Improving the PROSPECT Model to Consider Anisotropic Scattering of Leaf Internal Materials and Its Use for Retrieving Leaf Biomass in Fresh Leaves
暂无分享,去创建一个
Weimin Ju | Jing M. Chen | Jun Wang | Feng Qiu | Qian Zhang | Meihong Fang | W. Ju | J. Chen | Meihong Fang | Jun Wang | Qian Zhang | Feng Qiu
[1] W. Verhoef,et al. PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .
[2] Pablo J. Zarco-Tejada,et al. 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 , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[3] Margaret Kalacska,et al. Differences in leaf traits, leaf internal structure, and spectral reflectance between two communities of lianas and trees: Implications for remote sensing in tropical environments , 2009 .
[4] L. Poorter,et al. Causes and consequences of variation in leaf mass per area (LMA): a meta-analysis. , 2009, The New phytologist.
[5] S. Ustin,et al. Estimating leaf biochemistry using the PROSPECT leaf optical properties model , 1996 .
[6] H. Lichtenthaler. CHLOROPHYLL AND CAROTENOIDS: PIGMENTS OF PHOTOSYNTHETIC BIOMEMBRANES , 1987 .
[7] P. Matile,et al. Biochemistry of Indian summer: physiology of autumnal leaf coloration , 2000, Experimental Gerontology.
[8] R. Clark,et al. Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression , 1999 .
[9] C. Wessman,et al. Remote sensing of canopy chemistry and nitrogen cycling in temperate forest ecosystems , 1988, Nature.
[10] Roberta E. Martin,et al. Multi-method ensemble selection of spectral bands related to leaf biochemistry , 2015 .
[11] John R. Miller,et al. Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .
[12] K. Thompson,et al. The plant traits that drive ecosystems: Evidence from three continents , 2004 .
[13] H. Gausman,et al. Interaction of Isotropic Light with a Compact Plant Leaf , 1969 .
[14] J. Chen,et al. Retrieving chlorophyll content in conifer needles from hyperspectral measurements , 2008, Canadian Journal of Remote Sensing.
[15] Xianjun Hao,et al. Estimating dry matter content from spectral reflectance for green leaves of different species , 2011 .
[16] W. Smith,et al. Ontogenetic differences in mesophyll structure and chlorophyll distribution in Eucalyptus globulus ssp. globulus. , 1999, American journal of botany.
[17] K. Soudani,et al. Calibration and validation of hyperspectral indices for the estimation of broadleaved forest leaf chlorophyll content, leaf mass per area, leaf area index and leaf canopy biomass , 2008 .
[18] A. Gitelson,et al. Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC) , 2015 .
[19] Margaret Kalacska,et al. Estimation of foliar chlorophyll and nitrogen content in an ombrotrophic bog from hyperspectral data: Scaling from leaf to image , 2015 .
[20] Emilio Chuvieco,et al. Linking ecological information and radiative transfer models to estimate fuel moisture content in the Mediterranean region of Spain: Solving the ill-posed inverse problem , 2009 .
[21] P. Reich,et al. From tropics to tundra: global convergence in plant functioning. , 1997, Proceedings of the National Academy of Sciences of the United States of America.
[22] Jean-Baptiste Féret,et al. Deriving leaf mass per area (LMA) from foliar reflectance across a variety of plant species using continuous wavelet analysis , 2014 .
[23] Yuri Knyazikhin,et al. Retrieval of canopy biophysical variables from bidirectional reflectance Using prior information to solve the ill-posed inverse problem , 2003 .
[24] D. Sims,et al. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .
[25] K. Barry,et al. Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling , 2011 .
[26] H. Mohr,et al. ABSORPTION SPECTRA OF LEAVES CORRECTED FOR SCATTERING and DISTRIBUTIONAL ERROR: A RADIATIVE TRANSFER and ABSORPTION STATISTICS TREATMENT , 1993 .
[27] Sean C. Thomas,et al. The worldwide leaf economics spectrum , 2004, Nature.
[28] John R. Miller,et al. Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data , 2001, IEEE Trans. Geosci. Remote. Sens..
[29] Marco Heurich,et al. Estimating leaf functional traits by inversion of PROSPECT: Assessing leaf dry matter content and specific leaf area in mixed mountainous forest , 2016, Int. J. Appl. Earth Obs. Geoinformation.
[30] G. Carter,et al. Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. , 2001, American journal of botany.
[31] L. C. Henyey,et al. Diffuse radiation in the Galaxy , 1940 .
[32] J. Norman,et al. Leaf Optical Properties , 1991 .
[33] Philip A. Townsend,et al. Quantifying the influences of spectral resolution on uncertainty in leaf trait estimates through a Bayesian approach to RTM inversion , 2016 .
[34] Quan Wang,et al. Retrieval of Leaf Biochemical Parameters Using PROSPECT Inversion: A New Approach for Alleviating Ill-Posed Problems , 2011, IEEE Transactions on Geoscience and Remote Sensing.
[35] Holly Croft,et al. The applicability of empirical vegetation indices for determining leaf chlorophyll content over different leaf and canopy structures , 2014 .
[36] E. Hunt,et al. Estimating near-infrared leaf reflectance from leaf structural characteristics. , 2001, American journal of botany.
[37] E. Garnier,et al. Leaf anatomy, specific mass and water content in congeneric annual and perennial grass species , 1994 .
[38] Thomas C. Vogelmann,et al. The functional significance of palisade tissue : penetration of directional versus diffuse light , 1993 .
[39] H. Lichtenthaler. Vegetation stress : an introduction to the stress concept in plants , 1996 .
[40] S. Jacquemoud,et al. Leaf BRDF measurements and model for specular and diffuse components differentiation , 2005 .
[41] A. Skidmore,et al. Applicability of the PROSPECT model for estimating protein and cellulose + lignin in fresh leaves , 2015 .
[42] Jing M. Chen,et al. Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery , 2008 .
[43] Roberta E. Martin,et al. Taxonomy and remote sensing of leaf mass per area (LMA) in humid tropical forests. , 2011, Ecological applications : a publication of the Ecological Society of America.
[44] J. Cornelissen,et al. Leaf structure and anatomy as related to leaf mass per area variation in seedlings of a wide range of woody plant species and types , 2000, Oecologia.
[45] Yuri A. Gritz,et al. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.
[46] F. Baret,et al. PROSPECT: A model of leaf optical properties spectra , 1990 .
[47] K. Chartzoulakisa,et al. Water stress affects leaf anatomy , gas exchange , water relations and growth of two avocado cultivars , 2002 .
[48] Pablo J. Zarco-Tejada,et al. Chlorophyll Fluorescence Effects on Vegetation Apparent Reflectance: I. Leaf-Level Measurements and Model Simulation , 2000 .
[49] William K. Smith,et al. Chlorophyll and light gradients in sun and shade leaves of Spinacia oleracea , 1991 .
[50] Peter E. Thornton,et al. Parameterization and Sensitivity Analysis of the BIOME–BGC Terrestrial Ecosystem Model: Net Primary Production Controls , 2000 .
[51] Flavio Cannavó,et al. Sensitivity analysis for volcanic source modeling quality assessment and model selection , 2012, Comput. Geosci..
[52] Pol Coppin,et al. A dorsiventral leaf radiative transfer model: Development, validation and improved model inversion techniques , 2009 .
[53] S. Ustin,et al. Leaf Optical Properties , 2019 .
[54] P. Zarco-Tejada,et al. Carotenoid content estimation in a heterogeneous conifer forest using narrow-band indices and PROSPECT + DART simulations , 2012 .
[55] C. François,et al. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements , 2004 .
[56] Albert Olioso,et al. Modeling directional–hemispherical reflectance and transmittance of fresh and dry leaves from 0.4 μm to 5.7 μm with the PROSPECT-VISIR model , 2011 .
[57] J. Cornelissen,et al. Functional leaf attributes predict litter decomposition rate in herbaceous plants. , 1997, The New phytologist.
[58] Roberta E. Martin,et al. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .
[59] Hendrik Poorter,et al. Exploring variation in leaf mass per area (LMA) from leaf to cell: an anatomical analysis of 26 woody species. , 2013, American journal of botany.
[60] Alan K. Knapp,et al. Light and chlorophyll gradients within Cucurbita cotyledons , 1988 .
[61] Marta Yebra,et al. Estimation of dry matter content in leaves using normalized indexes and PROSPECT model inversion , 2012 .