Joint leaf chlorophyll content and leaf area index retrieval from Landsat data using a regularized model inversion system (REGFLEC)

Remote Sensing of Environment

Volumn 159, Issue , 2015, Pages 203-221

  Houborg, Rasmus ^a   McCabe, Matthew ^a   Cescatti, Alessandro ^b   Gao, Feng ^c   Schull, Mitchell ^c   Gitelson, Anatoly ^d  

^a KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

^b JOINT RESEARCH CENTRE   (Italy)

^c AGRICULTURAL RESEARCH SERVICE   (United States)

^d UNIVERSITY OF NEBRASKA LINCOLN   (United States)

Author keywords

Canopy reflectance; LAI; Landsat; Leaf chlorophyll; Model inversion; PROSPECT; SAIL

Indexed keywords

CHLOROPHYLL; OPTICAL PROPERTIES; REFLECTION; REMOTE SENSING; TIME SERIES ANALYSIS;

CANOPY REFLECTANCE; LAI; LANDSAT; LEAF CHLOROPHYLL; MODEL INVERSION; PROSPECT; SAIL;

SEARCH ENGINES;

BIOCHEMICAL COMPOSITION; BIOSPHERE; CANOPY REFLECTANCE; CHLOROPHYLL; DATA SET; ENERGY FLOW; ENERGY RESOURCE; FOLIAGE; LANDSAT; LEAF AREA INDEX; PHOTOSYNTHESIS; REMOTE SENSING; SPATIOTEMPORAL ANALYSIS;

NEBRASKA; UNITED STATES;

GLYCINE MAX; ZEA MAYS;

EID: 84923830705     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2014.12.008     Document Type: Article

References (129)

1. Asner G.P. Biophysical and biochemical sources of variability in canopy reflectance. Remote Sensing of Environment 1998, 64:234-253. 10.1016/S0034-4257(98)00014-5.
2. Atzberger C. Object-based retrieval of biophysical canopy variables using artificial neural nets and radiative transfer models. Remote Sensing of Environment 2004, 93:53-67. 10.1016/j.rse.2004.06.016.
3. Atzberger C., Richter K. Spatially constrained inversion of radiative transfer models for improved LAI mapping from future Sentinel-2 imagery. Remote Sensing of Environment 2012, 120:208-218. 10.1016/j.rse.2011.10.035.
4. Bacour C., Baret F., Béal D., Weiss M., Pavageau K. Neural network estimation of LAI, fAPAR, fCover and LAI×Cab, from top of canopy MERIS reflectance data: Principles and validation. Remote Sensing of Environment 2006, 105:313-325. 10.1016/j.rse.2006.07.014.
5. Bacour C., Jacquemoud S., Leroy M., Hautecœur O., Weiss M., Prévot L., et al. Reliability of the estimation of vegetation characteristics by inversion of three canopy reflectance models on airborne POLDER data. Agronomie 2002, 22:555-565.
6. Baret F. Vegetation canopy reflectance: Factors of variation and application for agriculture. Physical measurements and signatures in remote sensing 1991, 145-167. Courchevel, France. D. Hunt (Ed.).
7. Baret F., Buis S. Estimating canopy characteristics from remote sensing observations: Review of methods and associated problems. Advances in land remote sensing: System, modeling, inversion and application 2008, 173-201. Springer Verlag.
8. Baret F., Fourty T. Estimation du contenu en eau et de la masse seche surfacique des feuilles a partir de spectres de reflectance et de transmittance. Agronomie 1997, 17:455-464.
9. Baret F., Hagolle O., Geiger B., Bicheron P., Miras B., Huc M., et al. LAI, fAPAR and fCover CYCLOPES global products derived from VEGETATION. Remote Sensing of Environment 2007, 110:275-286. 10.1016/j.rse.2007.02.018.
10. Baret F., Weiss M., Lacaze R., Camacho F., Makhmara H., Pacholcyzk P., et al. GEOV1: LAI and FAPAR essential climate variables and FCOVER global time series capitalizing over existing products. Part1: Principles of development and production. Remote Sensing of Environment 2013, 137:299-309. 10.1016/j.rse.2012.12.027.
11. Blackburn G.A. Hyperspectral remote sensing of plant pigments. Journal of Experimental Botany 2007, 58:855-867. 10.1093/jxb/erl123.
12. Bonan G.B., Lawrence P.J., Oleson K.W., Levis S., Jung M., Reichstein M., et al. Improving canopy processes in the Community Land Model version 4 (CLM4) using global flux fields empirically inferred from FLUXNET data. Journal of Geophysical Research 2011, 116:1-22. 10.1029/2010JG001593.
13. Botha E.J., Leblon B., Zebarth B., Watmough J. Non-destructive estimation of potato leaf chlorophyll from canopy hyperspectral reflectance using the inverted PROSAIL model. International Journal of Applied Earth Observation and Geoinformation 2007, 9:360-374. 10.1016/j.jag.2006.11.003.
14. Botha E.J., Leblon B., Zebarth B.J., Watmough J. Non-destructive estimation of wheat leaf chlorophyll content from hyperspectral measurements through analytical model inversion. International Journal of Remote Sensing 2010, 31:1679-1697. 10.1080/01431160902926574.
15. Campbell G.S. Extinction coefficients for radiation in plant canopies calculated using an ellipsoidal inclination angle distribution. Agricultural and Forest Meteorology 1986, 36:317-321.
16. Chen J.M., Cihlar J. Retrieving leaf area index of boreal conifer forests using landsat TM images. Remote Sensing of Environment 1996, 55:153-162.
17. Ciganda V., Gitelson A., Schepers J. Vertical profile and temporal variation of chlorophyll in maize canopy: Quantitative "crop vigor" indicator by means of reflectance-based techniques. Agronomy Journal 2008, 100:1409-1417. 10.2134/agronj2007.0322.
18. Ciganda V., Gitelson A., Schepers J. Non-destructive determination of maize leaf and canopy chlorophyll content. Journal of Plant Physiology 2009, 166:157-167. 10.1016/j.jplph.2008.03.004.
19. Ciganda V.S., Gitelson A.A., Schepers J. How deep does a remote sensor sense? Expression of chlorophyll content in a maize canopy. Remote Sensing of Environment 2012, 126:240-247. 10.1016/j.rse.2012.08.019.
20. Clevers J.G.P.W., Gitelson A.A. Remote estimation of crop and grass chlorophyll and nitrogen content using red-edge bands on Sentinel-2 and -3. International Journal of Applied Earth Observation and Geoinformation 2013, 23:344-351. 10.1016/j.jag.2012.10.008.
21. Clevers J.G.P.W., Kooistra L. Using hyperspectral remote sensing data for retrieving canopy chlorophyll and nitrogen content. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 2012, 5:574-583. 10.1109/JSTARS.2011.2176468.
22. Comar A., Baret F., Obein G., Simonot L., Meneveaux D., Viénot F., et al. ACT: A leaf BRDF model taking into account the azimuthal anisotropy of monocotyledonous leaf surface. Remote Sensing of Environment 2014, 143:112-121. 10.1016/j.rse.2013.12.006.
23. Combal B., Baret F., Weiss M., Trubuil A. Retrieval of canopy biophysical variables from bidirectional reflectance: Using prior information to solve the ill-posed inverse problem. Remote Sensing of Environment 2002, 84:1-15.
24. Darvishzadeh R., Skidmore A., Schlerf M., Atzberger C. Inversion of a radiative transfer model for estimating vegetation LAI and chlorophyll in a heterogeneous grassland. Remote Sensing of Environment 2008, 112:2592-2604. 10.1016/j.rse.2007.12.003.
25. Dash J., Curran P.J. Evaluation of the MERIS terrestrial chlorophyll index (MTCI). Advances in Space Research 2007, 39:100-104. 10.1016/j.asr.2006.02.034.
26. Daughtry C.S.T., Walthall C.L., Kim M.S., Colstoun E.B.De Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance. Remote Sensing of Environment 2000, 229-239.
27. Delegido J., Alonso L., González G., Moreno J. Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC). International Journal of Applied Earth Observation and Geoinformation 2010, 12:165-174. 10.1016/j.jag.2010.02.003.
28. Delegido J., Vergara C., Verrelst J., Gandía S., Moreno J. Remote estimation of crop chlorophyll content by means of high-spectral-resolution reflectance techniques. Agronomy Journal 2011, 103:1834. 10.2134/agronj2011.0101.
29. Demarez V., Duthoit S., Baret F., Weiss M., Dedieu G. Estimation of leaf area and clumping indexes of crops with hemispherical photographs. Agricultural and Forest Meteorology 2008, 148:644-655. 10.1016/j.agrformet.2007.11.015.
30. Dorigo W., Richter R., Baret F., Bamler R., Wagner W. Enhanced automated canopy characterization from hyperspectral data by a novel two step radiative transfer model inversion approach. Remote Sensing 2009, 1:1139-1170. 10.3390/rs1041139.
31. Dorigo W.A., Zurita-Milla R., de Wit A.J.W., Brazile J., Singh R., Schaepman M.E. A review on reflective remote sensing and data assimilation techniques for enhanced agroecosystem modeling. International Journal of Applied Earth Observation and Geoinformation 2007, 9:165-193. 10.1016/j.jag.2006.05.003.
32. Duthoit S., Demarez V., Gastellu-Etchegorry J.-P., Martin E., Roujean J.-L. Assessing the effects of the clumping phenomenon on BRDF of a maize crop based on 3D numerical scenes using DART model. Agricultural and Forest Meteorology 2008, 148:1341-1352. 10.1016/j.agrformet.2008.03.011.
33. Ershadi A., McCabe M.F., Evans J.P., Mariethoz G., Kavetski D. A Bayesian analysis of sensible heat flux estimation: Quantifying uncertainty in meteorological forcing to improve model prediction. Water Resources Research 2013, 49:2343-2358. 10.1002/wrcr.20231.
34. España M., Baret F., Chelle M., Aries F., Andrieu B. A dynamic model of maize 3D architecture: Application to the parameterisation of the clumpiness of the canopy. Agronomie 1998, 18:609-626.
35. Evans J. Photosynthesis and nitrogen relationships in leaves of C3 plants. Oecologia 1989, 78:9-19.
36. Fensholt R., Sandholt I., Stisen S. Evaluating MODIS, MERIS, and VEGETATION vegetation indices using in situ measurements in a semiarid environment. IEEE Transactions on Geoscience and Remote Sensing 2006, 44:1774-1786. 10.1109/TGRS.2006.875940.
37. Feret J.-B., François C., Asner G.P., Gitelson A.A., Martin R.E., Bidel L.P.R., et al. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments. Remote Sensing of Environment 2008, 112:3030-3043. 10.1016/j.rse.2008.02.012.
38. Feret J.-B., François C., Gitelson A., Asner G.P., Barry K.M., Panigada C., et al. Optimizing spectral indices and chemometric analysis of leaf chemical properties using radiative transfer modeling. Remote Sensing of Environment 2011, 115:2742-2750. 10.1016/j.rse.2011.06.016.
39. Ganguly S., Nemani R.R., Zhang G., Hashimoto H., Milesi C., Michaelis A., et al. Generating global Leaf Area Index from Landsat: Algorithm formulation and demonstration. Remote Sensing of Environment 2012, 122:185-202. 10.1016/j.rse.2011.10.032.
40. Gao F., Anderson M.C., Kustas W.P., Houborg R. Retrieving Leaf Area Index from Landsat using MODIS LAI products and field measurements. IEEE Geoscience and Remote Sensing Letters 2014, 11:773-777. 10.1109/LGRS.2013.2278782.
41. Gao F., Anderson M.C., Kustas W.P., Wang Y. Simple method for retrieving leaf area index from Landsat using MODIS leaf area index products as reference. Journal of Applied Remote Sensing 2012, 6:63515-63554. 10.1117/1.JRS.6.063554.
42. Gao F., Masek J., Schwaller M., Hall F. On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance. IEEE Transactions on Geoscience and Remote Sensing 2006, 44:2207-2218. 10.1109/TGRS.2006.872081.
43. Garrigues S., Lacaze R., Baret F., Morisette J.T., Weiss M., Nickeson J.E., et al. Validation and intercomparison of global Leaf Area Index products derived from remote sensing data. Journal of Geophysical Research 2008, 113. 10.1029/2007JG000635.
44. Gastellu-Etchegorry J. Modeling radiative transfer in heterogeneous 3-D vegetation canopies. Remote Sensing of Environment 1996, 58:131-156. 10.1016/0034-4257(95)00253-7.
45. Gitelson A.A., Gritz Y., 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 2003, 160:271-282. 10.1078/0176-1617-00887.
46. Gitelson A.A., Keydan G.P., Merzlyak M.N. Three-band model for noninvasive estimation of chlorophyll, carotenoids, and anthocyanin contents in higher plant leaves. Geophysical Research Letters 2006, 33:L11402. 10.1029/2006GL026457.
47. Gitelson A.A., Peng Y., Arkebauer T.J., Schepers J. Relationships between gross primary production, green LAI, and canopy chlorophyll content in maize: Implications for remote sensing of primary production. Remote Sensing of Environment 2014, 144:65-72. 10.1016/j.rse.2014.01.004.
48. Gitelson A.a., Peng Y., Masek J.G., Rundquist D.C., Verma S., Suyker A., et al. Remote estimation of crop gross primary production with Landsat data. Remote Sensing of Environment 2012, 121:404-414. 10.1016/j.rse.2012.02.017.
49. Gitelson A.A., Vina A., Arkebauer T.J., Rundquist D.C., Keydan G., Leavitt B. Remote estimation of leaf area index and green leaf biomass in maize canopies. Geophysical Research Letters 2003, 30:1248. 10.1029/2002GL016450.
50. Gitelson A.A., Vina A., Ciganda V., Rundquist D.C., Arkebauer T.J. Remote estimation of canopy chlorophyll content in crops. Geophysical Research Letters 2005, 32:L08403. 10.1029/2005GL022688.
51. Gitelson A.A., Wardlow B.D., Keydan G.P., Leavitt B. An evaluation of MODIS 250-m data for green LAI estimation in crops. Geophysical Research Letters 2007, 34:L20403. 10.1029/2007GL031620.
52. Gobron N., Pinty B., Verstraete M.M. Theoretical limits to the estimation of the leaf area index on the basis of visible and near-infrared remote sensing data. IEEE Transactions on Geoscience and Remote Sensing 1997, 35:1438-1445. 10.1109/36.649798.
53. Gobron N., Pinty B., Verstraete M.M., Govaerts Y. A semidiscrete model for the scattering of light by vegetation. Journal of Geophysical Research, D: Atmospheres 1997, 102:9431-9446.
54. Goel N. Models of vegetation canopy reflectance and their use in estimation of biophysical parameters from reflectance data. Remote Sensing Reviews 1988, 4:1-212.
55. Gray J., Song C. Mapping leaf area index using spatial, spectral, and temporal information from multiple sensors. Remote Sensing of Environment 2012, 119:173-183. 10.1016/j.rse.2011.12.016.
56. Groenendijk M., Dolman a.J., van der Molen M.K., Leuning R., Arneth a., Delpierre N., et al. Assessing parameter variability in a photosynthesis model within and between plant functional types using global Fluxnet eddy covariance data. Agricultural and Forest Meteorology 2011, 151:22-38. 10.1016/j.agrformet.2010.08.013.
57. Guindin-Garcia N., Gitelson A.A., Arkebauer T.J., Shanahan J., Weiss A. An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index. Agricultural and Forest Meteorology 2012, 161:15-25. 10.1016/j.agrformet.2012.03.012.
58. Haboudane D., Miller J.R., Pattey E., Zarco-Tejada P.J., Strachan I.B. Hyperspectral vegetation indices and novel algorithms forpredicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture. Remote Sensing of Environment 2004, 90(3):337-352. 10.1016/j.rse.2003.12.013.
59. Han W., Yang Z., Di L., Mueller R. CropScape: A Web service based application for exploring and disseminating US conterminous geospatial cropland data products for decision support. Computers and Electronics in Agriculture 2012, 84:111-123. 10.1016/j.compag.2012.03.005.
60. Holben B., Eck T., Slutsker I., Tanre D., Buis J., Setzer A., et al. AERONET - A federated instrument network and data archive for aerosol characterization. Remote Sensing of Environment 1998, 66:1-16.
61. Hosgood B., Jacquemoud S., Andreoli G., Verdebout J., Pedrini G., Schmuck G. Leaf Optical Properties Experiment 93 (LOPEX93) 1995.
62. Houborg R., Anderson M.C. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales. Journal of Applied Remote Sensing 2009, 3:033529. 10.1117/1.3141522.
63. Houborg R., Anderson M., Daughtry C. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale. Remote Sensing of Environment 2009, 113:259-274. 10.1016/j.rse.2008.09.014.
64. Houborg R., Boegh E. Mapping leaf chlorophyll and leaf area index using inverse and forward canopy reflectance modeling and SPOT reflectance data. Remote Sensing of Environment 2008, 112:186-202. 10.1016/j.rse.2007.04.012.
65. Houborg R., Cescatti A., Migliavacca M., Kustas W.P. Agricultural and Forest Meteorology Satellite retrievals of leaf chlorophyll and photosynthetic capacity for improved modeling of GPP[U+0B1D]. Agricultural and Forest Meteorology 2013, 177:10-23. 10.1016/j.agrformet.2013.04.006.
66. Houborg R., Soegaard H., Boegh E. Combining vegetation index and model inversion methods for the extraction of key vegetation biophysical parameters using Terra and Aqua MODIS reflectance data. Remote Sensing of Environment 2007, 106:39-58. 10.1016/j.rse.2006.07.016.
67. Huemmrich K.F. Simulations of seasonal and latitudinal variations in leaf inclination angle distribution[U+202F]: Implications for remote sensing 2013 2013, 93-101.
68. Huete A., Didan K., Miura T., Rodriguez E.P., Gao X., Ferreira L.G. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment 2002, 83:195-213.
69. Hunt E.R., Daughtry C.S.T., Eitel J.U.H., Long D.S. Remote sensing leaf chlorophyll content using a visible band index. Agronomy Journal 2011, 103:1090-1099. 10.2134/agronj2010.0395.
70. Jacquemoud S., Bacour C., Poilve H., Frangi J.-P. Comparison of four radiative transfer models to simulate plant canopies reflectance direct and inverse mode. Remote Sensing of Environment 2000, 74:471-481. 10.1016/S0034-4257(00)00139-5.
71. Jacquemoud S., Baret F. PROSPECT: A model of leaf optical properties spectra. Remote Sensing of Environment 1990, 34:75-91. 10.1016/0034-4257(90)90100-Z.
72. Jacquemoud S., Baret F., Andrieu B., Danson F.M., Jaggard K. Extraction of vegetation biophysical parameters by inversion of the PROSPECT+SAIL models on sugar beet canopy reflectance data. Application to TM and AVIRIS sensors. Remote Sensing of Environment 1995, 52:163-172. 10.1016/0034-4257(95)00018-V.
73. Jacquemoud S., Verhoef W., Baret F., Bacour C., Zarco-Tejada P.J., Asner G.P., et al. PROSPECT+SAIL models: A review of use for vegetation characterization. Remote Sensing of Environment 2009, 113:S56-S66. 10.1016/j.rse.2008.01.026.
74. Jiang Z., Huete A., Didan K., Miura T. Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment 2008, 112:3833-3845. 10.1016/j.rse.2008.06.006.
75. Jung M., Vetter M., Herold M., Churkina G., Reichstein M., Zaehle S., et al. Uncertainties of modeling gross primary productivity over Europe: A systematic study on the effects of using different drivers and terrestrial biosphere models. Global Biogeochemical Cycles 2007, 21:1-12. 10.1029/2006GB002915.
76. Kalfas J.L., Xiao X., Vanegas D.X., Verma S.B., Suyker A.E. Modeling gross primary production of irrigated and rain-fed maize using MODIS imagery and CO2 flux tower data. Agricultural and Forest Meteorology 2011, 151:1514-1528. 10.1016/j.agrformet.2011.06.007.
77. Kalma J.D., McVicar T.R., McCabe M.F. Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surveys in Geophysics 2008, 29:421-469. 10.1007/s10712-008-9037-z.
78. 2 into a terrestrial vegetation model and interactive mission benefit analysis. Biogeosciences 2012, 9:3173-3184. 10.5194/bg-9-3173-2012.
79. Kattge J., Díaz S., Lavorel S., Prentice I.C., Leadley P., Bönisch G., et al. TRY - a global database of plant traits. Global Change Biology 2011, 17:2905-2935. 10.1111/j.1365-2486.2011.02451.x.
80. Kattge J., Knorr W., Raddatz T., Wirth C. Quantifying photosynthetic capacity and its relationship to leaf nitrogen content for global-scale terrestrial biosphere models. Global Change Biology 2009, 15:976-991. 10.1111/j.1365-2486.2008.01744.x.
81. Knorr W., Heimann M. Uncertainties in global terrestrial biosphere modeling: 1. A comprehensive sensitivity analysis with a new photosynthesis and energy balance scheme. Global Biogeochemical Cycles 2001, 15:207-225. 10.1029/1998GB001059.
82. Knyazikhin Y., Martonchik J.V., Myneni R.B., Diner D.J., Running S.W. Synergistic algorithm for estimating vegetation canopy leaf area index and fraction of absorbed photosynthetically active radiation from MODIS and MISR data. Journal of Geophysical Research, D: Atmospheres 1998, 103:32257-32275.
83. Koetz B., Baret F., Poilvé H., Hill J. Use of coupled canopy structure dynamic and radiative transfer models to estimate biophysical canopy characteristics. Remote Sensing of Environment 2005, 95:115-124. 10.1016/j.rse.2004.11.017.
84. Kotchenova S.Y., Vermote E.F., Matarrese R., Klemm F.J. Validation of a vector version of the 6S radiative transfer code for atmospheric correction of satellite data. Part I: path radiance. Applied Optics 2006, 45:6762-6774.
85. Kuusk A. The hot spot effect in the leaf canopy. Digest - International Geoscience and Remote Sensing Symposium (IGARSS) 1991, 1555-1557. Publ by IEEE.
86. Kuusk A. A two-layer canopy reflectance model. Journal of Quantitative Spectroscopy and Radiation Transfer 2001, 71:1-9.
87. Lauvernet C., Baret F., Hascoët L., Buis S., Le Dimet F.-X. Multitemporal-patch ensemble inversion of coupled surface-atmosphere radiative transfer models for land surface characterization. Remote Sensing of Environment 2008, 112:851-861. 10.1016/j.rse.2007.06.027.
88. Le Maire G., François C., Dufrêne E. Towards universal broad leaf chlorophyll indices using PROSPECT simulated database and hyperspectral reflectance measurements. Remote Sensing of Environment 2004, 89:1-28. 10.1016/j.rse.2003.09.004.
89. Lewis P., Disney M. Spectral invariants and scattering across multiple scales from within-leaf to canopy. Remote Sensing of Environment 2007, 109:196-206. 10.1016/j.rse.2006.12.015.
90. López-Lozano R., Baret F., Chelle M., Rochdi N., España M. Sensitivity of gap fraction to maize architectural characteristics based on 4D model simulations. Agricultural and Forest Meteorology 2007, 143:217-229. 10.1016/j.agrformet.2006.12.005.
91. Malenovský Z., Homolová L., Zurita-Milla R., Lukeš P., Kaplan V., Hanuš J., et al. Retrieval of spruce leaf chlorophyll content from airborne image data using continuum removal and radiative transfer. Remote Sensing of Environment 2013, 131:85-102. 10.1016/j.rse.2012.12.015.
92. Masek J.G., Vermote E.F., Saleous N.E., Wolfe R., Hall F.G., Huemmrich K.F., et al. A Landsat surface reflectance dataset. Terra 2006, 3:68-72.
93. Maxwell S.K., Schmidt G.L., Storey J.C. A multi-scale segmentation approach to filling gaps in Landsat ETM+ SLC-off images. International Journal of Remote Sensing 2007, 28:5339-5356. 10.1080/01431160601034902.
94. McCabe M.F., Kalma J.D., Franks S.W. Spatial and temporal patterns of land surface fluxes from remotely sensed surface temperatures within an uncertainty modelling framework. Hydrology and Earth System Sciences 2005, 9:467-480.
95. Medvigy D., Wofsy S.C., Munger J.W., Hollinger D.Y., Moorcroft P.R. Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2. Journal of Geophysical Research 2009, 114:G01002. 10.1029/2008JG000812.
96. Myneni R., Hoffman S., Knyazikhin Y., Privette J., Glassy J., Tian Y., et al. Global products of vegetation leaf area and fraction absorbed PAR from year one of MODIS data. Remote Sensing of Environment 2002, 83:214-231. 10.1016/S0034-4257(02)00074-3.
97. Pinty B., Jung M., Kaminski T., Lavergne T., Mund M., Plummer S., et al. Evaluation of the JRC-TIP 0.01° products over a mid-latitude deciduous forest site. Remote Sensing of Environment 2011, 115:3567-3581. 10.1016/j.rse.2011.08.018.
98. Pisek J., Ryu Y., Sprintsin M., He L., Oliphant A.J., Korhonen L., et al. Retrieving vegetation clumping index from Multi-angle Imaging SpectroRadiometer (MISR) data at 275m resolution. Remote Sensing of Environment 2013, 138:126-133. 10.1016/j.rse.2013.07.014.
99. Price J.C. On the information content of soil reflectance spectra. Remote Sensing of Environment 1990, 33:113-121.
100. Proud S.R., Rasmussen M.O., Fensholt R., Sandholt I., Shisanya C., Mutero W., et al. Improving the SMAC atmospheric correction code by analysis of Meteosat Second Generation NDVI and surface reflectance data. Remote Sensing of Environment 2010, 114(8):1687-1698. 10.1016/j.rse.2010.02.020.
101. Richter K., Atzberger C., Vuolo F., Weihs P., D'Urso G. Experimental assessment of the Sentinel-2 band setting for RTM-based LAI retrieval of sugar beet and maize. Canadian Journal of Remote Sensing 2009, 35:230-247.
102. Rivera J., Verrelst J., Leonenko G., Moreno J. Multiple cost functions and regularization options for improved retrieval of leaf chlorophyll content and LAI through inversion of the PROSAIL model. Remote Sensing 2013, 5:3280-3304. 10.3390/rs5073280.
103. Ross J. The radiation regime and architecture of plant stands 1981, Springer. 10.1007/978-94-009-8647-3.
104. Rouse J.W., Haas R.H., Schell J.A., Deering D.W. Monitoring vegetation systems in the Great Plains with ERTS, Third ERTS Symposium. NASA SP-351 I 1974, 309-317.
105. Sage R.F., Pearcy R.W., Seeman J.R. The nitrogen Use efficiency of C3 and C4 plants. Plant Physiology 1987, 85:355-359.
106. Schlemmer M., Gitelson A., Schepers J., Ferguson R., Peng Y., Shanahan J., et al. Remote estimation of nitrogen and chlorophyll contents in maize at leaf and canopy levels. International Journal of Applied Earth Observation and Geoinformation 2013, 25:47-54. 10.1016/j.jag.2013.04.003.
107. Schlerf M., Atzberger C. Inversion of a forest reflectance model to estimate structural canopy variables from hyperspectral remote sensing data. Remote Sensing of Environment 2006, 100:281-294. 10.1016/j.rse.2005.10.006.
108. Sellers P., Randall D., Collatz G., Berry J., Field C., Dazlich D., et al. A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: Model Formulation. Journal of Climate 1996, 9:676-705.
109. Sims D.A., 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 2002, 81:337-354. 10.1016/S0034-4257(02)00010-X.
110. Singh S.K., Hoyos-Villegas V., Ray J.D., Smith J.R., Fritschi F.B. Quantification of leaf pigments in soybean (Glycine max (L.) Merr.) based on wavelet decomposition of hyperspectral features. Field Crops Research 2013, 149:20-32. 10.1016/j.fcr.2013.04.019.
111. Tou J.T., Gonzalez R.C. Pattern recognition principles 1974, Addison-Wesley, Reading, Massachusetts.
112. Vanderbilt V.C., Grant L., Daughtry C.S.T. Polarization of light scattered by vegetation. Proceedings of the IEEE 1985, 73:1012-1024. 10.1109/PROC.1985.13232.
113. Verhoef W. Light scattering by leaf layers with application to canopy reflectance modeling: The SAIL model. Remote Sensing of Environment 1984, 16:125-141.
114. Verhoef W. Earth observation modeling based on layer scattering matrices. Remote Sensing of Environment 1985, 17:165-178.
115. Verhoef W., Bach H. Simulation of hyperspectral and directional radiance images using coupled biophysical and atmospheric radiative transfer models. Remote Sensing of Environment 2003, 87(1):23-41. 10.1016/S0034-4257(03)00143-3.
116. Verhoef W., Bach H. Coupled soil-leaf-canopy and atmosphere radiative transfer modeling to simulate hyperspectral multi-angular surface reflectance and TOA radiance data. Remote Sensing of Environment 2007, 109:166-182. 10.1016/j.rse.2006.12.013.
117. Verhoef W., Jia L., Xiao Q., Su Z. Unified optical-thermal four-stream radiative transfer theory for homogeneous vegetation canopies. IEEE Transactions on Geoscience and Remote Sensing 2007, 45:1808-1822. 10.1109/TGRS.2007.895844.
118. Verma S.B., Dobermann A., Cassman K.G., Walters D.T., Knops J.M., Arkebauer T.J., et al. Annual carbon dioxide exchange in irrigated and rainfed maize-based agroecosystems. Agricultural and Forest Meteorology 2005, 131:77-96. 10.1016/j.agrformet.2005.05.003.
119. Vermote E.F., Tanre D., Deuze J.L., Herman M., Morcette J.-J. Second simulation of the satellite signal in the solar spectrum, 6S: An overview. IEEE Transactions on Geoscience and Remote Sensing 1997, 35:675-686. 10.1109/36.581987.
120. Viña A., Gitelson A.A., Nguy-Robertson A.L., Peng Y. Comparison of different vegetation indices for the remote assessment of green leaf area index of crops. Remote Sensing of Environment 2011, 115:3468-3478. 10.1016/j.rse.2011.08.010.
121. Vuolo F., Dini L., D'Urso G. Retrieval of Leaf Area Index from CHRIS/PROBA data: an analysis of the directional and spectral information content. International Journal of Remote Sensing 2008, 29:5063-5072. 10.1080/01431160802036490.
122. Wang Y.P., Baldocchi D., Leuning R., Falge E., Vesala T. Estimating parameters in a land-surface model by applying nonlinear inversion to eddy covariance flux measurements from eight FLUXNET sites. Global Change Biology 2007, 13:652-670. 10.1111/j.1365-2486.2006.01225.x.
123. Wang Q., Tenhunen J., Dinh N., Reichstein M., Otieno D., Granier A., et al. Evaluation of seasonal variation of MODIS derived leaf area index at two European deciduous broadleaf forest sites. Remote Sensing of Environment 2005, 96:475-484. 10.1016/j.rse.2005.04.003.
124. Weiss M., Baret F., Myneni R.B., Pragnère A., Knyazikhin Y. Investigation of a model inversion technique to estimate canopy biophysical variables from spectral and directional reflectance data. Agronomie 2000, 20:3-22.
125. Wu C., Niu Z., Tang Q., Huang W. Estimating chlorophyll content from hyperspectral vegetation indices: Modeling and validation. Agricultural and Forest Meteorology 2008, 148:1230-1241. 10.1016/j.agrformet.2008.03.005.
126. Xu L., Baldocchi D.D. Seasonal trends in photosynthetic parameters and stomatal conductance of blue oak (Quercus douglasii) under prolonged summer drought and high temperature. Tree Physiology 2003, 23:865-877.
127. Yang W., Shabanov N.V., Huang D., Wang W., Dickinson R.E., Nemani R.R., et al. Analysis of leaf area index products from combination of MODIS Terra and Aqua data. Remote Sensing of Environment 2006, 104:297-312. 10.1016/j.rse.2006.04.016.
128. Zaehle S. Effects of parameter uncertainties on the modeling of terrestrial biosphere dynamics. Global Biogeochemical Cycles 2005, 19. 10.1029/2004GB002395.
129. Zhu Z., Woodcock C.E. Object-based cloud and cloud shadow detection in Landsat imagery. Remote Sensing of Environment 2012, 118:83-94. 10.1016/j.rse.2011.10.028.