Analyzing the performance of PROSPECT model inversion based on different spectral information for leaf biochemical properties retrieval

Allen, 1969, Interaction of isotropic light with a compact plant leaf, JOSA, 59, 1376, 10.1364/JOSA.59.001376 Allen, 1968, Interaction of light with a plant canopy, JOSA, 58, 1023, 10.1364/JOSA.58.001023 Arabian, J., 2015. Retrieving leaf chlorophyll content in wheat and corn using Landsat-8 imagery. In. Baldocchi, 1994, A comparative study of mass and energy exchange rates over a closed C 3 (wheat) and an open C 4 (corn) crop: II. CO 2 exchange and water use efficiency, Agric. For. Meteorol., 67, 291, 10.1016/0168-1923(94)90008-6 Bowyer, 2004, Sensitivity of spectral reflectance to variation in live fuel moisture content at leaf and canopy level, Remote Sens. Environ., 92, 297, 10.1016/j.rse.2004.05.020 Cannavó, 2012, Sensitivity analysis for volcanic source modeling quality assessment and model selection, Comput. Geosci., 44, 52, 10.1016/j.cageo.2012.03.008 Curran, 2001, Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: testing the Kokaly and Clark methodologies, Remote Sens. Environ., 76, 349, 10.1016/S0034-4257(01)00182-1 Dawson, 1998, LIBERTY—Modeling the effects of leaf biochemical concentration on reflectance spectra, Remote Sens. Environ., 65, 50, 10.1016/S0034-4257(98)00007-8 Féret, 2011, Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling, Remote Sens. Environ., 115, 2742, 10.1016/j.rse.2011.06.016 Féret, 2017, PROSPECT-D: Towards modeling leaf optical properties through a complete lifecycle, Remote Sens. Environ., 193, 204, 10.1016/j.rse.2017.03.004 Feret, 2008, PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments, Remote Sens. Environ., 112, 3030, 10.1016/j.rse.2008.02.012 Gastellu-Etchegorry, 1996, Modeling radiative transfer in heterogeneous 3-D vegetation canopies, Remote Sens. Environ., 58, 131, 10.1016/0034-4257(95)00253-7 Gitelson, 2006, Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves, Geophys. Res. Lett., 33, 10.1029/2006GL026457 Govaerts, 1998, Raytran: A Monte Carlo ray-tracing model to compute light scattering in three-dimensional heterogeneous media, IEEE Trans. Geosci. Remote Sens., 36, 493, 10.1109/36.662732 Hooper, 1997, The effects of plant composition and diversity on ecosystem processes, Science, 277, 1302, 10.1126/science.277.5330.1302 Hosgood, B., Jacquemoud, S., Andreoli, G., Verdebout, J., Pedrini, G., Schmuck, G., 1995. Leaf optical properties experiment 93 (LOPEX93). Ispra Italy’European Commission, Joint Research Centre Institute of Remote Sensing Applications. Huete, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195, 10.1016/S0034-4257(02)00096-2 Huete, 1997, A comparison of vegetation indices over a global set of TM images for EOS-MODIS, Remote Sens. Environ., 59, 440, 10.1016/S0034-4257(96)00112-5 Jacquemoud, 2000, Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode, Remote Sens. Environ., 74, 471, 10.1016/S0034-4257(00)00139-5 Jacquemoud, 1990, PROSPECT: A model of leaf optical properties spectra, Remote Sens. Environ., 34, 75, 10.1016/0034-4257(90)90100-Z Jacquemoud, 1996, Estimating leaf biochemistry using the PROSPECT leaf optical properties model, Remote Sens. Environ., 56, 194, 10.1016/0034-4257(95)00238-3 Jacquemoud, 2009, PROSPECT+ SAIL models: A review of use for vegetation characterization, Remote Sens. Environ., 113, S56, 10.1016/j.rse.2008.01.026 Kumar, 1973, Light ray tracing through a leaf cross section, Appl. Opt., 12, 2950, 10.1364/AO.12.002950 LaCapra, 1996, Remote sensing of foliar chemistry of inundated rice with imaging spectrometry, Remote Sens. Environ., 55, 50, 10.1016/0034-4257(95)00185-9 Li, 2011, Retrieval of leaf biochemical parameters using PROSPECT inversion: A new approach for alleviating ill-posed problems, IEEE Trans. Geosci. Remote Sens., 49, 2499, 10.1109/TGRS.2011.2109390 Ma, 2017, Retrieving forest canopy extinction coefficient from terrestrial and airborne lidar, Agric. For. Meteorol., 236, 1, 10.1016/j.agrformet.2017.01.004 Maier, 1999, SLOP: A revised version of the stochastic model for leaf optical properties, Remote Sens. Environ., 68, 273, 10.1016/S0034-4257(98)00118-7 Markwell, 1995, Calibration of the Minolta SPAD-502 leaf chlorophyll meter, Photosynth. Res., 46, 467, 10.1007/BF00032301 Martin, 1997, High spectral resolution remote sensing of forest canopy lignin, nitrogen, and ecosystem processes, Ecol. Appl., 7, 431, 10.1890/1051-0761(1997)007[0431:HSRRSO]2.0.CO;2 Milenković, 2017, Total canopy transmittance estimated from small-footprint, full-waveform airborne LiDAR, ISPRS J. Photogramm. Remote Sens., 128, 61, 10.1016/j.isprsjprs.2017.03.008 Morsdorf, 2006, Estimation of LAI and fractional cover from small footprint airborne laser scanning data based on gap fraction, Remote Sens. Environ., 104, 50, 10.1016/j.rse.2006.04.019 Morsdorf, 2009, Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling, Remote Sens. Environ., 113, 2152, 10.1016/j.rse.2009.05.019 Naud, 2009, Leaf transmittance measurements can improve predictions of the nitrogen status for winter wheat crop, Field Crops Res., 110, 27, 10.1016/j.fcr.2008.06.012 Oshio, 2016, Estimating the solar transmittance of urban trees using airborne LiDAR and radiative transfer simulation, IEEE Trans. Geosci. Remote Sens., 54, 5483, 10.1109/TGRS.2016.2565699 Parker, 2001, Light transmittance in forest canopies determined using airborne laser altimetry and in-canopy quantum measurements, Remote Sens. Environ., 76, 298, 10.1016/S0034-4257(00)00211-X Riaño, 2005, Estimation of fuel moisture content by inversion of radiative transfer models to simulate equivalent water thickness and dry matter content: Analysis at leaf and canopy level, IEEE Trans. Geosci. Remote Sens., 43, 819, 10.1109/TGRS.2005.843316 Sims, 2002, Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages, Remote Sens. Environ., 81, 337, 10.1016/S0034-4257(02)00010-X Solberg, 2006, Mapping defoliation during a severe insect attack on Scots pine using airborne laser scanning, Remote Sens. Environ., 102, 364, 10.1016/j.rse.2006.03.001 Ustin, 2009, Retrieval of foliar information about plant pigment systems from high resolution spectroscopy, Remote Sens. Environ., 113, S67, 10.1016/j.rse.2008.10.019 Ustin, 2004, Using imaging spectroscopy to study ecosystem processes and properties, Bioscience, 54, 523, 10.1641/0006-3568(2004)054[0523:UISTSE]2.0.CO;2 Verhoef, 1984, Light scattering by leaf layers with application to canopy reflectance modeling: the SAIL model, Remote Sens. Environ., 16, 125, 10.1016/0034-4257(84)90057-9 Wang, 2015, Applicability of the PROSPECT model for estimating protein and cellulose+ lignin in fresh leaves, Remote Sens. Environ., 168, 205, 10.1016/j.rse.2015.07.007 Zhang, 2008, Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery, Remote Sens. Environ., 112, 3234, 10.1016/j.rse.2008.04.005 Zhao, 2014, Early detection of crop injury from herbicide glyphosate by leaf biochemical parameter inversion, Int. J. Appl. Earth Obs. Geoinf., 31, 78 Zhao, 2013, Hyperspectral remote sensing of plant biochemistry using Bayesian model averaging with variable and band selection, Remote Sens. Environ., 132, 102, 10.1016/j.rse.2012.12.026