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Remote estimation of leaf area index and green leaf biomass in maize canopies
Open accessAbstract
Leaf area index (LAI) is an important variable for climate modeling, estimates of primary production, agricultural yield forecasting, and many other diverse studies. Remote sensing provides a considerable potential for estimating LAI at local to regional and global scales. Several spectral vegetation indices have been proposed, but their capacity to estimate LAI is highly reduced at moderate‐to‐high LAI. In this paper, we propose a technique to estimate LAI and green leaf biomass remotely using reflectances in two spectral channels either in the green around 550 nm, or at the red edge near 700 nm, and in the NIR (beyond 750 nm). The technique was tested in agricultural fields under a maize canopy, and proved suitable for accurate estimation of LAI ranging from 0 to more than 6.
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Cited by
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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
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Cai, Y., Guan, K., Peng, J., Wang, S., Seifert, C., Wardlow, B., & Li, Z. (2018) · Remote Sensing of Environment · doi:10.1016/j.rse.2018.02.045 · Cited by 540
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Metadata
- Authors
- Gitelson, A. A., Viña, A., Arkebauer, T. J., Rundquist, D. C., Keydan, G., & Leavitt, B.
- Venue
- Geophysical Research Letters
- Publisher
- American Geophysical Union (AGU)
- Published
- 2003-03
- Volume
- 30
- Issue
- 5
- ISSN
- 0094-8276 (ISSN-L)
- 1944-8007
- OpenAlex
- W2149813070
- Cited by
- 886
- References
- 0
- FWCI
- 5.69
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Gitelson, A. A., Viña, A., Arkebauer, T. J., Rundquist, D. C., Keydan, G., & Leavitt, B. (2003). Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters. https://doi.org/10.1029/2002gl016450
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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