Hyperspectral remote sensing of plant pigments.

The dynamics of pigment concentrations are diagnostic of a range of plant physiological properties and processes. This paper appraises the developing technologies and analytical methods for quantifying pigments non-destructively and repeatedly across a range of spatial scales using hyperspectral remote sensing. Progress in deriving predictive relationships between various characteristics and transforms of hyperspectral reflectance data are evaluated and the roles of leaf and canopy radiative transfer models are reviewed. Requirements are identified for more extensive intercomparisons of different approaches and for further work on the strategies for interpreting canopy scale data. The paper examines the prospects for extending research to the wider range of pigments in addition to chlorophyll, testing emerging methods of hyperspectral analysis and exploring the fusion of hyperspectral and LIDAR remote sensing. In spite of these opportunities for further development and the refinement of techniques, current evidence of an expanding range of applications in the ecophysiological, environmental, agricultural, and forestry sciences highlights the growing value of hyperspectral remote sensing of plant pigments.

[1]  R. Colwell.  Remote sensing of the environment , 1980, Nature.

[2]  H. Lichtenthaler.  CHLOROPHYLL AND CAROTENOIDS: PIGMENTS OF PHOTOSYNTHETIC BIOMEMBRANES , 1987 .

[3]  John R. Miller,et al.  Quantitative characterization of the vegetation red edge reflectance 1. An inverted-Gaussian reflectance model , 1990 .

[4]  Andrew J. Young,et al.  Carotenoids and stress , 1990 .

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

[6]  R. Alscher,et al.  Stress responses in plants: Adaptation and acclimation mechanisms. , 1990 .

[7]  F. Boochs,et al.  Shape of the red edge as vitality indicator for plants , 1990 .

[8]  J. Dungan,et al.  The effect of a red leaf pigment on the relationship between red edge and chlorophyll concentration , 1991 .

[9]  S. Fujimura,et al.  Nondestructive measurement of chlorophyll pigment content in plant leaves from three-color reflectance and transmittance. , 1991, Applied optics.

[10]  G. Guyot,et al.  Physical measurements and signatures in remote sensing , 1992 .

[11]  C. Field,et al.  A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency , 1992 .

[12]  Moon S. Kim,et al.  Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and carotenoids in soybean leaves , 1992 .

[13]  Carle M. Pieters,et al.  Estimating modal abundances from the spectra of natural and laboratory pyroxene mixtures using the modified Gaussian model , 1993 .

[14]  D. M. Moss,et al.  Red edge spectral measurements from sugar maple leaves , 1993 .

[15]  Moon S. Kim,et al.  The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation (A par) , 1994 .

[16]  J. Hughes,et al.  A FULLY AUTOMATED DUAL‐WAVELENGTH PHOTOMETER FOR PHYTOCHROME MEASUREMENTS AND ITS APPLICATION TO PHYTOCHROME FROM CHLOROPHYLLCONTAINING EXTRACE , 1994 .

[17]  Josep Peñuelas,et al.  Evaluating Wheat Nitrogen Status with Canopy Reflectance Indices and Discriminant Analysis , 1995 .

[18]  Amara Lynn Graps,et al.  An introduction to wavelets , 1995 .

[19]  P. A. Scolnik,et al.  Plant carotenoids: pigments for photoprotection, visual attraction, and human health. , 1995, The Plant cell.

[20]  B. Yoder,et al.  Predicting nitrogen and chlorophyll content and concentrations from reflectance spectra (400–2500 nm) at leaf and canopy scales , 1995 .

[21]  C. Elvidge,et al.  Comparison of broad-band and narrow-band red and near-infrared vegetation indices , 1995 .

[22]  F. M. Danson,et al.  Extraction of vegetation biophysical parameters by inversion of the PROSPECT + SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors , 1995 .

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

[24]  A. Gitelson,et al.  Non-destructive determination of chlorophyll content of leaves of a green and an aurea mutant of tobacco by reflectance measurements , 1996 .

[25]  B. Demmig‐Adams,et al.  The role of xanthophyll cycle carotenoids in the protection of photosynthesis , 1996 .

[26]  J. Schepers,et al.  Transmittance and reflectance measurements of corn leaves from plants with different nitrogen and water supply , 1996 .

[27]  Marco Mariotti,et al.  Spectral properties of iron-deficient corn and sunflower leaves☆ , 1996 .

[28]  S. Robinson,et al.  Internal and external photoprotection in developing leaves of the CAM plant Cotyledon orbiculata , 1997 .

[29]  Henry L. Gholz,et al.  The Use of Remote Sensing in the Modeling of Forest Productivity , 1997, Forestry Sciences.

[30]  A. Gitelson,et al.  Remote estimation of chlorophyll content in higher plant leaves , 1997 .

[31]  Belinda E. Medlyn,et al.  Energy Conversion and Use in Forests: An Analysis of Forest Production in Terms of Radiation Utilisation Efficiency (ɛ) , 1997 .

[32]  L. Johnson,et al.  LEAFMOD : A new within-leaf radiative transfer model , 1998 .

[33]  B. Grimm,et al.  Consequences of chlorophyll deficiency for leaf carotenoid composition in tobacco synthesizing glutamate 1-semialdehyde aminotransferase antisense RNA: dependency on developmental age and growth light , 1998 .

[34]  G. A. Blackburn,et al.  Spectral indices for estimating photosynthetic pigment concentrations: A test using senescent tree leaves , 1998 .

[35]  G. A. Blackburn,et al.  Quantifying Chlorophylls and Caroteniods at Leaf and Canopy Scales: An Evaluation of Some Hyperspectral Approaches , 1998 .

[36]  P. Curran,et al.  A new technique for interpolating the reflectance red edge position , 1998 .

[37]  John C. Bouwkamp,et al.  Chlorophyllase activities and chlorophyll degradation during leaf senescence in non-yellowing mutant and wild type of Phaseolus vulgaris L. , 1998 .

[38]  B. Datt.  Remote Sensing of Chlorophyll a, Chlorophyll b, Chlorophyll a+b, and Total Carotenoid Content in Eucalyptus Leaves , 1998 .

[39]  Linda Chalker-Scott,et al.  Environmental Significance of Anthocyanins in Plant Stress Responses , 1999 .

[40]  John A. Gamon,et al.  Assessing leaf pigment content and activity with a reflectometer , 1999 .

[41]  A. Gitelson,et al.  Non‐destructive optical detection of pigment changes during leaf senescence and fruit ripening , 1999 .

[42]  K. Gould,et al.  Optical properties of leaves in relation to anthocyanin concentration and distribution , 1999 .

[43]  Valérie Demarez,et al.  Seasonal variation of leaf chlorophyll content of a temperate forest. Inversion of the PROSPECT model , 1999 .

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

[45]  William D. Philpot,et al.  Yellowness index: An application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation , 1999 .

[46]  George Alan Blackburn,et al.  Relationships between Spectral Reflectance and Pigment Concentrations in Stacks of Deciduous Broadleaves , 1999 .

[47]  G. A. Blackburn,et al.  Towards the Remote Sensing of Matorral Vegetation Physiology : Relationships between Spectral Reflectance, Pigment, and Biophysical Characteristics of Semiarid Bushland Canopies. , 1999 .

[48]  Mark Cutler,et al.  Estimating Canopy Chlorophyll Concentration from Field and Airborne Spectra , 1999 .

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

[50]  C. Bacour,et al.  Comparison of four radiative transfer models to simulate plant canopies reflectance: direct and inverse mode. , 2000 .

[51]  R. Myneni,et al.  Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data , 2000 .

[52]  M. Archetti,et al.  The origin of autumn colours by coevolution. , 2000, Journal of theoretical biology.

[53]  V. Demarez,et al.  A Modeling Approach for Studying Forest Chlorophyll Content , 2000 .

[54]  A. K. Mitchell,et al.  Differentiation among effects of nitrogen fertilization treatments on conifer seedlings by foliar reflectance: a comparison of methods. , 2000, Tree physiology.

[55]  Pablo J. Zarco-Tejada,et al.  The Bioindicators of Forest Condition Project: a physiological, remote sensing approach. , 2000 .

[56]  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..

[57]  Steven D. Brown,et al.  Robust Calibration with Respect to Background Variation , 2001 .

[58]  Sam P. Brown,et al.  Autumn tree colours as a handicap signal , 2001, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[59]  Dar A. Roberts,et al.  Mapping Canadian boreal forest vegetation using pigment and water absorption features derived from the AVIRIS sensor , 2001 .

[60]  Josep Peñuelas,et al.  An AOTF-based hyperspectral imaging system for field use in ecophysiological and agricultural applications , 2001 .

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

[62]  G. Carter,et al.  Leaf optical properties in higher plants: linking spectral characteristics to stress and chlorophyll concentration. , 2001, American journal of botany.

[63]  A. Richardson,et al.  Spectral reflectance of Picea rubens (Pinaceae) and Abies balsamea (Pinaceae) needles along an elevational gradient, Mt. Moosilauke, New Hampshire, USA. , 2001, American journal of botany.

[64]  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 .

[65]  A. Gitelson,et al.  Optical Properties and Nondestructive Estimation of Anthocyanin Content in Plant Leaves¶ , 2001, Photochemistry and photobiology.

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

[67]  Nicholas C. Coops,et al.  Comparison of green leaf eucalypt spectra using spectral decomposition , 2002 .

[68]  D. Sims,et al.  Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages , 2002 .

[69]  J. Schepers,et al.  Use of Spectral Radiance to Estimate In-Season Biomass and Grain Yield in Nitrogen- and Water-Stressed Corn. , 2002, Crop science.

[70]  Investigation on Physiological Status of Regional Vegetation Using Pushbroom Hyperspectral Imager Data , 2002 .

[71]  Prasad S. Thenkabail,et al.  Evaluation of Narrowband and Broadband Vegetation Indices for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterization , 2002 .

[72]  G. A. Blackburn,et al.  Remote sensing of forest pigments using airborne imaging spectrometer and LIDAR imagery , 2002 .

[73]  Paul J. Curran,et al.  Biochemical and reflectance variation throughout a Sitka spruce canopy , 2002 .

[74]  S. Wand,et al.  Anthocyanins in vegetative tissues: a proposed unified function in photoprotection. , 2002, The New phytologist.

[75]  Gregory A Carter,et al.  Optical properties of intact leaves for estimating chlorophyll concentration. , 2002, Journal of environmental quality.

[76]  Andrew D. Richardson,et al.  An evaluation of noninvasive methods to estimate foliar chlorophyll content , 2002 .

[77]  A. Gitelson,et al.  Assessing Carotenoid Content in Plant Leaves with Reflectance Spectroscopy¶ , 2002, Photochemistry and photobiology.

[78]  Siza D. Tumbo,et al.  HYPERSPECTRAL–BASED NEURAL NETWORK FOR PREDICTING CHLOROPHYLL STATUS IN CORN , 2002 .

[79]  J. Varco,et al.  EARLY DETECTION OF COTTON LEAF NITROGEN STATUS USING LEAF REFLECTANCE , 2002 .

[80]  N. Broge,et al.  Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data , 2002 .

[81]  K. Gould,et al.  Do anthocyanins function as antioxidants in leaves? Imaging of H2O2 in red and green leaves after mechanical injury , 2002 .

[82]  Marilyn C. Ball,et al.  Spatial patterning of pigmentation in evergreen leaves in response to freezing stress , 2003 .

[83]  P. M. Hansena,et al.  Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression , 2003 .

[84]  Pablo J. Zarco-Tejada,et al.  Hyperspectral Remote Sensing of Forest Condition: Estimating Chlorophyll Content in Tolerant Hardwoods , 2003, Forest Science.

[85]  J. Schjoerring,et al.  Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression , 2003 .

[86]  Lei Tian,et al.  A genetic-algorithm-based selective principal component analysis (GA-SPCA) method for high-dimensional data feature extraction , 2003, IEEE Trans. Geosci. Remote. Sens..

[87]  Shiv O. Prasher,et al.  ESTIMATION OF CROP BIOPHYSICAL PARAMETERS THROUGH AIRBORNE AND FIELD HYPERSPECTRAL REMOTE SENSING , 2003 .

[88]  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.

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

[90]  Christine Stone,et al.  Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data. , 2003, Tree physiology.

[91]  S. Dobrowski,et al.  Steady-state chlorophyll a fluorescence detection from canopy derivative reflectance and double-peak red-edge effects , 2003 .

[92]  Raffaele Casa,et al.  Radiation measurement for plant ecophysiology. , 2003, Journal of experimental botany.

[93]  A. Gitelson,et al.  Non-Destructive Assessment of Chlorophyll Carotenoid and Anthocyanin Content in Higher Plant Leaves: Principles and Algorithms , 2004 .

[94]  B. Turner,et al.  Estimating foliage nitrogen concentration from HYMAP data using continuum, removal analysis , 2004 .

[95]  M. Reynolds,et al.  Association between canopy reflectance indices and yield and physiological traits in bread wheat under drought and well-irrigated conditions , 2004 .

[96]  Johanna D. Turnbull,et al.  Comparison of solvent regimes for the extraction of photosynthetic pigments from leaves of higher plants. , 2004, Functional plant biology : FPB.

[97]  D. Roberts,et al.  Using Imaging Spectroscopy to Study Ecosystem Processes and Properties , 2004 .

[98]  J. Markwell,et al.  Calibration of the Minolta SPAD-502 leaf chlorophyll meter , 2004, Photosynthesis Research.

[99]  Sam P. Brown,et al.  The coevolution theory of autumn colours , 2004, Proceedings of the Royal Society of London. Series B: Biological Sciences.

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

[101]  T. Almeida,et al.  Principal component analysis applied to feature-oriented band ratios of hyperspectral data: A tool for vegetation studies , 2004 .

[102]  K. Davies,et al.  Plant pigments and their manipulation. , 2004 .

[103]  Emilio Chuvieco,et al.  Estimation of leaf area index and covered ground from airborne laser scanner (Lidar) in two contrasting forests , 2004 .

[104]  Pablo J. Zarco-Tejada,et al.  Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops , 2004 .

[105]  J. Dash,et al.  The MERIS terrestrial chlorophyll index , 2004 .

[106]  J. Clevers,et al.  Study of heavy metal contamination in river floodplains using the red-edge position in spectroscopic data , 2004 .

[107]  K. Itten,et al.  Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties , 2004 .

[108]  J. J. Colls,et al.  Use of hyperspectral derivative ratios in the red-edge region to identify plant stress responses to gas leaks , 2004 .

[109]  Duli Zhao,et al.  Corn (Zea mays L.) growth, leaf pigment concentration, photosynthesis and leaf hyperspectral reflectance properties as affected by nitrogen supply , 2003, Plant and Soil.

[110]  Antonio Roberto Formaggio,et al.  Narrow band spectral indexes for chlorophyll determination in soybean canopies [Glycine max (L.) Merril] , 2004 .

[111]  Liangyun Liu,et al.  Prediction of grain protein content in winter wheat (Triticum aestivum L.) using plant pigment ratio (PPR) , 2004 .

[112]  J. Peñuelas,et al.  Leaf reflectance and photo‐ and antioxidant protection in field‐grown summer‐stressed Phillyrea angustifolia. Optical signals of oxidative stress? , 2004 .

[113]  C. François,et al.  Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements , 2004 .

[114]  Shufeng Han,et al.  DYNAMIC CALIBRATION AND IMAGE SEGMENTATION METHODS FOR MULTISPECTRAL IMAGING CROP NITROGEN DEFICIENCY SENSORS , 2005 .

[115]  A. Viña,et al.  Remote estimation of canopy chlorophyll content in crops , 2005 .

[116]  Nicholas C. Coops,et al.  A comparison of field-based and modelled reflectance spectra from damaged Pinus radiata foliage , 2005 .

[117]  Ingo Truppel,et al.  Spectral Measurements on ‘Elstar’ Apples during Fruit Development on the Tree , 2005 .

[118]  Dirk D. Reum,et al.  Wavelet Based Multi-Spectral Image Analysis of Corn Leaf Chlorophyll Content , 2005 .

[119]  Pablo J. Zarco-Tejada,et al.  Temporal and Spatial Relationships between within-field Yield variability in Cotton and High-Spatial Hyperspectral Remote Sensing Imagery , 2005 .

[120]  M. Sari,et al.  Determination of seasonal variations in solar energy utilization by the leaves of Washington navel orange trees (Citrus sinensis L. Osbeck) , 2005 .

[121]  Xia Zhang,et al.  Algorithms for the Estimation of the Concentrations of Chlorophyll A and Carotenoids in Rice Leaves from Airborne Hyperspectral Data , 2005, International Conference on Computational Science.

[122]  John R. Miller,et al.  Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .

[123]  LEAF OPTICAL RESPONSES TO LIGHT AND SOIL , 2005 .

[124]  J. Baltzer,et al.  Leaf optical responses to light and soil nutrient availability in temperate deciduous trees. , 2005, American journal of botany.

[125]  V. Kakani,et al.  Selection of Optimum Reflectance Ratios for Estimating Leaf Nitrogen and Chlorophyll Concentrations of Field-Grown Cotton , 2005 .

[126]  A. Viña,et al.  Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity , 2006 .

[127]  M. Cho,et al.  A new technique for extracting the red edge position from hyperspectral data: The linear extrapolation method , 2006 .

[128]  Simon D. Jones,et al.  Continuous wavelet transformations for hyperspectral feature detection , 2006 .

[129]  Johanna Link,et al.  Assessment of cereal nitrogen requirements derived by optical on-the-go sensors on heterogeneous soils , 2006 .

[130]  Kevin S. Powell,et al.  Comparison of PROSPECT and HPLC estimates of leaf chlorophyll contents in a grapevine stress study , 2006 .

[131]  George Alan Blackburn,et al.  Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation , 2007 .

[132]  L. Aurdal,et al.  REMOTE SENSING OF FOLIAR MASS AND CHLOROPHYLL AS INDICATORS OF FOREST HEALTH : PRELIMINARY RESULTS FROM A PROJECT IN NORWAY , 2007 .

[133]  Fumin Wang,et al.  Comparison between back propagation neural network and regression models for the estimation of pigment content in rice leaves and panicles using hyperspectral data , 2007 .

[134]  Dugald C. Close,et al.  The ecophysiology of foliar anthocyanin , 2003, The Botanical Review.