Simple and robust methods for remote sensing of canopy chlorophyll content: a comparative analysis of hyperspectral data for different types of vegetation

AUTHORS

Inoue, Yoshio; Guerif, Martine; Baret, Frederic; Skidmore, Andrew; Gitelson, Anatoly; Schlerf, Martin; Darvishzadeh, Roshanak; Olioso, Albert

ABSTRACT

Authors : Inoue, Yoshio; Guerif, Martine; Baret, Frederic; Skidmore, Andrew; Gitelson, Anatoly; Schlerf, Martin; Darvishzadeh, Roshanak; Olioso, Albert | Abstract :

Canopy chlorophyll content (CCC) is an essential ecophysiological variable for photosynthetic functioning. Remote sensing of CCC is vital for a wide range of ecological and agricultural applications. The objectives of this study were to explore simple and robust algorithms for spectral assessment of CCC. Hyperspectral datasets for six vegetation types (rice, wheat, corn, soybean, sugar beet and natural grass) acquired in four locations (Japan, France, Italy and USA) were analysed. To explore the best predictive model, spectral index approaches using the entire wavebands and multivariable regression approaches were employed. The comprehensive analysis elucidated the accuracy, linearity, sensitivity and applicability of various spectral models. Multivariable regression models using many wavebands proved inferior in applicability to different datasets. A simple model using the ratio spectral index (RSI; R815, R704) with the reflectance at 815 and 704nm showed the highest accuracy and applicability. Simulation analysis using a physically based reflectance model suggested the biophysical soundness of the results. The model would work as a robust algorithm for canopy-chlorophyll-metre and/or remote sensing of CCC in ecosystem and regional scales. The predictive-ability maps using hyperspectral data allow not only evaluation of the relative significance of wavebands in various sensors but also selection of the optimal wavelengths and effective bandwidths.

PUBLISHED IN

PLANT CELL AND ENVIRONMENT Volume: 39 Issue: 12 Pages: 2609-2623 DOI: 10.1111/pce.12815 Published: DEC 2016 Document Type:Article

UMR EMMAH
228 route de l’Aérodrome – CS 40509
84914 Avignon Cedex 9
Google Maps

Contact UMT CAPTE here :

UMT-CAPTE

Hiphen