The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index
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Citations
Cites
Optimization of soil-adjusted vegetation indices
Rondeaux, G., Steven, M. D., & Baret, F. (1996) · Remote Sensing of Environment · doi:10.1016/0034-4257(95)00186-7 · Cited by 2,920
A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency
Gamon, J. A., Peñuelas, J., & Field, C. B. (1992) · Remote Sensing of Environment · doi:10.1016/0034-4257(92)90059-s · Cited by 2,184
Plants and Microclimate: A Quantitative Approach to Environmental Plant Physiology
Jones, H. G. (2013) · Cambridge University Press eBooks · doi:10.1017/cbo9780511845727 · Cited by 2,052
Haboudane, D., Miller, J. R., Tremblay, N., Zarco-Tejada, P. J., & Dextraze, L. (2002) · Remote Sensing of Environment · doi:10.1016/s0034-4257(02)00018-4 · Cited by 2,029
Self-citationDeficit irrigation for reducing agricultural water use
Fereres, E., & Soriano, M. A. (2006) · Journal of Experimental Botany · doi:10.1093/jxb/erl165 · Cited by 1,923
Self-citationChlorophyll Fluorescence as a Nonintrusive Indicator for Rapid Assessment of In Vivo Photosynthesis
Schreiber, U., Bilger, W., & Neubauer, C. (1995) · Ecophysiology of Photosynthesis · doi:10.1007/978-3-642-79354-7_3 · Cited by 1,663
Ecophysiology of Photosynthesis
(1994) · Springer eBooks · doi:10.1007/978-3-642-79354-7 · Cited by 1,528
Estimating PAR absorbed by vegetation from bidirectional reflectance measurements
Roujean, J.-L., & Breon, F.-M. (1995) · Remote Sensing of Environment · doi:10.1016/0034-4257(94)00114-3 · Cited by 1,422
Berni, J., Zarco-Tejada, P. J., Suarez, L., & Fereres, E. (2009) · IEEE Transactions on Geoscience and Remote Sensing · doi:10.1109/tgrs.2008.2010457 · Cited by 1,308
Self-citationMoran, M. S., Clarke, T. R., Inoue, Y., & Vidal, A. (1994) · Remote Sensing of Environment · doi:10.1016/0034-4257(94)90020-5 · Cited by 1,221
Cited by
New strategies on the application of artificial intelligence in the field of phytoremediation
Singh, P., Pani, A., Mujumdar, A. S., & Shirkole, S. S. (2023) · International Journal of Phytoremediation · doi:10.1080/15226514.2022.2090500 · Cited by 41
Metadata
- Authors
- Zarco-Tejada, P. J., González-Dugo, V., Williams, L. E., Suárez, L., Berni, J. A. J., Goldhamer, D., & Fereres, E.
- Venue
- Remote Sensing of Environment
- Publisher
- Elsevier BV
- Published
- 2013-11
- Volume
- 138
- Pages
- 38-50
- ISSN
- 0034-4257 (ISSN-L)
- OpenAlex
- W2007146840
- Cited by
- 329
- References
- 40
- FWCI
- 10.94
- 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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- CoChat. (2026). Citation check: A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index. https://app.cochat.ai/papers/10.1016/j.rse.2013.07.024
- The paper
- Zarco-Tejada, P. J., González-Dugo, V., Williams, L. E., Suárez, L., Berni, J. A. J., Goldhamer, D., & Fereres, E. (2013). A PRI-based water stress index combining structural and chlorophyll effects: Assessment using diurnal narrow-band airborne imagery and the CWSI thermal index. Remote Sensing of Environment. https://doi.org/10.1016/j.rse.2013.07.024
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.
