Estimating winter wheat (Triticum aestivum) LAI and leaf chlorophyll content from canopy reflectance data by integrating agronomic prior knowledge with the PROSAIL model

International Journal of Remote Sensing

Volumn 36, Issue 10, 2015, Pages 2634-2653

  Li, Zhenhai ^a,b,c   Jin, Xiuliang ^b,c   Wang, Jihua ^a   Yang, Guijun ^b,c   Nie, Chenwei ^b,c   Xu, Xingang ^b,c   Feng, Haikuan ^b,c  

^a ZHEJIANG UNIVERSITY   (China)

^b INSTITUTE OF PLANT AND ENVIRONMENT PROTECTION   (China)

^c NATIONAL ENGINEERING RESEARCH CENTER FOR INFORMATION TECHNOLOGY IN AGRICULTURE   (China)

Author keywords

[No Author keywords available]

Indexed keywords

AGRONOMY; CHLOROPHYLL; DECISION MAKING; RADIATIVE TRANSFER; REFLECTION; REMOTE SENSING;

AGRICULTURAL PLANNING; BIO-PHYSICAL VARIABLES; CANOPY REFLECTANCE MODEL; LEAF CHLOROPHYLL CONTENT; MANAGEMENT DECISIONS; RADIATIVE TRANSFER MODEL; REMOTE SENSING DATA; ROOT MEAN SQUARE ERRORS;

MEAN SQUARE ERROR;

CANOPY REFLECTANCE; CHLOROPHYLL; ESTIMATION METHOD; FARMERS KNOWLEDGE; LEAF AREA INDEX; RADIATIVE TRANSFER; WHEAT;

TRITICUM AESTIVUM;

EID: 84929618993     PISSN: 01431161     EISSN: 13665901     Source Type: Journal    
DOI: 10.1080/01431161.2015.1041176     Document Type: Article

References (53)

1. C.Atzberger, 2004. “Object-Based Retrieval of Biophysical Canopy Variables Using Artificial Neural Nets and Radiative Transfer Models.” Remote Sensing of Environment 93: 53–67. doi:10.1016/j.rse.2004.06.016.
2. C.Atzberger,, M.Guérif, F.Baret, and W.Werner. 2010. “Comparative Analysis of Three Chemometric Techniques for the Spectroradiometric Assessment of Canopy Chlorophyll Content in Winter Wheat.” Computers and Electronics in Agriculture 73: 165–173. doi:10.1016/j.compag.2010.05.006.
3. C.Atzberger,, T.Jarmer, M.Schlerf, and Kotz. 2003. “Retrieval of Wheat Bio-Physical Attributes from Hyperspectral Data and SAILH+PROSPECT Radiative Transfer Model.” Proceedings of the third EARSeL Workshop on Imaging Spectroscopy, Oberpfaffenhofen, May 13–16, 473–482.
4. C.Bacour,, F.Baret, D.Béal, M.Weiss, and K.Pavageau. 2006. “Neural Network Estimation of LAI, Fapar, Fcover and Lai×Cab, from Top of Canopy MERIS Reflectance Data: Principles and Validation.” Remote Sensing of Environment 105: 313–325. doi:10.1016/j.rse.2006.07.014.
5. E.Baret,, and G.Guyot. 1991. “Potentials and Limits of Vegetation Indices for LAI and APAR Assessment.” Remote Sensing of Environment 35: 161–173.
6. E.Boegh,, H.Soegaard, N.Broge, C.B.Hasager, N.O.Jensen, K.Schelde, and A.Thomsen. 2002. “Airborne Multispectral Data for Quantifying Leaf Area Index, Nitrogen Concentration, and Photosynthetic Efficiency in Agriculture.” Remote Sensing of Environment 81: 179–193. doi:10.1016/S0034-4257(01)00342-X.
7. N.J.Breda, 2003. “Ground-Based Measurements of Leaf Area Index: A Review of Methods, Instruments and Current Controversies.” Journal of Experimental Botany 54: 2403–2417. doi:10.1093/jxb/erg263.
8. J.M.Chen, 1996. “Evaluation of Vegetation Indices and a Modified Simple Ratio for Boreal Applications.” Canadian Journal of Remote Sensing 22: 229–242. doi:10.1080/07038992.1996.10855178.
9. P.Chen,, D.Haboudane, N.Tremblay, J.Wang, P.Vigneault, and B.Li. 2010. “New Spectral Indicator Assessing the Efficiency of Crop Nitrogen Treatment in Corn and Wheat.” Remote Sensing of Environment 114: 1987–1997. doi:10.1016/j.rse.2010.04.006.
10. B.Combal,, F.Baret, M.Weiss, A.Trubuil, D.Macé, A.Pragnère, R.Myneni, Y.Knyazikhin, and L.Wang. 2003. “Retrieval of Canopy Biophysical Variables from Bidirectional Reflectance - Using Prior Information to Solve the Ill-Posed Inverse Problem.” Remote Sensing of Environment 84: 1–15. doi:10.1016/S0034-4257(02)00035-4.
11. R.Darvishzadeh,, A.Skidmore, M.Schlerf, and C.Atzberger. 2008. “Inversion of a Radiative Transfer Model for Estimating Vegetation LAI and Chlorophyll in a Heterogeneous Grassland.” Remote Sensing of Environment 112: 2592–2604. doi:10.1016/j.rse.2007.12.003.
12. K.Deb,, A.Pratap, S.Agarwal, and T.Meyarivan. 2002. “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II.” IEEE Transactions on Evolutionary Computation 6: 182–197. doi:10.1109/4235.996017.
13. S.Delalieux,, B.Somers, S.Hereijgers, W.W.Verstraeten, W.Keulemans, and P.Coppin. 2008. “A Near-Infrared Narrow-Waveband Ratio to Determine Leaf Area Index in Orchards.” Remote Sensing of Environment 112: 3762–3772. doi:10.1016/j.rse.2008.05.003.
14. H.L.Fang,, S.L.Liang, and A.Kuusk. 2003. “Retrieving Leaf Area Index Using a Genetic Algorithm with a Canopy Radiative Transfer Model.” Remote Sensing of Environment 85: 257–270. doi:10.1016/S0034-4257(03)00005-1.
15. G.Fitzgerald,, D.Rodriguez, and G.O’Leary. 2010. “Measuring and Predicting Canopy Nitrogen Nutrition in Wheat Using a Spectral Index-The Canopy Chlorophyll Content Index (CCCI).” Field Crops Research 116: 318–324. doi:10.1016/j.fcr.2010.01.010.
16. C.M.Fonseca,, and P.J.Fleming. 1993. “Genetic Algorithms for Multiobjective Optimization: Formulation Discussion and Generalization.” Proceedings of the fifth international conference on the genetic algorithms, San Mateo, 416–423.
17. A.A.Gitelson, 2004. “Wide Dynamic Range Vegetation Index for Remote Quantification of Biophysical Characteristics of Vegetation.” Journal of Plant Physiology 161: 165–173. doi:10.1078/0176-1617-01176.
18. A.A.Gitelson,, and M.N.Merzlyak. 1997. “Remote Estimation of Chlorophyll Content in Higher Plant Leaves.” International Journal of Remote Sensing 18: 2691–2697. doi:10.1080/014311697217558.
19. A.A.Gitelson,, A.Vina, V.Ciganda, D.C.Rundquist, and T.J.Arkebauer. 2005. “Remote Estimation of Canopy Chlorophyll Content in Crops.” Geophysical Research Letters 32: L08403. doi:10.1029/2005GL022688.
20. Z.Guo,, C.Zhao, W.Huang, Y.Wang, and J.Guo. 2014. “Nondestructive Quantification of Foliar Chlorophyll in an Apple Orchard by Visible/Near-Infrared Reflectance Spectroscopy and Partial Least Squares.” Spectroscopy Letters 47: 481–487. doi:10.1080/00387010.2013.816748.
21. D.Haboudane,, J.R.Miller, E.Pattey, P.J.Zarco-Tejada, and I.B.Strachan. 2004. “Hyperspectral Vegetation Indices and Novel Algorithms for Predicting Green LAI of Crop Canopies: Modeling and Validation in the Context of Precision Agriculture.” Remote Sensing of Environment 90: 337–352. doi:10.1016/j.rse.2003.12.013.
22. W.He,, H.Yang, J.Pan, and P.Xu, 2012. “Exploring Optimal Design of Look-Up Table for PROSAIL Model Inversion with Multi-Angle MODIS Data.” Proceedings of SPIE 8524, land surface remote sensing, Kyoto, October29, 1–13. doi:10.1117/12.977234.
23. V.Houlès,, M.Guérif, and B.Mary. 2007. “Elaboration of a Nitrogen Nutrition Indicator for Winter Wheat Based on Leaf Area Index and Chlorophyll Content for Making Nitrogen Recommendations.” European Journal of Agronomy 27: 1–11. doi:10.1016/j.eja.2006.10.001.
24. S.Jacquemoud,, and F.Baret. 1990. “PROSPECT: A Model of Leaf Optical-Properties Spectra.” Remote Sensing of Environment 34: 75–91. doi:10.1016/0034-4257(90)90100-Z.
25. S.Jacquemoud,, F.Baret, B.Andrieu, F.M.Danson, and K.Jaggard. 1995. “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 52: 163–172. doi:10.1016/0034-4257(95)00018-V.
26. S.Jacquemoud,, W.Verhoef, F.Baret, C.Bacour, P.J.Zarco-Tejada, G.P.Asner, C.François, and S.L.Ustin. 2009. “PROSPECT + SAIL Models: A Review of Use for Vegetation Characterization.” Remote Sensing Of Environment 113: S56–S66. doi:10.1016/j.rse.2008.01.026.
27. B.Koetz,, F.Baret, H.Poilvé, and J.Hill. 2005. “Use of Coupled Canopy Structure Dynamic and Radiative Transfer Models to Estimate Biophysical Canopy Characteristics.” Remote Sensing of Environment 95: 115–124. doi:10.1016/j.rse.2004.11.017.
28. T.Lavergne,, T.Kaminski, B.Pinty, M.Taberner, N.Gobron, M.M.Verstraete, M.Vossbeck, J.-L.Widlowski, and R.Giering. 2007. “Application to MISR Land Products of an RPV Model Inversion Package Using Adjoint and Hessian Codes.” Remote Sensing of Environment 107: 362–375. doi:10.1016/j.rse.2006.05.021.
29. G.Lemaire,, M.Jeuffroy, and F.Gastal. 2008. “Diagnosis Tool for Plant and Crop N Status in Vegetative Stage Theory and Practices for Crop N Management.” European Journal of Agronomy 28: 614–624. doi:10.1016/j.eja.2008.01.005.
30. G.Lemaire,, E.Oosterom, J.Sheehy, M.H.Jeuffroy, A.Massignam, and L.Rossato. 2007. “Is Crop N Demand More Closely Related to Dry Matter Accumulation or Leaf Area Expansion during Vegetative Growth?” Field Crops Research 100: 91–106. doi:10.1016/j.fcr.2006.05.009.
31. X.Li,, Y.Zhang, Y.Bao, J.Luo, X.Jin, X.Xu, X.Song, and G.Yang. 2014. “Exploring the Best Hyperspectral Features for LAI Estimation Using Partial Least Squares Regression.” Remote Sensing 6: 6221–6241. doi:10.3390/rs6076221.
32. L.Y.Liu,, J.H.Wang, Y.S.Bao, W.J.Huang, Z.H.Ma, and C.J.Zhao. 2006. “Predicting Winter Wheat Condition, Grain Yield and Protein Content Using Multi-Temporal Envisat-Asar and Landsat TM Satellite Images.” International Journal of Remote Sensing 27: 737–753. doi:10.1080/01431160500296867.
33. T.Matsunaka,, Y.Watanabe, T.Miyawaki, and N.Ichikawa. 1997. “Prediction of Grain Protein Content in Winter Wheat through Leaf Color Measurements Using a Chlorophyll Meter.” Soil Science and Plant Nutrition 43: 127–134. doi:10.1080/00380768.1997.10414721.
34. M.Meroni,, R.Colombo, and C.Panigada. 2004. “Inversion of a Radiative Transfer Model with Hyperspectral Observations for LAI Mapping in Poplar Plantations.” Remote Sensing of Environment 92: 195–206. doi:10.1016/j.rse.2004.06.005.
35. G.Mountrakis,, J.Im, and C.Ogole. 2011. “Support Vector Machines in Remote Sensing: A Review.” ISPRS Journal of Photogrammetry and Remote Sensing 66: 247–259. doi:10.1016/j.isprsjprs.2010.11.001.
36. G.S.Nearing,, W.T.Crow, K.R.Thorp, M.S.Moran, R.H.Reichle, and H.V.Gupta. 2012. “Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment.” Water Resources Research 48: W05525. doi:10.1029/2011WR011420.
37. J.P.Rivera,, J.Verrelst, G.Leonenko, and J.Moreno. 2013. “Multiple Cost Functions and Regularization Options for Improved Retrieval of Leaf Chlorophyll Content and LAI through Inversion of the PROSAIL Model.” Remote Sensing 5: 3280–3304. doi:10.3390/rs5073280.
38. D.A.Sims,, and J.A.Gamon. 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. doi:10.1016/S0034-4257(02)00010-X.
39. K.Steddom,, G.Heidel, D.Jones, and C.M.Rush. 2003. “Remote Detection of Rhizomania in Sugar Beets.” Phytopathology 93: 720–726. doi:10.1094/PHYTO.2003.93.6.720.
40. K.R.Thorp,, G.Wang, A.L.West, M.S.Moran, K.F.Bronson, J.W.White, and J.Mon. 2012. “Estimating Crop Biophysical Properties from Remote Sensing Data by Inverting Linked Radiative Transfer and Ecophysiological Models.” Remote Sensing of Environment 124: 224–233. doi:10.1016/j.rse.2012.05.013.
41. D.R.Tottman, 1987. “The Decimal Code for the Growth Stages of Cereals, with Illustrations.” Annals of Applied Biology 110: 441–454. doi:10.1111/j.1744-7348.1987.tb03275.x.
42. R.Tripathi,, R.N.Sahoo, V.K.Sehgal, R.K.Tomar, S.Pandey, D.Chakraborty, and N.Kalra. 2006. “Retrieval of Plant Biophysical Parameters through Inversion of PROSAIL Model.” Proceedings of SPIE 6411, Agriculture and Hydrology Applications of Remote Sensing, Goa, November13, 1–7. doi:10.1117/12.697954.
43. S.L.Ustin,, A.A.Gitelson, S.Jacquemoud, M.Schaepman, G.P.Asner, J.A.Gamon, and P.Zarco-Tejada. 2009. “Retrieval of Foliar Information about Plant Pigment Systems from High Resolution Spectroscopy.” Remote Sensing of Environment 113: S67–S77. doi:10.1016/j.rse.2008.10.019.
44. W.Verhoef, 1984. “Light Scattering by Leaf Layers with Application to Canopy Reflectance Modeling: The SAIL Model.” Remote Sensing of Environment 16: 125–141. doi:10.1016/0034-4257(84)90057-9.
45. A.Viña,, A.A.Gitelson, A.L.Nguy-Robertson, and Y.Peng. 2011. “Comparison of Different Vegetation Indices for the Remote Assessment of Green Leaf Area Index of Crops.” Remote Sensing of Environment 115: 3468–3478. doi:10.1016/j.rse.2011.08.010.
46. M.Vincini,, E.Frazzi, and P.D’Alessio. 2006. “Angular Dependence of Maize and Sugar Beet Vis from Directional Chris/Proba Data.” Proceedings of the fourth ESA CHRIS PROBA workshop, September19–21. Frascati: ESRIN.
47. X.Xu,, C.Zhao, J.Wang, J.Zhang, and X.Song. 2014. “Using Optimal Combination Method and in Situ Hyperspectral Measurements to Estimate Leaf Nitrogen Concentration in Barley.” Precision Agriculture 15: 227–240. doi:10.1007/s11119-013-9339-0.
48. F.Yang,, J.L.Sun, H.L.Fang, Z.F.Yao, J.H.Zhang, Y.Q.Zhu, K.S.Song, Z.M.Wang, and M.G.Hu. 2012. “Comparison of Different Methods for Corn LAI Estimation over Northeastern China.” International Journal of Applied Earth Observation and Geoinformation 18: 462–471. doi:10.1016/j.jag.2011.09.004.
49. J.C.Zadoks,, T.T.Chang, and C.F.Konzak. 1974. “A Decimal Code for the Growth Stages of Cereals.” Weed Research 14: 415–421. doi:10.1111/j.1365-3180.1974.tb01084.x.
50. P.J.Zarco-Tejada,, A.Berjon, R.Lopez-Lozano, J.R.Miller, P.Martin, V.Cachorro, M.R.Gonzalez, and A.De Frutos. 2005. “Assessing Vineyard Condition with Hyperspectral Indices: Leaf and Canopy Reflectance Simulation in a Row-Structured Discontinuous Canopy.” Remote Sensing of Environment 99: 271–287. doi:10.1016/j.rse.2005.09.002.
51. P.Zhang,, B.Anderson, B.Tan, D.Huang, and R.Myneni. 2005. “Potential Monitoring of Crop Production Using a Satellite-Based Climate-Variability Impact Index.” Agricultural and Forest Meteorology 132: 344–358. doi:10.1016/j.agrformet.2005.09.004.
52. Q.Y.Zhang,, X.M.Xiao, B.Braswell, E.Linder, F.Baret, and B.Moore. 2005. “Estimating Light Absorption by Chlorophyll, Leaf and Canopy in a Deciduous Broadleaf Forest Using MODIS Data and a Radiative Transfer Model.” Remote Sensing of Environment 99: 357–371. doi:10.1016/j.rse.2005.09.009.
53. S.J.Zhao,, G.A.Shi, and X.C.Dong. 2002. Techniques of Plant Physiological Experiment. Beijing: China Agriculture Scientech Press.