An investigation into robust spectral indices for leaf chlorophyll estimation

By Russell Main, Moses Azong Cho, Renaud Mathieu, M. O’Kennedy, Abel Ramoelo, Susan Koch. 2011

356 citations recorded by the source corpus.

Subfields: Analytical Chemistry, Ecology, Plant Science

View Paper: https://www.semanticscholar.org/paper/fac0f10aa43d51c74f129623453be3a3fa3c2ccd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Jing Tang
2. Juha M. Suomalainen
3. Lammert Kooistra
4. Caroline M. Gevaert
5. Fulya Baysal-Gurel
6. Samuel C. Hassler

Citations in the corpus

• Generation of Spectral–Temporal Response Surfaces by Combining Multispectral Satellite and Hyperspectral UAV Imagery for Precision Agriculture Applications (2015, background): “Narrowband vegetation indices obtained from hyperspectral data have been shown to obtain higher correlations to crop leaf area index (LAI) [6] and chlorophyll content [7] than broadband indices.”
• Estimating crop chlorophyll content with hyperspectral vegetation indices and the hybrid inversion method (2016, background): “Some of these VIs are suitable for both LCC and CCC inversion, whereas others are only suitable for either LCC or CCC (Main et al. 2011; Hunt et al. 2013; Liang et al. 2012).”
• Recent Advances of Hyperspectral Imaging Technology and Applications in Agriculture (2020, background): “[167] investigated 73 vegetation indices for estimating chlorophyll content in crop and savanna tree species.”
• HyperART: non-invasive quantification of leaf traits using hyperspectral absorption-reflectance-transmittance imaging (2015, unknown): “, NDVI, MCARI) [47,48].”