Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer

[1]  John R. Miller,et al.  Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .

[2]  Mathias Disney,et al.  Monte Carlo ray tracing in optical canopy reflectance modelling , 2000 .

[3]  Andrew K. Skidmore,et al.  Dry season mapping of savanna forage quality, using the hyperspectral Carnegie Airborne Observatory sensor , 2011 .

[4]  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..

[5]  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 .

[6]  Tomáš Polák,et al.  Does the azimuth orientation of Norway spruce (Picea abies/L./Karst.) branches within sunlit crown part influence the heterogeneity of biochemical, structural and spectral characteristics of needles? , 2007 .

[7]  T. Painter,et al.  Reflectance quantities in optical remote sensing - definitions and case studies , 2006 .

[8]  P. Curran Remote sensing of foliar chemistry , 1989 .

[9]  G. Heinson,et al.  Electrical evidence of continental accretion: Steeply‐dipping crustal‐scale conductivity contrast , 2006 .

[10]  M. Schaepman,et al.  Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval , 2010 .

[11]  Moon S. Kim,et al.  Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .

[12]  R. Myneni,et al.  A Three-Dimensional Radiative Transfer Method for Optical Remote Sensing of Vegetated Land Surfaces , 1991, [Proceedings] IGARSS'91 Remote Sensing: Global Monitoring for Earth Management.

[13]  M. Schaepman,et al.  Applicability of the PROSPECT model for Norway spruce needles , 2006 .

[14]  Roberta E. Martin,et al.  PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .

[15]  Jean-Luc Widlowski,et al.  The RAMI On-line Model Checker (ROMC): A web-based benchmarking facility for canopy reflectance models , 2008 .

[16]  R. Clark,et al.  Reflectance spectroscopy: Quantitative analysis techniques for remote sensing applications , 1984 .

[17]  F. Baret,et al.  Neural network estimation of LAI, fAPAR, fCover and LAI×Cab, from top of canopy MERIS reflectance data : Principles and validation , 2006 .

[18]  E. Milton,et al.  The use of the empirical line method to calibrate remotely sensed data to reflectance , 1999 .

[19]  A. Wellburn The Spectral Determination of Chlorophylls a and b, as well as Total Carotenoids, Using Various Solvents with Spectrophotometers of Different Resolution* , 1994 .

[20]  Zuzana Lhotáková,et al.  Measurement methods and variability assessment of the Norway spruce total leaf area: implications for remote sensing , 2013, Trees.

[21]  V. Demarez,et al.  Modeling radiative transfer in heterogeneous 3-D vegetation canopies , 1996 .

[22]  Jadunandan Dash,et al.  The potential of the MERIS Terrestrial Chlorophyll Index for carbon flux estimation , 2010 .

[23]  Nadine Gobron,et al.  Horizontal radiation transport in 3-D forest canopies at multiple spatial resolutions: Simulated impact on canopy absorption , 2006 .

[24]  Luis Alonso,et al.  Gridding Artifacts on Medium-Resolution Satellite Image Time Series: MERIS Case Study , 2011, IEEE Transactions on Geoscience and Remote Sensing.

[25]  S. Ustin,et al.  Estimating leaf biochemistry using the PROSPECT leaf optical properties model , 1996 .

[26]  Shunlin Liang,et al.  Earth system science related imaging spectroscopy — an assessment , 2009 .

[27]  J. Clevers Application of a weighted infrared-red vegetation index for estimating leaf Area Index by Correcting for Soil Moisture , 1989 .

[28]  C. Willmott ON THE VALIDATION OF MODELS , 1981 .

[29]  Philip Lewis,et al.  3D modelling of forest canopy structure for remote sensing simulations in the optical and microwave domains , 2006 .

[30]  R. Clark,et al.  Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data , 2003 .

[31]  Michael E. Schaepman,et al.  Retrieval of foliar information about plant pigment systems from high resolution spectroscopy , 2009 .

[32]  Giuseppina Rea,et al.  Technological applications of chlorophyll a fluorescence for the assessment of environmental pollutants , 2011, Analytical and bioanalytical chemistry.

[33]  D. Roberts,et al.  Mapping two Eucalyptus subgenera using multiple endmember spectral mixture analysis and continuum-removed imaging spectrometry data , 2011 .

[34]  H. Scheer,et al.  A Red-Shifted Chlorophyll , 2010, Science.

[35]  R. Clark,et al.  Spectroscopic Determination of Leaf Biochemistry Using Band-Depth Analysis of Absorption Features and Stepwise Multiple Linear Regression , 1999 .

[36]  Pauline Stenberg,et al.  Simulations of the effects of shoot structure and orientation on vertical gradients in intercepted light by conifer canopies. , 1996, Tree physiology.

[37]  M. Marek,et al.  Test of Accuracy of LAI Estimation by LAI-2000 under Artificially Changed Leaf to Wood Area Proportions , 2000, Biologia Plantarum.

[38]  A. Wellburn,et al.  The spectral determination of chlorophyll a and chlorophyll b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. , 1994 .

[39]  S. Ustin,et al.  Mapping nonnative plants using hyperspectral imagery , 2003 .

[40]  Jing M. Chen,et al.  Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery , 2008 .

[41]  R. Richter,et al.  Geo-atmospheric processing of airborne imaging spectrometry data. Part 2: Atmospheric/topographic correction , 2002 .

[42]  Clement Atzberger,et al.  Retrieval of chlorophyll and nitrogen in Norway spruce (Picea abies L. Karst.) using imaging spectroscopy , 2010, Int. J. Appl. Earth Obs. Geoinformation.

[43]  D. Normile,et al.  Round and round: a guide to the carbon cycle. , 2009, Science.

[44]  J. Dungan,et al.  Estimating the foliar biochemical concentration of leaves with reflectance spectrometry: Testing the Kokaly and Clark methodologies , 2001 .

[45]  C. Jordan Derivation of leaf-area index from quality of light on the forest floor , 1969 .

[46]  F. Baret,et al.  PROSPECT: A model of leaf optical properties spectra , 1990 .

[47]  Peter M. Atkinson,et al.  The use of MERIS Terrestrial Chlorophyll Index to study spatio-temporal variation in vegetation phenology over India , 2010 .

[48]  N. Goel,et al.  Needle chlorophyll content estimation through model inversion using hyperspectral data from boreal conifer forest canopies , 2004 .

[49]  A. Gitelson,et al.  Three‐band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves , 2006 .

[50]  Jean-Philippe Gastellu-Etchegorry,et al.  DART: a 3D model for simulating satellite images and studying surface radiation budget , 2004 .

[51]  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.

[52]  Yuri Knyazikhin,et al.  Retrieval of canopy biophysical variables from bidirectional reflectance Using prior information to solve the ill-posed inverse problem , 2003 .

[53]  Olga Sykioti,et al.  Monitoring canopy biophysical and biochemical parameters in ecosystem scale using satellite hyperspectral imagery: An application on a Phlomis fruticosa Mediterranean ecosystem using multiangular CHRIS/PROBA observations , 2010 .

[54]  John R. Miller,et al.  Estimating chlorophyll concentration in conifer needles with hyperspectral data: An assessment at the needle and canopy level , 2008 .

[55]  R. Myneni Modeling radiative transfer and photosynthesis in three-dimensional vegetation canopies , 1991 .

[56]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[57]  J. Pisek,et al.  Estimation of vegetation clumping index using MODIS BRDF data , 2011 .

[58]  J. Grace,et al.  Ecophysiological controls over the net ecosystem exchange of mountain spruce stand. Comparison of the response in direct vs. diffuse solar radiation , 2007 .

[59]  A. Skidmore,et al.  Spectral discrimination of vegetation types in a coastal wetland , 2003 .

[60]  D S Kimes,et al.  Radiative transfer model for heterogeneous 3-D scenes. , 1982, Applied optics.

[61]  R. J. Porra,et al.  Determination of accurate extinction coefficients and simultaneous equations for assaying chlorophylls a and b extracted with four different solvents: verification of the concentration of chlorophyll standards by atomic absorption spectroscopy , 1989 .

[62]  A. Gitelson,et al.  Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm , 1996 .

[63]  N. Broge,et al.  Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density , 2001 .

[64]  P. Stenberg,et al.  A method to account for shoot scale clumping in coniferous canopy reflectance models , 2003 .

[65]  Michael E. Schaepman,et al.  Influence of woody elements of a Norway spruce canopy on nadir reflectance simulated by the DART model at very high spatial resolution , 2008 .