title: Assessing leaf photoprotective mechanisms using terrestrial LiDAR: towards mapping canopy photosynthetic performance in three dimensions.
abstract: Terrestrial laser scanning (TLS) data allow spatially explicit (x, y, z) laser return intensities to be recorded throughout a plant canopy, which could considerably improve our understanding of how physiological processes vary in three-dimensional space. However, the utility of TLS data for the quantification of plant physiological properties remains largely unexplored. Here, we test whether the laser return intensity of green (532-nm) TLS correlates with changes in the de-epoxidation state of the xanthophyll cycle and photoprotective non-photochemical quenching (NPQ), and compare the ability of TLS to quantify these parameters with the passively measured photochemical reflectance index (PRI). We exposed leaves from five plant species to increasing light intensities to induce NPQ and de-epoxidation of violaxanthin (V) to antheraxanthin (A) and zeaxanthin (Z). At each light intensity, the green laser return intensity (GLRI), narrowband spectral reflectance, chlorophyll fluorescence emission and xanthophyll cycle pigment composition were recorded. Strong relationships between both predictor variables (GLRI, PRI) and both explanatory variables (NPQ, xanthophyll cycle de-epoxidation) were observed. GLRI holds promise to provide detailed (mm) information about plant physiological status to improve our understanding of the patterns and mechanisms driving foliar photoprotection. We discuss the potential for scaling these laboratory data to three-dimensional canopy space.
authors.affiliation: Geospatial Laboratory for Environmental Dynamics, College of Natural Resources, University of Idaho, 875 Perimeter Drive, MS 1135, Moscow, ID, 83844-1135, USA.|McCall Outdoor Science School, University of Idaho, 1800 University Lane, McCall, ID, 83638, USA.
authors.forename: Troy S
authors.initials: TS
authors.lastname: Magney
authors.affiliation: Department of Biology, Bowdoin College, 6500 College Station, Brunswick, ME, 04011, USA.
authors.forename: Spencer A
authors.initials: SA
authors.lastname: Eusden
authors.affiliation: Geospatial Laboratory for Environmental Dynamics, College of Natural Resources, University of Idaho, 875 Perimeter Drive, MS 1135, Moscow, ID, 83844-1135, USA.|McCall Outdoor Science School, University of Idaho, 1800 University Lane, McCall, ID, 83638, USA.
authors.forename: Jan U H
authors.initials: JUH
authors.lastname: Eitel
authors.affiliation: Department of Biology, Bowdoin College, 6500 College Station, Brunswick, ME, 04011, USA.
authors.forename: Barry A
authors.initials: BA
authors.lastname: Logan
authors.affiliation: Geospatial Laboratory for Environmental Dynamics, College of Natural Resources, University of Idaho, 875 Perimeter Drive, MS 1135, Moscow, ID, 83844-1135, USA.|Computer School, Wuhan University, A519, Wuhan, Hubei, 430072, China.
authors.forename: Jingjue
authors.initials: J
authors.lastname: Jiang
authors.affiliation: Geospatial Laboratory for Environmental Dynamics, College of Natural Resources, University of Idaho, 875 Perimeter Drive, MS 1135, Moscow, ID, 83844-1135, USA.|McCall Outdoor Science School, University of Idaho, 1800 University Lane, McCall, ID, 83638, USA.
authors.forename: Lee A
authors.initials: LA
authors.lastname: Vierling
mesh_terms: D002734:Chlorophyll / Q000378:metabolism*; D007834:Lasers; D008027:Light; D010788:Photosynthesis; D045322:Photosynthetic Reaction Center Complex Proteins / Q000378:metabolism; D018515:Plant Leaves / Q000378:metabolism / Q000502:physiology*; D018521:Plant Physiological Phenomena; D010944:Plants; D024341:Xanthophylls / Q000378:metabolism
chemical_list: D045322:Photosynthetic Reaction Center Complex Proteins; D024341:Xanthophylls; D002734:Chlorophyll
keywords: green laser return intensity (GLRI); leaf pigments; light detection and ranging (LiDAR); non-photochemical quenching (NPQ); photochemical reflectance index (PRI); remote sensing; terrestrial laser scanning (TLS); xanthophyll cycle
references.citation: Adams WW, Demmig-Adams B. 1992. Operation of the xanthophyll cycle in higher plants in response to diurnal changes in incident sunlight. Planta 186: 390-398.
references.citation: Ananyev G, Kolber ZS, Klimov D, Falkowski PG, Berry JA, Rascher U, Martin R, Osmond B. 2005. Remote sensing of heterogeneity in photosynthetic efficiency, electron transport and dissipation of excess light in Populus deltoides stands under ambient and elevated CO2 concentrations, and in a tropical forest canopy, using a new laser-induced fluorescence transient device. Global Change Biology 11: 1195-1206.
references.citation: Baldocchi D. 2008. Turner Review No. 15. ‘Breathing’ of the terrestrial biosphere: lessons learned from a global network of carbon dioxide flux measurement systems. Australian Journal of Botany 56: 1-26.
references.citation: Balduzzi MAF, Van der Zande D, Stuckens J, Verstraeten WW, Coppin P. 2011. The properties of terrestrial laser system intensity for measuring leaf geometries: a case study with conference pear trees (Pyrus communis). Sensors 11: 1657-1681.
references.citation: Barton CVM. 2012. Advances in remote sensing of plant stress. Plant and Soil 354: 41-44.
references.citation: Barton CVM, North PRJ. 2001. Remote sensing of canopy light use efficiency using the photochemical reflectance index - model and sensitivity analysis. Remote Sensing of Environment 78: 264-273.
references.citation: Bilger W, Björkman O. 1990. Role of the xanthophylls cycle in photoprotection elucidated by measurements of light-induced absorbance changes, fluorescence and photosynthesis in leaves of Hedera canariensis. Photosynthesis Research 25: 173-186.
references.citation: Bittner S, Gayler S, Biernath C, Winkler JB, Seifert S, Pretzsch H, Priesack E. 2012. Evaluation of a ray-tracing canopy light model based on terrestrial laser scans. Canadian Journal of Remote Sensing 38: 619-628.
references.citation: Björkman O. 1981. Responses to different quantum flux densities. In: Lange OL, Nobel PS, Osmond CB, Ziegler H, eds. Encyclopedia of plant physiology, vol. 12A. Physiological plant ecology I. Responses to the physical environment. Berlin, Germany: Springer-Verlag, 57-107.
references.citation: Bungard RA, Ruban AV, Hibberd JM, Press MC, Horton P, Scholes JD. 1999. Unusual carotenoid composition and a new type of xanthophyll cycle in plants. Proceedings of the National Academy of Sciences, USA 96: 1135-1139.
references.citation: Chen Y, Räikkönen E, Kaasalainen S, Suomalainen J, Hakala T, Hyyppä J, Chen R. 2010. Two-channel hyperspectral LiDAR with a supercontinuum laser source. Sensors 10: 7057-7066.
references.citation: Clawges R, Vierling LA, Calhoon M. 2007. Use of ground-based scanning lidar for estimation of biophysical properties of western larch (Larix occidentalis). International Journal of Remote Sensing 28: 4331-4344.
references.citation: Demmig-Adams B. 1990. Carotenoids and photoprotection in plants: a role for the xanthophyll zeaxanthin. Biochimica et Biophysica Acta 1020: 1-24.
references.citation: Demmig-Adams B, Adams WW III. 1992. Photoprotection and other responses of plants to high light stress. Annual Review of Plant Physiology 43: 599-626.
references.citation: Demmig-Adams B, Adams WW III. 1996. The role of xanthophyll cycle carotenoids in the protection of photosynthesis. Trends in Plant Science 1: 21-26.
references.citation: Demmig-Adams B, Adams WW III. 2006. Photoprotection in an ecological context: the remarkable complexity of thermal energy dissipation. New Phytologist 172: 11-21.
references.citation: Eitel JUH, Vierling LA, Long DS. 2010. Simultaneous measurements of plant structure and chlorophyll content in broadleaf saplings with a terrestrial laser scanner. Remote Sensing of Environment 114: 2229-2237.
references.citation: Eitel JUH, Vierling LA, Long DS, Hunt ER. 2011. Early season remote sensing of wheat nitrogen status using a green scanning laser. Agricultural and Forest Meteorology 151: 1338-1345.
references.citation: Eitel JUH, Vierling LA, Magney TS. 2013. A lightweight, low-cost autonomously operating terrestrial laser scanner for quantifying and monitoring ecosystem structural dynamics. Agricultural and Forest Meteorology 180: 86-96.
references.citation: Fernández-Sarría A, Martínez L, Velázquez-Martí B, Sajdak M, Estornell J, Recio JA. 2013. Different methodologies for calculating crown volumes of Platanus hispanica trees using terrestrial laser scanner and a comparison with classical dendrometric measurements. Computers and Electronics in Agriculture 90: 176-185.
references.citation: Filella I, Amaro T, Araus JL, Peñuelas J. 1996. Relationship between photosynthetic radiation-use efficiency of barley canopies and the photochemical reflectance index (PRI). Physiologia Plantarum 96: 211-216.
references.citation: Filella I, Peñuelas J, Llorens L, Estiarte M. 2004a. Reflectance assessment of seasonal and annual changes in biomass and CO2 uptake of a Mediterranean shrubland submitted to experimental warming and drought. Remote Sensing of Environment 90: 308-318.
references.citation: Filella I, Porcar-Castell A, Munné Bosch S, Bäck J, Garbulsky MF, Peñuelas J. 2004b. PRI assessment of long-term changes in carotenoids/chlorophyll ratio and short-term changes in de-epoxidation state of the xanthophyll cycle. International Journal of Remote Sensing 30: 4443-4455.
references.citation: Gamon JA, Field CB, Bilger W, Björkman O, Fredeen A, Peñuelas J. 1990. Remote sensing of the xanthophyll cycle and chlorophyll fluorescence in sunflower leaves and canopies. Oecologia 85: 1-7.
references.citation: Gamon JA, Field CB, Fredeen AL, Thayer S. 2001. Assessing photosynthetic downregulation in sunflower stands with an optically-based model. Photosynthesis Research 67: 113-125.
references.citation: Gamon JA, Peñuelas J, Field CB. 1992. A narrow-waveband spectral index that tracks diurnal changes in photosynthetic efficiency. Remote Sensing of Environment 41: 35-44.
references.citation: Gamon JA, Serrano L, Surfus JS. 1997. The photochemical reflectance index: an optical indicator of photosynthetic radiation use efficiency across species, functional types, and nutrient levels. Oecologia 112: 492-501.
references.citation: Gamon JA, Surfus JS. 1999. Assessing leaf pigment content and activity with a reflectometer. New Phytologist 143: 105-117.
references.citation: Garbulsky MF, Peñuelas J, Gamon J, Inoue Y, Filella I. 2011. The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: a review and meta-analysis. Remote Sensing of Environment 115: 281-297.
references.citation: Garrity SR, Eitel JUH, Vierling LA. 2011. Disentangling the relationships between plant pigments and the photochemical reflectance index reveals a new approach for remote estimation of carotenoid content. Remote Sensing of Environment 115: 628-635.
references.citation: Garrity SR, Vierling LA, Bickford K. 2010. A simple filtered photodiode instrument for continuous measurement of narrowband NDVI and PRI over vegetated canopies. Agricultural and Forest Meteorology 150: 489-496.
references.citation: Gaulton RA, Danson FM, Ramirez FA, Gunawan O. 2013. The potential of dual-wavelength laser scanning for estimating vegetation moisture content. Remote Sensing of Environment 132: 32-39.
references.citation: Gilmore AM, Yamamoto HY. 1991. Resolution of lutein and zeaxanthin using a non-endcapped, lightly carbon-loaded C-18 high performance liquid chromatographic column. Journal of Chromatography 543: 137-145.
references.citation: Gilmore AM, Yamamoto HY. 1993. Linear models relating xanthophylls and lumen acidity to non-photochemical fluorescence quenching. Evidence that antheraxanthin explains zeaxanthin-independent quenching. Photosynthesis Research 35: 67-78.
references.citation: Grace J, Nichol C, Disney M, Lewis P, Quaife T, Bowyer P. 2007. Can we measure terrestrial photosynthesis from space directly, using spectral reflectance and fluorescence? Global Change Biology 13: 1484-1497.
references.citation: Häckel H. 1999. Strahlung Meteorologie. Stuttgart, Germany: Eugen Ulmer GmbH & Co.
references.citation: Hakala T, Suomalainen J, Kaasalainen S, Chen Y. 2012. Full waveform hyperspectral LiDAR for terrestrial laser scanning. Optics Express 20: 7119.
references.citation: Hall FG, Hilker T, Coops NC. 2011. PHOTOSYNSAT, photosynthesis from space: theoretical foundations of a satellite concept and validation from tower and spaceborne data. Remote Sensing of Environment 115: 1918-1925.
references.citation: Hall FG, Hilker T, Coops NC. 2012. Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: I. Model formulation. Remote Sensing of Environment 121: 301-308.
references.citation: Hall FG, Hilker T, Coops NC, Lyapustin A, Huemmrich KF, Middleton E, Margolis H, Drolet G, Black TA. 2008. Multi-angle remote sensing of forest light use efficiency by observing PRI variation with canopy shadow fraction. Remote Sensing of Environment 112: 3201-3211.
references.citation: Hartel H, Lokstein H, Grimm B, Rank B. 1999. Kinetic studies on the xanthophyll cycle in barley leaves. Plant Physiology 110: 471-482.
references.citation: Hebert M, Krotkov E. 1992. 3D measurements from imaging laser radars: how good are they? Image and Vision Computing 10: 170-178.
references.citation: Hilker T, Coops NC, Coggins SB, Wulder MA, Brown M, Black TA, Nesic Z. 2009. Detection of foliage conditions and disturbance from multi-angular high spectral resolution remote sensing. Remote Sensing of Environment 113: 421-434.
references.citation: Hilker T, Coops NC, Hall FG, Black TA, Wulder MA, Nesic Z, Krishnan P. 2008. Separating physiologically and directionally induced changes in PRI using BRDF models. Remote Sensing of Environment 112: 2777-2788.
references.citation: Hilker T, Coops NC, Hall FG, Nichol CJ, Lyapustin A, Black TA, Wulder MA, Leuning R, Barr A, Hollinger DY et al. 2011. Inferring terrestrial photosynthetic light use efficiency of temperate ecosystems from space. Journal of Geophysical Research 116: G03014.
references.citation: Hilker T, Hall FG, Tucker CJ, Coops NC, Black TA, Nichol CJ, Sellers PJ, Barr A, Hollinger DY, Munger B. 2012. Data assimilation of photosynthetic light-use efficiency using multi-angular satellite data: II Model implementation and validation. Remote Sensing of Environment 121: 287-300.
references.citation: Hilker T, Nesic Z, Coops NC, Lessard D. 2010. A new, automated, multi-angular radiometer instrument for tower-based observation of canopy reflectance (AMSPEC II). Instrumentation Science & Technology 38: 319-340.
references.citation: Hopkinson C, Chasmer L, Young-Pow C, Treitz P. 2004. Assessing forest metrics with a ground-based scanning lidar. Canadian Journal of Forest Research 34: 573-583.
references.citation: Jupp DB, Culvenor DS, Lovell JL, Newnham GJ, Strahler AH, Woodcock CE. 2009. Estimating forest LAI profiles and structural parameters using a ground-based laser called Echidna. Tree Physiology 29: 171-181.
references.citation: Keightley KW, Bawden GW. 2010. 3D volumetric modeling of grapevine biomass using tripod LiDAR. Computers and Electronics in Agriculture 74: 305-312.
references.citation: Kok B. 1956. On the inhibition of photosynthesis by intense light. Biochimica et Biophysica Acta 21: 234-244.
references.citation: Kolber Z, Klimov D, Ananyev G, Rascher U, Berry J, Osmond B. 2005. Measuring photosynthetic parameters at a distance: laser induced fluorescence transient (LIFT) method for remote measurements of photosynthesis in terrestrial vegetation. Photosynthesis Research 84: 121-129.
references.citation: Konishi A, Akira E, Hosoi F, Omasa K. 2009. 3D monitoring spatio-temporal effects of herbicide on a whole plant using combined range and chlorophyll a fluorescence imaging. Functional Plant Biology 36: 874-879.
references.citation: Le Quéré C, Raupach MR, Canadell JG, Marland G, Bopp L, Ciais P, Conway TJ, Doney SC, Feely RA, Foster P et al. 2009. Trends in the sources and sinks of carbon dioxide. Nature Geoscience 2: 831-836.
references.citation: Logan B, Demmig-Adams B, Rosenstiel T, Adams W. 1999. Effect of nitrogen limitation on foliar antioxidants in relationship to other metabolic characteristics. Planta 209: 213-220.
references.citation: Logan BA, Demmig-Adams B, Adams WW III, Grace SC. 1998a. Antioxidation and xanthophyll cycle-dependent energy dissipation in Cucurbita pepo and Vinca major acclimated to four growth irradiances in the field. Journal of Experimental Botany 49: 1869-1879.
references.citation: Logan BA, Grace SC, Adams WW III, Demmig-Adams B. 1998b. Seasonal differences in xanthophyll cycle characteristics and antioxidants in Mahonia repens growing in different light environments. Oecologia 116: 9-17.
references.citation: Lovell JL, Jupp DLB, Culvenor D, Coops NC. 2003. Using airborne and ground based ranging Lidar to measure canopy structure in Australian forests. Canadian Journal of Remote Sensing 29: 607-622.
references.citation: Melis A. 1999. Photosystem II damage and repair cycle in chloroplasts: what modulates the rate of photodamage in vivo? Trends in Plant Science 4: 130-135.
references.citation: Middleton EM, Cheng YB, Hilker T, Black TA, Krishnan P, Coops NC, Huemmrich KF. 2009. Linking foliage spectral responses to canopy-level ecosystem photosynthetic light-use efficiency at a Douglas-fir forest in Canada. Canadian Journal of Remote Sensing 35: 166-188.
references.citation: Moorthy I, Miller JR, Berni JAJ, Zarco-Tejada P, Hu B, Chen J. 2011. Field characterization of olive (Olea europaea L.) tree crown architecture using terrestrial laser scanning data. Agricultural and Forest Meteorology 151: 204-214.
references.citation: Morsdorf F, Nichol C, Malthus T, Woodhouse IH. 2009. Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling. Remote Sensing of Environment 113: 2152-2163.
references.citation: Müller P, Li X, Niyogi KK. 2001. Non-photochemical quenching. A response to excess light energy. Plant Physiology 125: 1558-1566.
references.citation: Nakaji T, Oguma H, Fujinuma Y. 2006. Seasonal changes in the relationship between photochemical reflectance index and photosynthetic light use efficiency of Japanese larch needles. International Journal of Remote Sensing 27: 493-509.
references.citation: Nichol CJ, Pieruschka R, Takayama K, Förster B, Kolber Z, Rascher U, Grace J, Robinson SA, Pogson B, Osmond B. 2012. Canopy conundrums: building on the Biosphere 2 experience to scale measurements of inner and outer canopy photoprotection from the leaf to the landscape. Functional Plant Biology 39: 1-24.
references.citation: Ollinger SV. 2011. Sources of variability in canopy reflectance and the convergent properties of plants. New Phytologist 189: 375-394.
references.citation: Omasa K, Hosoi F, Konishi A. 2007. 3D lidar imaging for detecting and understanding plant responses and canopy structure. Journal of Experimental Botany 58: 881-898.
references.citation: Peguero-Pina JJ, Gil-Pelegrín E, Morales F. 2013. Three pools of zeaxanthin in Quercus coccifera leaves during light transitions with different roles in rapidly reversible photoprotective energy dissipation and photoprotection. Journal of Experimental Botany 64: 1649-1661.
references.citation: Peñuelas J, Filella I, Gamon JA. 1995. Assessment of photosynthetic radiation-use efficiency with spectral reflectance. New Phytologist 131: 291-296.
references.citation: Peñuelas J, Garbulsky MF, Filella I. 2011. Photochemical reflectance index (PRI) and remote sensing of plant CO2 uptake. New Phytologist 191: 596-599.
references.citation: R Development Core Team. 2010. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. http://www.R-project.org
references.citation: Rahimzadeh-Bajgiran P, Munehiro M, Omasa K. 2012. Relationships between the photochemical reflectance index (PRI) and chlorophyll fluorescence parameters and plant pigment indices at different leaf growth stages. Photosynthesis Research 113: 261-271.
references.citation: Richardson AD, Berlyn GP. 2002. Changes in foliar spectral reflectance and chlorophyll fluorescence of four temperate species following branch cutting. Tree Physiology 22: 499-506.
references.citation: Ruban AV, Berera R, Ilioaia C, Van Stokkum IHM, Kennis JTM, Pascal AA, van Amerongen H, Robert B, Horton P, van Grondelle R. 2007. Identification of a mechanism of photoprotective energy dissipation in higher plants. Nature 450: 575-578.
references.citation: Running SW, Nemani RR, Heinsch FA, Zhao M, Reeves M, Hashimoto H. 2004. A continuous satellite-derived measure of global terrestrial primary production. BioScience 54: 547-560.
references.citation: Runyon J, Waring RH, Goward SN, Welles JM. 1994. Environmental limits on net primary production and light-use efficiency across the Oregon Transect. Ecological Applications 4: 226-237.
references.citation: Sanz-Cortiella R, Llorens-Calveras J, Escolà A, Arnó-Satorra J, Ribes-Dasi M, Masip-Vilalta J, Camp F, Gràcia-Aguilá F, Solanelles-Batlle F, Planas-DeMartí S et al. 2011. Innovative LiDAR 3D dynamic measurement system to estimate fruit-tree leaf area. Sensors 11: 5769-5791.
references.citation: Schreiber U, Schliwa U, Bilger W. 1986. Continuous recording of photochemical chlorophyll fluorescence quenching with a new type of modulation fluorometer. Photosynthesis Research 10: 51-62.
references.citation: Schurr U, Walter A, Rascher U. 2006. Functional dynamics of plant growth and photosynthesis - from steady-state to dynamics - from homogeneity to heterogeneity. Plant, Cell & Environment 29: 340-352.
references.citation: Serbin SP, Dillaway DN, Kruger EL, Townsend PA. 2012. Leaf optical properties reflect variation in photosynthetic metabolism and its sensitivity to temperature. Journal of Experimental Botany 63: 289-502.
references.citation: Sims D, Luo H, Hastings S, Oechel W, Rahman A, Gamon J. 2006. Parallel adjustments in vegetation greenness and ecosystem CO2 exchange in response to drought in a Southern California chaparral ecosystem. Remote Sensing of Environment 103: 289-303.
references.citation: Sims DA, Gamon JA. 2002. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment 81: 337-354.
references.citation: Strahler AH, Jupp DB, Woodcock CE, Schaaf CE, Yao T, Zhao F, Yang X, Lovell J, Culvenor D, Newham G et al. 2008. Retrieval of forest structural parameters using a ground-based lidar instrument (Echidna). Canadian Journal of Remote Sensing 34: 426-440.
references.citation: Stylinski C, Gamon J, Oechel W. 2002. Seasonal patterns of reflectance indices, carotenoid pigments and photosynthesis of evergreen chaparral species. Oecologia 131: 366-374.
references.citation: Ustin SL, Gamon JA. 2010. Remote sensing of plant functional types. New Phytologist 186: 795-816.
references.citation: Vierling LA, Xu Y, Eitel JUH, Odlow JS. 2012. Shrub characterization using terrestrial laser scanning and implications for airborne LiDAR assessment. Canadian Journal of Remote Sensing 38: 709-722.
references.citation: Wallace A, Nichol C, Woodhouse I. 2012. Recovery of forest canopy parameters by inversion of multispectral LiDAR data. Remote Sensing 4: 509-531.
references.citation: Watt PJ, Donoghue DNM. 2005. Measuring forest structure with terrestrial laser scanning. International Journal of Remote Sensing 26: 1437-1446.
references.citation: Woodhouse IH, Nichol C, Sinclair P, Jack J, Morsdorf F, Malthus TJ, Patenaude G. 2011. A multispectral canopy LiDAR demonstrator project. IEEE Geoscience and Remote Sensing Letters 8: 839-843.
references.citation: Yamamoto HY. 1979. Biochemistry of the violaxanthin cycle in higher plants. Pure Applied Chemistry 51: 639-648.
references.citation: Zheng G, Moskal M. 2012. Leaf orientation retrieval from terrestrial laser scanning (TLS) data. IEEE Transactions on Geoscience and Remote Sensing 50: 3070-3079.