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

References

• Atzberger, C. 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.
   Web of Science ®Google Scholar
• Atzberger, C., 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.
   Web of Science ®Google Scholar
• Atzberger, C., 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.
   Google Scholar
• Bacour, C., 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.
   Web of Science ®Google Scholar
• Baret, E., and G. Guyot. 1991. “Potentials and Limits of Vegetation Indices for LAI and APAR Assessment.” Remote Sensing of Environment 35: 161–173.
   Web of Science ®Google Scholar
• Boegh, E., 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.
   Web of Science ®Google Scholar
• Breda, N. J. 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.
   PubMed Web of Science ®Google Scholar
• Chen, J. M. 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.
   Google Scholar
• Chen, P., 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.
   Web of Science ®Google Scholar
• Combal, B., 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.
   Web of Science ®Google Scholar
• Darvishzadeh, R., 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.
   Web of Science ®Google Scholar
• Deb, K., 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.
   Web of Science ®Google Scholar
• Delalieux, S., 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.
   Web of Science ®Google Scholar
• Fang, H. L., 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.
   Web of Science ®Google Scholar
• Fitzgerald, G., 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.
   Web of Science ®Google Scholar
• Fonseca, C. M., 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.
   Google Scholar
• Gitelson, A. A. 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.
   PubMed Web of Science ®Google Scholar
• Gitelson, A. A., 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.
   Web of Science ®Google Scholar
• Gitelson, A. A., 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.
   Web of Science ®Google Scholar
• Guo, Z., 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.
   Web of Science ®Google Scholar
• Haboudane, D., 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.
   Web of Science ®Google Scholar
• He, W., 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, October 29, 1–13. doi:10.1117/12.977234.
   Google Scholar
• Houlès, V., 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.
   Web of Science ®Google Scholar
• Jacquemoud, S., 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.
   Web of Science ®Google Scholar
• Jacquemoud, S., 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.
   Web of Science ®Google Scholar
• Jacquemoud, S., 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.
   Web of Science ®Google Scholar
• Koetz, B., 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.
   Web of Science ®Google Scholar
• Lavergne, T., 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.
   Web of Science ®Google Scholar
• Lemaire, G., 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.
   Web of Science ®Google Scholar
• Lemaire, G., 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.
   Web of Science ®Google Scholar
• Li, X., 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.
   Web of Science ®Google Scholar
• Liu, L. Y., 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.
   Web of Science ®Google Scholar
• Matsunaka, T., 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.
   Web of Science ®Google Scholar
• Meroni, M., 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.
   Web of Science ®Google Scholar
• Mountrakis, G., 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.
   Web of Science ®Google Scholar
• Nearing, G. S., 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.
   Web of Science ®Google Scholar
• Rivera, J. P., 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.
   Web of Science ®Google Scholar
• Sims, D. A., 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.
   Web of Science ®Google Scholar
• Steddom, K., 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.
   PubMed Web of Science ®Google Scholar
• Thorp, K. R., 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.
   Web of Science ®Google Scholar
• Tottman, D. R. 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.
   Web of Science ®Google Scholar
• Tripathi, R., 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, November 13, 1–7. doi:10.1117/12.697954.
   Google Scholar
• Ustin, S. L., 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.
   Web of Science ®Google Scholar
• Verhoef, W. 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.
   Web of Science ®Google Scholar
• Viña, A., 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.
   Web of Science ®Google Scholar
• Vincini, M., 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, September 19–21. Frascati: ESRIN.
   Google Scholar
• Xu, X., 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.
   Web of Science ®Google Scholar
• Yang, F., 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.
   Web of Science ®Google Scholar
• Zadoks, J. C., 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.
   Web of Science ®Google Scholar
• Zarco-Tejada, P. J., 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.
   Web of Science ®Google Scholar
• Zhang, P., 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.
   Web of Science ®Google Scholar
• Zhang, Q. Y., 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.
   Web of Science ®Google Scholar
• Zhao, S. J., G. A. Shi, and X. C. Dong. 2002. Techniques of Plant Physiological Experiment. Beijing: China Agriculture Scientech Press.
   Google Scholar