Data from: A hyperspectral image can predict tropical tree growth rates in single-species stands

T. Trevor Caughlin, Sarah J. Graves, Gregory P. Asner, Michiel Van Breugel, Jefferson S. Hall, Roberta E. Martin, Mark S. Ashton & Stephanie A. Bohlman
Remote sensing is increasingly needed to meet the critical demand for estimates of forest structure and composition at landscape to continental scales. Hyperspectral images can detect tree canopy properties, including species identity, leaf chemistry and disease. Tree growth rates are related to these measurable canopy properties but whether growth can be directly predicted from hyperspectral data remains unknown. We used a single hyperspectral image and LiDAR-derived elevation to predict growth rates for twenty tropical tree...
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