Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data

By Peng Gong, Ruiliang Pu, G. Biging, Mirta Rosa Larrieu. IEEE Transactions on Geoscience and Remote Sensing, 2003

428 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/0bd8ee2bf2156871db25256cb77f67fda118e7bc

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In Environmental Engineering

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Citations in the corpus

A new vegetation index based on the universal pattern decomposition method (2007, background): “Direct measure of canopy LAI is relatively accurate but extremely labourintensive and destructive (Gong et al. 2003).”
Remote sensing of forest biophysical variables using HyMap imaging spectrometer data (2005, methodology): “For instance, Gong et al. (2003) estimated forest LAI using vegetation indices derived from Hyperion hyperspectral data.”
In-Season Estimation of Corn Yield Potential Using Proximal Sensing (2017, background): “…c spectra of light, typically in the visible (VIS; green, red, or red-edge) and the near-infrared (NIR), from the plant canopy providing a wide range of vegetation indices such as the NDVI ([NIR–VIS]/[NIR+VIS]) (Rouse et al., 1973) and the inverse simple ratio (ISR; [VIS/NIR]) (Gong et al., 2003).”
Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data (2008, background): “canopy as well as on the underlying soil properties, illumination conditions, and viewing geometry [20], [22], [42], [59].”
Performance evaluation of spectral vegetation indices using a statistical sensitivity function (2007, methodology): “Previous studies have frequently used regression techniques to evaluate the effectiveness of various VIs as predictors of biophysical parameters (e.g., Gong et al., 2003; Haboudane et al., 2004; Lawrence & Ripple, 1998; Purevdorj et al., 1998).”
A unified vegetation index for quantifying the terrestrial biosphere (2021, methodology): “Unlike previous approaches to improve indices based on principled ( 10 , 20 , 21 ) or heuristic parametric transformations ( 11 , 12 , 22 , 23 ), here we adopt a machine learning standpoint using the theory of kernel methods, which has been widely used to derive nonlinear algorithms from linear…”
Tree Species Classification in Boreal Forests With Hyperspectral Data (2013, methodology): “combined acquisition using both sensors might be useful as the SWIR bands can be used for other purposes, such as forest biophysical characteristic estimation [38].”