The DOI matches its Crossref record; 14 of the 14 references it cites were found in a registry or an index.
Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop
Open accessAbstract
Leaf area index (LAI) and chlorophyll content, at leaf and canopy level, are important variables for agricultural applications because of their crucial role in photosynthesis and in plant functioning. The goal of this study was to test the hypothesis that LAI, leaf chlorophyll content (LCC), and canopy chlorophyll content (CCC) of a potato crop can be estimated by vegetation indices for the first time using Sentinel-2 satellite images. In 2016 ten plots of 30 × 30 m were designed in a potato field with different fertilization levels. During the growing season approximately 10 daily radiometric field measurements were used to determine LAI, LCC, and CCC. These radiometric determinations were extensively calibrated against LAI2000 and chlorophyll meter (SPAD, soil plant analysis development) measurements for potato crops grown in the years 2010–2014. Results for Sentinel-2 showed that the weighted difference vegetation index (WDVI) using bands at 10 m spatial resolution can be used for estimating the LAI (R2 of 0.809; root mean square error of prediction (RMSEP) of 0.36). The ratio of the transformed chlorophyll in reflectance index and the optimized soil-adjusted vegetation index (TCARI/OSAVI) showed to be a good linear estimator of LCC at 20 m (R2 of 0.696; RMSEP of 0.062 g·m−2). The performance of the chlorophyll vegetation index (CVI) at 10 m spatial resolution was slightly worse (R2 of 0.656; RMSEP of 0.066 g·m−2) compared to TCARI/OSAVI. Finally, results showed that the green chlorophyll index (CIgreen) was an accurate and linear estimator of CCC at 10 m (R2 of 0.818; RMSEP of 0.29 g·m−2). Results for CIgreen were better than for the red-edge chlorophyll index (CIred-edge, R2 of 0.576, RMSE of 0.43 g·m−2). Our results show that Sentinel-2 bands at 10 m spatial resolution are suitable for estimating LAI, LCC, and CCC, avoiding the need for red-edge bands that are only available at 20 m. This is an important finding for applying Sentinel-2 data in precision agriculture.
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
Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services
Drusch, M., Del Bello, U., Carlier, S., Colin, O., Fernandez, V., Gascon, F., Hoersch, B., Isola, C., Laberinti, P., Martimort, P., et al. (2012) · Remote Sensing of Environment · doi:10.1016/j.rse.2011.11.026 · Cited by 4,815
Gitelson, A. A., Gritz †, Y., & Merzlyak, M. N. (2003) · Journal of Plant Physiology · doi:10.1078/0176-1617-00887 · Cited by 2,683
Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance
Daughtry, C. (2000) · Remote Sensing of Environment · doi:10.1016/s0034-4257(00)00113-9 · Cited by 2,543
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
Mulla, D. J. (2013) · Biosystems Engineering · doi:10.1016/j.biosystemseng.2012.08.009 · Cited by 1,982
Remote estimation of canopy chlorophyll content in crops
Gitelson, A. A., Viña, A., Ciganda, V., Rundquist, D. C., & Arkebauer, T. J. (2005) · Geophysical Research Letters · doi:10.1029/2005gl022688 · Cited by 1,645
The MERIS terrestrial chlorophyll index
Dash, J., & Curran, P. J. (2004) · International Journal of Remote Sensing · doi:10.1080/0143116042000274015 · Cited by 1,226
First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe
Immitzer, M., Vuolo, F., & Atzberger, C. (2016) · Remote Sensing · doi:10.3390/rs8030166 · Cited by 948
Uddling, J., Gelang-Alfredsson, J., Piikki, K., & Pleijel, H. (2007) · Photosynthesis Research · doi:10.1007/s11120-006-9077-5 · Cited by 885
Gitelson, A. A., & Merzlyak, M. N. (1996) · Journal of Plant Physiology · doi:10.1016/s0176-1617(96)80284-7 · Cited by 867
Cited by
West, H., Quinn, N., & Horswell, M. (2019) · Remote Sensing of Environment · doi:10.1016/j.rse.2019.111291 · Cited by 538
Hasan, M. E., Zhang, L., Dewan, A., Guo, H., & Mahmood, R. (2021) · Land Degradation & Development · doi:10.1002/ldr.3821 · Cited by 56
Metadata
- Authors
- Clevers, J., Kooistra, L., & Van den Brande, M.
- Venue
- Remote Sensing
- Publisher
- MDPI AG
- Published
- 2017-04-25
- Volume
- 9
- Issue
- 5
- Pages
- 405
- ISSN
- 2072-4292 (ISSN-L)
- OpenAlex
- W2609044008
- Cited by
- 339
- References
- 14
- FWCI
- 26.65
- Type
- journal article
- Language
- en
- Open access
- gold
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: Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop. https://app.cochat.ai/papers/10.3390/rs9050405
- The paper
- Clevers, J., Kooistra, L., & Van den Brande, M. (2017). Using Sentinel-2 Data for Retrieving LAI and Leaf and Canopy Chlorophyll Content of a Potato Crop. Remote Sensing. https://doi.org/10.3390/rs9050405
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.
