Effects of woody elements on simulated canopy reflectance: Implications for forest chlorophyll content retrieval

Remote Sensing of Environment

Volumn 114, Issue 3, 2010, Pages 647-656

  Verrelst, Jochem ^a   Schaepman, Michael E ^a,b   Malenovský, Zbyněk ^a,b   Clevers, Jan G P W ^a  

^a WAGENINGEN UNIVERSITY   (Netherlands)

^b UNIVERSITY OF ZURICH   (Switzerland)

Author keywords

Chlorophyll content; Chlorophyll indices; FLIGHT; Non photosynthetic vegetation; Old growth forest; PROSPECT; Radiative transfer

Indexed keywords

BIDIRECTIONAL REFLECTANCE; CANOPY CHLOROPHYLL; CANOPY LEVEL; CANOPY REFLECTANCE; CANOPY STRUCTURE; CHLOROPHYLL CONTENTS; CHLOROPHYLL INDEX; COMPACT HIGH RESOLUTION IMAGING SPECTROMETERS; CONIFEROUS FORESTS; CONTENT OF CHLOROPHYLL; DEAD WOOD; DENSE CANOPY; FOREST CANOPIES; HEALTH STATUS; IMAGING SPECTROSCOPY; LEAF AREA INDEX; LEAF LEVEL; MODELING RESULTS; NON-PHOTOSYNTHETIC VEGETATION; OLD-GROWTH FOREST; OLD-GROWTH STANDS; RADIATIVE TRANSFER MODEL; RADIATIVE TRANSFER MODELING; SCATTERING ELEMENTS; SINGLE WAVELENGTH; SPECTRAL RESPONSE; SPECTRAL VARIATION; STRUCTURAL INFORMATION; SUBMODELS;

CHLOROPHYLL; PORPHYRINS; RADIATIVE TRANSFER; REFLECTION; SENSITIVITY ANALYSIS; VEGETATION;

FORESTRY;

BIDIRECTIONAL REFLECTANCE; BIOINDICATOR; CHLOROPHYLL; DEAD WOOD; DEFOLIATION; FOREST CANOPY; OLD-GROWTH FOREST; PHOTOSYNTHESIS; PHYTOCHEMISTRY; RADIATIVE TRANSFER; SENSITIVITY ANALYSIS; UNDERSTORY;

CHLOROPHYLLS; FORESTRY; PHOTOSYNTHESIS; PLANTS; REFLECTION;

NUCLEOPOLYHEDROVIRUS;

EID: 74149091549     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2009.11.004     Document Type: Article

References (85)

1. Asner G.P. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sensing of Environment 64 (1998) 234-253
2. Asner G.P., Borghi C.E., and Ojeda R.A. Desertification in Central Argentina: Changes in ecosystem carbon and nitrogen from imaging spectroscopy. Ecological Applications 13 (2003) 629-648
3. Barnsley M.J., Settle J.J., Cutter M.A., Lobb D.R., and Teston F. The PROBA/CHRIS mission: A low-cost smallsat for hyperspectral multiangle observations of the earth surface and atmosphere. IEEE Transactions on Geoscience and Remote Sensing 42 (2004) 1512-1520
4. Barton C.V.M., and North P.R.J. Remote sensing of canopy light use efficiency using the photochemical reflectance index: Model and sensitivity analysis. Remote Sensing of Environment 78 (2001) 264-273
5. Belanger M.J., Miller J.R., and Boyer M.G. Comparative relationships between some red edge parameters and seasonal leaf chlorophyll concentrations. Canadian Journal of Remote Sensing 21 (1995) 16-21
6. Blackburn G.A., and Steele C.M. Towards the remote sensing of matorral vegetation physiology: Relationships between spectral reflectance, pigment, and biophysical characteristics of semiarid bushland canopies. Remote Sensing of Environment 70 (1999) 278-292
7. Cacuci, D.G. (2003). Sensitivity and uncertainty analysis: Theory, Volume 1, Chapman & Hall/CRC, Boca Raton
8. Carter G.A., and Knapp A.K. Leaf optical properties in higher plants: Linking spectral characteristics to stress and chlorophyll concentration. American Journal of Botany 88 (2001) 677-684
9. Chen J.M., and Black T.A. Defining leaf area index for non-flat leaves. Plant, Cell & Environment 15 (1992) 421-429
10. Chen J.M., Pavlic G., Brown L., Cihlar J., Leblanc S.G., White H.P., Hall R.J., Peddle D.R., King D.J., Trofymow J.A., Swift E., Van Der Sanden J., and Pellikka P.K.E. Derivation and validation of Canada-wide coarse-resolution leaf area index maps using high-resolution satellite imagery and ground measurements. Remote Sensing of Environment 80 (2002) 165-184
11. Côté J.F., Widlowski J.L., Fournier R.A., and Verstraete M.M. The structural and radiative consistency of three-dimensional tree reconstructions from terrestrial lidar. Remote Sensing of Environment 113 (2009) 1067-1081
12. Datt B. Remote sensing of chlorophyll a, chlorophyll b, chlorophyll a + b, and total carotenoid content in eucalyptus leaves. Remote Sensing of Environment 66 (1998) 111-121
13. Datt B. Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves. International Journal of Remote Sensing 20 (1999) 2741-2759
14. Dawson T.P., Curran P.J., North P.R.J., and Plummer S.E. The propagation of foliar biochemical absorption features in forest canopy reflectance: A theoretical analysis. Remote Sensing of Environment 67 (1999) 147-159
15. Dawson T.P., Curran P.J., and Plummer S.E. LIBERTY - Modeling the effects of leaf biochemical concentration on reflectance spectra. Remote Sensing of Environment 65 (1998) 50-60
16. Demarez V., and Gastellu-Etchegorry J.P. A modeling approach for studying forest chlorophyll content. Remote Sensing of Environment 71 (2000) 226-238
17. Disney M.I., Lewis P., and North P.R.J. Monte Carlo ray tracing in optical canopy reflectance modelling. Remote Sensing Reviews 18 (2000) 163-196
18. Dobbertin M., and Brang P. Crown defoliation improves tree mortality models. Forest Ecology and Management 141 (2001) 271-284
19. Feret J.B., François C., Asner G.P., Gitelson A.A., Martin R.E., Bidel L.P.R., Ustin S.L., le Maire G., and Jacquemoud S. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment 112 (2008) 3030-3043
20. Fernandes R., Fraser R., Latifovic R., Cihlar J., Beaubien J., and Du Y. Approaches to fractional land cover and continuous field mapping: A comparative assessment over the BOREAS study region. Remote Sensing of Environment 89 (2004) 234-251
21. Franklin S.E., Hall R.J., Smith L., and Gerylo G.R. Discrimination of conifer height, age and crown closure classes using Landsat-5 TM imagery in the Canadian Northwest Territories. International Journal of Remote Sensing 24 (2003) 1823-1834
22. Franklin J.F., Spies T.A., Pelt R.V., Carey A.B., Thornburgh D.A., Berg D.R., Lindenmayer D.B., Harmon M.E., Keeton W.S., Shaw D.C., Bible K., and Chen J. Disturbances and structural development of natural forest ecosystems with silvicultural implications, using Douglas-fir forests as an example. Forest Ecology and Management 155 (2002) 399-423
23. Gerard F.F., and North P.R.J. Analyzing the effect of structural variability and canopy gaps on forest BRDF using a geometric-optical model. Remote Sensing of Environment 62 (1997) 46-62
24. Gitelson A.A., Gritz Y., and Merzlyak M.N. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. Journal of Plant Physiology 160 (2003) 271-282
25. Gitelson A., and Merzlyak M.N. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation. Journal of Plant Physiology 143 (1994) 286-292
26. Gitelson A.A., Viña A., Verma S.B., Rundquist D.C., Arkebauer T.J., Keydan G., Leavitt B., Ciganda V., Burba G.G., and Suyker A.E. Relationship between gross primary production and chlorophyll content in crops: Implications for the synoptic monitoring of vegetation productivity. Journal of Geophysical Research D: Atmospheres 111 (2006)
27. Haboudane D., Miller J.R., Tremblay N., Zarco-Tejada P.J., and Dextraze L. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture. Remote Sensing of Environment 81 (2002) 416-426
28. Hapke B. Bidirectional reflectance spectroscopy. 1. Theory. Journal of Geophysical Research 86 (1981) 3039-3054
29. Harris A.T., Asner G.P., and Miller M.E. Changes in vegetation structure after long-term grazing in pinyon-juniper ecosystems: Integrating imaging spectroscopy and field studies. Ecosystems 6 (2003) 368-383
30. Homolová L., Malenovský Z., Hanuš J., Tomášková I., Dvořáková M., and Pokorný R. Comparison of different ground techniques to map leaf area index of Norway spruce forest canopy. In: Schaepman M.E., Liang S., Groot N.E., and Kneubühler M. (Eds). 10th intl. symposium on physical measurements and spectral signatures in remote sensing. Intl. Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. XXXVI (2007) Part 7/C50, pp. 499-504. ISPRS, Davos (CH). ISSN 1682-1777
31. 2 on photosynthesis in Scots pine (Pinus sylvestris). Tree Physiology 20 (2000) 145-157
32. Jacquemoud S., and Baret F. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment 34 (1990) 75-91
33. Jacquemoud S., Bacour C., Poilve H., and Frangi J.P. Comparison of four radiative transfer models to simulate plant canopies reflectance: Direct and inverse mode. Remote Sensing of Environment 74 (2000) 471-481
34. Jacquemoud S., Verhoef W., Baret F., Bacour C., Zarco-Tejada P.J., Asner G.P., François C., and Ustin S.L. PROSPECT + SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment 113 SUPPL. 1 (2009) S56-S166
35. Jia G.J., Burke I.C., Goetz A.F.H., Kaufmann M.R., and Kindel B.C. Assessing spatial patterns of forest fuel using AVIRIS data. Remote Sensing of Environment 102 (2006) 318-327
36. Kane V.R., Gillespie A.R., McGaughey R., Lutz J.A., Ceder K., and Franklin J.F. Interpretation and topographic compensation of conifer canopy self-shadowing. Remote Sensing of Environment 112 (2008) 3820-3832
37. Koetz B., Sun G., Morsdorf F., Ranson K.J., Kneubühler M., Itten K., and Allgöwer B. Fusion of imaging spectrometer and LIDAR data over combined radiative transfer models for forest canopy characterization. Remote Sensing of Environment 106 (2007) 449-459
38. Kokaly R.F., Asner G.P., Ollinger S.V., Martin M.E., and Wessman C.A. Characterizing canopy biochemistry from imaging spectroscopy and its application to ecosystem studies. Remote Sensing of Environment 113 SUPPL. 1 (2009) S78-S91
39. Kötz B., Morsdorf F., Itten K., Schaepman M., Bowyer P., and Allgöwer B. Radiative transfer modeling within a heterogeneous canopy for estimation of forest fire fuel properties. Remote Sensing of Environment 92 (2004) 332-344
40. Le Maire G., François C., and Dufrêne E. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment 89 (2004) 1-28
41. Lichtenthaler H.K., Lang M., Sowinska M., Heisel F., and Miehe J.A. Detection of vegetation stress via a new high resolution fluorescence imaging system. Journal of Plant Physiology 148 (1996) 599-612
42. Lillesand T.M., Kiefer R.W., and Chipman J.W. Remote sensing and image interpretation (2004), Hohn Wiley & Sons
43. Maccioni A., Agati G., and Mazzinghi P. New vegetation indices for remote measurement of chlorophylls based on leaf directional reflectance spectra. Journal of Photochemistry and Photobiology B: Biology 61 (2001) 52-61
44. McMurtrey Iii J.E., Chappelle E.W., Kim M.S., Meisinger J.J., and Corp L.A. Distinguishing nitrogen fertilization levels in field corn (Zea mays L.) with actively induced fluorescence and passive reflectance measurements. Remote Sensing of Environment 47 (1994) 36-44
45. Malenovský Z., Albrechtova J., Lhotákova Z., Zurita-Milla R., Clevers J.G.P.W., Schaepman M.E., and Cudlín P. Applicability of the PROSPECT model for Norway spruce needles. International Journal of Remote Sensing 27 (2006) 5315-5340
46. Malenovsky Z., Martin E., Homolova L., Gastellu-Etchegorry J.P., Zurita-Milla R., Schaepman M.E., Pokorny R., Clevers J.G.P.W., and Cudlin P. Influence of woody elements of a Norway spruce canopy on nadir reflectance simulated by the DART model at very high spatial resolution. Remote Sensing of Environment 112 (2008) 1-18
47. Morsdorf F., Nichol C., Malthus T., and Woodhouse I.H. Assessing forest structural and physiological information content of multi-spectral LiDAR waveforms by radiative transfer modelling. Remote Sensing of Environment 113 (2009) 2152-2163
48. Myneni R.B., Ross J., and Asrar G. A review of the theory of photon transport in leaf canopies. Agricultural & Forest Meteorology 45 (1989) 1-153
49. Nichol C.J., Lloyd J., Shibistova O., Arneth A., Roser C., Knohl A., Matsubara S., and Grace J. Remote sensing of photosynthetic-light-use efficiency of a Siberian boreal forest. Tellus, Series B: Chemical and Physical Meteorology 54 (2002) 677-687
50. Nilson T., and Peterson U. Age dependence of forest reflectance: Analysis of main driving factors. Remote Sensing of Environment 48 (1994) 319-331
51. North P.R.J. Three-dimensional forest light interaction model using a Monte Carlo method. IEEE Transactions on Geoscience and Remote Sensing 34 (1996) 946-956
52. Okin G.S., Roberts D.A., Murray B., and Okin W.J. Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments. Remote Sensing of Environment 77 (2001) 212-225
53. Pearlman J.S., Barry P.S., Segal C.C., Shepanski J., Beiso D., and Carman S.L. Hyperion, a space-based imaging spectrometer. IEEE Transactions on Geoscience and Remote Sensing 41 (2003) 1160-1173
54. Peñuelas J., Baret F., and Filella I. Semi-empirical indices to assess carotenoids/chlorophyll a ratio from leaf spectral reflectance. Photosynthetica 31 (1995) 221-230
55. Radeloff V.C., Mladenoff D.J., and Boyce M.S. Detecting jack pine budworm defoliation using spectral mixture analysis: Separating effects from determinants. Remote Sensing of Environment 69 (1999) 156-169
56. Rautiainen M., Stenberg P., Nilson T., and Kuusk A. The effect of crown shape on the reflectance of coniferous stands. Remote Sensing of Environment 89 (2004) 41-52
57. Risch A.C., Nagel L.M., Schütz M., Krüsi B.O., Kienast F., and Bugmann H. Structure and long-term development of subalpine Pinus montana Miller and Pinus cembra L. forests in the Central European Alps. (Struktur und Langzeitentwicklung von subalpinen Pinus montana Miller und Pinus cembra L. Wäldern in den zentraleuropäischen). Alpen 122 (2003) 219-230
58. Roberts D.A., Smith M.O., and Adams J.B. Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data. Remote Sensing of Environment 44 (1993) 255-269
59. Roberts D.A., Ustin S.L., Ogunjemiyo S., Greenberg J., Bobrowski S.Z., Chen J., and Hinckley T.M. Spectral and structural measures of northwest forest vegetation at leaf to landscape scales. Ecosystems 7 (2004) 545-562
60. Sampson P.H., Zarco-Tejada P.J., Mohammed G.H., Miller J.R., and Noland T.L. Hyperspectral remote sensing of forest condition: Estimating chlorophyll content in tolerant hardwoods. Forest Science 49 (2003) 381-391
61. Sandmeier S., and Deering D.W. Structure analysis and classification of boreal forests using airborne hyperspectral BRDF data from ASAS. Remote Sensing of Environment 69 (1999) 281-295
62. Schaepman M.E., Kötz B., Schaepman-Strub G., Zimmermann N.E., and Itten K.I. Quantitative retrieval of biogeophysical characteristics using imaging spectroscopy - A mountain forest case study. Community Ecology 5 (2004) 93-104
63. Schaepman M.E. Spectrodirectional remote sensing: From pixels to processes. International Journal of Applied Earth Observation and Geoinformation 9 (2007) 204-223
64. Schaepman M.E., Ustin S.L., Plaza A., Painter T., Verrelst J., and Liang S. Earth system science related imaging spectroscopy - An assessment. Remote Sensing of Environment. 113 SUPPL. 1 (2009) S123-S137
65. Schaepman-Strub G., Schaepman M.E., Painter T.H., Dangel S., and Martonchik J.V. Reflectance quantities in optical remote sensing-Definitions and case studies. Remote Sensing of Environment 103 (2006) 27-42
66. Siitonen J. Forest management, coarse woody debris and saproxylic organisms: Fennoscandian boreal forests as an example. Ecological Bulletins 49 (2001) 11-41
67. Sims D.A., and Gamon J.A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages. Remote Sensing of Environment 81 (2002) 337-354
68. Smith R.C., Adams J., Stephens D.J., and Hick P.T. Forecasting wheat yield in a Mediterranean-type environment from the NOAA satellite. Australian Journal of Agricultural Research 46 (1995) 113-125
69. Snedecor G.W., and Cochran W.G. Statistical methods. 7th edition (1980), Iowa State University Press, Iowa
70. Song C., Schroeder T.A., and Cohen W.B. Predicting temperate conifer forest successional stage distributions with multitemporal Landsat Thematic Mapper imagery. Remote Sensing of Environment 106 (2007) 228-237
71. Song C., and Woodcock C.E. The spatial manifestation of forest succession in optical imagery: The potential of multiresolution imagery. Remote Sensing of Environment 82 (2002) 271-284
72. Suárez L., Zarco-Tejada P.J., Sepulcre-Canto G., Pérez-Priego O., Miller J.R., Jiménez-Muñoz J.C., and Sobrino J. Assessing canopy PRI for water stress detection with diurnal airborne imagery. Remote Sensing of Environment 112 (2008) 560-575
73. Trotter G.M., Whitehead D., and Pinkney E.J. The photochemical reflectance index as a measure of photosynthetic light use of efficiency for plants with varying foliar nitrogen contents. International Journal of Remote Sensing 23 (2002) 1207-1212
74. Ustin S.L., Gitelson A.A., Jacquemoud S., Schaepman M.E., Asner G., Gamon J.A., and Zarco-Tejada P. Retrieval of foliar information about plant pigment systems from high resolution spectroscopy. Remote Sensing of Environment. 113 suppl. 1 (2009) S67-S77
75. Ustin S.L., Roberts D.A., Gamon J.A., Asner G.P., and Green R.O. Using imaging spectroscopy to study ecosystem processes and properties. BioScience 54 (2004) 523-534
76. Verrelst J., Schaepman M.E., Koetz B., and Kneubühler M. Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data. Remote Sensing of Environment 112 (2008) 2341-2353
77. White J.C., Wulder M.A., Brooks D., Reich R., and Wheate R.D. Detection of red attack stage mountain pine beetle infestation with high spatial resolution satellite imagery. Remote Sensing of Environment 96 (2005) 340-351
78. Widlowski J.L., Taberner M., Pinty B., Bruniquel-Pinel V., Disney M., Fernandes R., Gastellu-Etchegorry J.P., Gobron N., Kuusk A., Lavergne T., Leblanc S., Lewis P.E., Martin E., Mõttus M., North P.R.J., Qin W., Robustelli M., Rochdi N., Ruiloba R., Soler C., Thompson R., Verhoef W., Verstraete M.M., and Xie D. Third Radiation Transfer Model Intercomparison (RAMI) exercise: Documenting progress in canopy reflectance models. Journal of Geophysical Research D: Atmospheres 112 (2007)
79. Xue L., and Yang L. Deriving leaf chlorophyll content of green-leafy vegetables from hyperspectral reflectance. ISPRS Journal of Photogrammetry and Remote Sensing 64 (2009) 97-106
80. Zarco-Tejada P.J., Miller J.R., Mohammed G.H., and Noland T.L. Chlorophyll fluorescence effects on vegetation apparent reflectance: I. Leaf-level measurements and model simulation. Remote Sensing of Environment 74 (2000) 582-595
81. Zarco-Tejada P.J., Miller J.R., Mohammed G.H., Noland T.L., and Sampson P.H. Vegetation stress detection through chlorophyll a + b estimation and fluorescence effects on hyperspectral imagery. Journal of Environmental Quality 31 (2002) 1433-1441
82. Zarco-Tejada P.J., Miller J.R., Morales A., Berjón A., and Agüera J. Hyperspectral indices and model simulation for chlorophyll estimation in open-canopy tree crops. Remote Sensing of Environment 90 (2004) 463-476
83. Zarco-Tejada P.J., Miller J.R., Noland T.L., Mohammed G.H., and Sampson P.H. Scaling-up and model inversion methods with narrowband optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data. IEEE Transactions on Geoscience and Remote Sensing 39 (2001) 1491-1507
84. Zhang Y., Chen J.M., Miller J.R., and Noland T.L. Leaf chlorophyll content retrieval from airborne hyperspectral remote sensing imagery. Remote Sensing of Environment 112 (2008) 3234-3247
85. Zoller H. Vegetationskarte des Schweizerischen Nationalparks. Erläuterungen (1995), National Park Forschnung, Zernetz, Switzerland 108