[1]Baret F, Guyot G. 1991. Potentials and limits of vegetationindices for LAI and APAR assessment. Remote Sensingof Environment, 35, 161-173[2]Baret F, Guyot G, Major D. 1989. TSAVI - A vegetationindex which minimizes soil brightness effects on LAIand APAR estimation. In: Proceedings of 12thCanadian Symposium on Remote Sensing andIGARSS’89.Vancouver, Canada. pp. 1355-1358[3]Blackburn G. 1998. Quantifying chlorophylls andcaroteniods at leaf and canopy scales: an evaluation ofsome hyperspectral approaches. Remote Sensing ofEnvironment, 66, 273-285[4]Boochs F, Kupfer G, Dockter K, Kühbauch W. 1990. Shapeof the red edge as vitality indicator for plants.International Journal of Remote Sensing, 11, 1741-1753[5]Broge N, Leblanc E. 2000. Comparing prediction power andstability of broadband and hyperspectral vegetationindices for estimation of green leaf area index and canopychlorophyll density. Remote Sensing of Environment,76, 156-172[6]Carlson T N, Ripley D A. 1997. On the relation betweenNDVI, fractional vegetation cover, and leaf area index.Remote Sensing of Environment, 62, 241-252[7]Carter G A. 1994. Ratios of leaf reflectances in narrowwavebands as indicators of plant stress. InternationalJournal of Remote Sensing, 15, 697-703[8]Chappelle E W, Kim M S, McMurtrey III J E. 1992. Ratio analysis of reflectance spectra (RARS): an algorithmfor the remote estimation of the concentrations ofchlorophyll a, chlorophyll b, and carotenoids insoybean leaves. Remote Sensing of Environment, 39,239-247[9]Cho M A, Skidmore A K. 2006. A new technique for extractingthe red edge position from hyperspectral data: the linearextrapolation method. Remote Sensing of Environment,101, 181-193[10]Clevers J, Kooistra L. 2011. Using hyperspectral remotesensing data for retrieving total canopy chlorophylland nitrogen content. In: The 3rd Workshop onHyperspectral Image and Signal Processing:Evolution in Remote Sensing (WHISPERS). IEEE,Lisbon. pp. 1-4[11]Colwell J E. 1974. Vegetation canopy reflectance. RemoteSensing of Environment, 3, 175-183[12]Curran P. 1989. Remote sensing of foliar chemistry. RemoteSensing of Environment, 30, 271-278[13]Daughtry C S T, Walthall C L, Kim M S, de Colstoun E B,McMurtrey J E. 2000. Estimating corn leaf chlorophyllconcentration from leaf and canopy reflectance. RemoteSensing of Environment, 74, 229-239[14]Elvidge C, Chen Z. 1995. Comparison of broad-band andnarrow-band red and near-infrared vegetation indices.Remote Sensing of Environment, 54, 38-48[15]Fava F, Colombo R, Bocchi S, Meroni M, Sitzia M, Fois N,Zucca C. 2009. Identification of hyperspectralvegetation indices for Mediterranean pasturecharacterization. International Journal of AppliedEarth Observation and Geoinformation, 11, 233-243[16]Feng W, Yao X, Zhu Y, Tian Y C, Cao W X. 2008. Monitoringleaf nitrogen status with hyperspectral reflectance inwheat. European Journal of Agronomy, 28, 394-404[17]Filella I, Penuelas J. 1994. The red edge position and shapeas indicators of plant chlorophyll content, biomass andhydric status. International Journal of Remote Sensing,15, 1459-1470[18]Fitzgerald G, Rodriguez D, O扡eary G. 2010. Measuring andpredicting canopy nitrogen nutrition in wheat using aspectral index - the canopy chlorophyll content index(CCCI). Field Crops Research, 116, 318-324[19]Freeman K W G, Arnall K, Mullen D B, Martin R W, Teal KL, Raun R K, William R. 2007. By-plant prediction ofcorn forage biomass and nitrogen uptake at variousgrowth stages using remote sensing and plant height.Agronomy Journal, 99, 530-536[20]Gamon J, Field C, Goulden M, Griffin K, Hartley A, Joel G,Pe駏elas J, Valentini R. 1995. Relationships betweenNDVI, canopy structure, and photosynthesis in threeCalifornian vegetation types. Ecological Applications,5, 28-41[21]Girma K, Holtz S, Tubana B, Solie J, Raun W. 2010. Nitrogenaccumulation in shoots as a function of growth stageof corn and winter wheat. Journal of Plant Nutrition,34, 165-182[22]Gitelson A, Gritz Y, Merzlyak M. 2003. Relationshipsbetween leaf chlorophyll content and spectral reflectanceand algorithms for non-destructive chlorophyllassessment in higher plant leaves. Journal of PlantPhysiology, 160, 271-282[23]Gitelson A A, Kaufman Y J, Merzlyak M N. 1996. Use of agreen channel in remote sensing of global vegetationfrom EOS-MODIS. Remote Sensing of Environment, 58,289-298[24]Hansen P, Schjoerring J. 2003. Reflectance measurement ofcanopy biomass and nitrogen status in wheat cropsusing normalized difference vegetation indices andpartial least squares regression. Remote Sensing ofEnvironment, 86, 542-553[25]Horler D, Dockray M, Barber J. 1983. The red edge of plantleaf reflectance. International Journal of RemoteSensing, 4, 273-288[26]Huete A. 1988. A soil-adjusted vegetation index (SAVI).Remote Sensing of Environment, 25, 295-309[27]van Keulen H. 1982. Graphical analysis of annual cropresponse to fertiliser application. Agricultural Systems,9, 113-126[28]Knipling E B. 1970. Physical and physiological basis forthe reflectance of visible and near-infrared radiationfrom vegetation. Remote Sensing of Environment, 1,155-159[29]Knox N, Skidmore A, Schlerf M, de Boer W, van Wieren S,van der Waal C, Prins H, Slotow R. 2010. Nitrogenprediction in grasses: effect of bandwidth and plantmaterial state on absorption feature selection.International Journal of Remote Sensing, 31, 691-704[30]Kokaly R, Clark R. 1999. Spectroscopic determination ofleaf biochemistry using band-depth analysis ofabsorption features and stepwise multiple linearregression. Remote Sensing of Environment, 67, 267-287[31]Lee K S, Cohen W B, Kennedy R E, Maiersperger T K,Gower S T. 2004. Hyperspectral versus multispectraldata for estimating leaf area index in four differentbiomes. Remote Sensing of Environment, 91, 508-520[32]van Leeuwen W J D, Orr B J, Marsh S E, Herrmann S M.2006. Multi-sensor NDVI data continuity: Uncertaintiesand implications for vegetation monitoring applications.Remote Sensing of Environment, 100, 67-81[33]Lemaire G, Gastal F. 1997. N uptake and distribution inplant canopies. In: Lemaire G, ed., Diagnosis of theNitrogen Status in Crops. Springer-Verlag, Berlin. pp.3-43[34]Li F, Gnyp M L, Jia L, Miao Y, Yu Z, Koppe W, Bareth G,Chen X, Zhang F. 2008. Estimating N status of winterwheat using a handheld spectrometer in the North ChinaPlain. Field Crops Research, 106, 77-85[35]Lukina E V, Freeman K W, Wynn K J, Thomason W E,Mullen R W, Stone M L, Solie J B, Klatt A R, Johnson GV, Elliott R L, et al. 2001. Nitrogen fertilizationoptimization algorithm based on in-season estimatesof yield and plant nitrogen uptake. Journal of Plant Nutrition, 24, 885-898[36]Massart D, Vandeginste B, Deming S, Michotte Y, KaufmanL. 1988. Chemometrics: A Textbook. Elsevier,Amsterdam.Miller J, Hare E, Wu J. 1990. Quantitative characterizationof the vegetation red edge reflectance 1. An inverted-Gaussian reflectance model. International Journal ofRemote Sensing, 11, 1755-1773[37]Moges S M, Raun W R, Mullen R W, Freeman K W,Johnson G V, Solie J B. 2004. Evaluation of green, red,and near infrared bands for predicting winter wheatbiomPass, nitrogen uptake, and final grain yield.Journal of Plant Nutrition, 27, 1431-1441[38]Mutanga O, Skidmore A K. 2004. Narrow band vegetationindices overcome the saturation problem in biomassestimation. International Journal of Remote Sensing,25, 3999-4014[39]Pe駏elas J, Filella I. 1998. Visible and near-iPnfraredreflectance techniques for diagnosing plant physiologicalstatus. Trends in Plant Science, 3, 151-156[40]Pearson R, Miller L. 1972. Remote mapping of standingcrop biomass for estimation of the productivity of theshort grass prairie. In: Proceedings of the 8thtnternational Symposium on Remote Sensing ofEnvironment, Ann Arbor, Michigan. Pawnee NationalGrasslands, Colorado. pp. 1357-1381[41]Peng S, Buresh R J, Huang J, Zhong X, Zou Y, Yang J,Wang G, Liu Y, Hu R, Tang Q. 2010. Improving nitrogenfertilization in rice by site-specific N management. Areview. Agronomy for Sustainable Development, 30,649-656[42]Raun W, Solie J, Johnson G, Stone M, Mullen R, FreemanK, Thomason W, Lukina E. 2002. Improving nitrogenuse efficiency in cereal grain production with opticalsensing and variable rate application. AgronomyJournal, 94, 815-820[43]Richardson A, Wiegand C. 1977. Distinguishing vegetationfrom soil background information. PhotogrammetricEngineering and Remote Sensing, 43, 1541-1552[44]Rondeaux G, Steven M, Baret F. 1996. Optimization of soiladjustedvegetation indices. Remote Sensing ofEnvironment, 55, 95-107[45]Sembiring H, Lees H L, Raun W R, Johnson G V, Solie J B,Stone M L, DeLeon M J, Lukina E V, Cossey D A,LaRuffa J M, et al. 2000. Effect of growth stage andvariety on spectral radiance in winter wheat. Journalof Plant Nutrition, 23, 141-149[46]Sims D, Gamon J. 2002. Relationships between leaf pigmentcontent and spectral reflectance across a wide range ofspecies, leaf structures and developmental stages.Remote Sensing of Environment, 81, 337-354[47]Stone M, Solie J, Raun W, Whitney R, Taylor S, Ringer J.1996. Use of spectral radiance for correcting in-seasonfertilizer nitrogen deficiencies in winter wheat.Transactions of the ASABE, 39, 1623-1631[48]Stroppiana D, Boschetti M, Brivio P, Bocchi S. 2009. Plantnitrogen concentration in paddy rice from field canopyhyperspectral radiometry. Field Crops Research, 111,119-129[49]Tarpley L, Reddy K, Sassenrath-Cole G. 2000. Reflectanceindices with precision and accuracy in predicting cottonleaf nitrogen concentration. Crop Science, 40, 1814-1819[50]Teillet P M, Staenz K, William D J. 1997. Effects of spectral,spatial, and radiometric characteristics on remotesensing vegetation indices of forested regions. RemoteSensing of Environment, 61, 139-149[51]Thenkabail P, Smith R, de Pauw E. 2000. Hyperspectralvegetation indices and their relationships withagricultural crop characteristics. Remote Sensing ofEnvironment, 71, 158-182[52]Tucker C. 1979. Red and photographic infrared linearcombinations for monitoring vegetation. RemoteSensing of Environment, 8, 127-150[53]Vogelmann J, Rock B, Moss D. 1993. Red edge spectralmeasurements from sugar maple leaves. InternationalJournal of Remote Sensing, 14, 1563-1575[54]Wang W, Yao X, Tian Y C, Liu X J, Ni J, Cao W X, Zhu Y.2012. Common spectral bands and optimum vegetationindices for monitoring leaf nitrogen accumulation inrice and wheat. Journal of Integrative Agriculture, 11,2001-2012[55]Walburg G, Bauer M E, Daughtry C S T. 1982. Effects ofnitrogen nutrition on the growth, yield, and reflectancecharacteristics of corn canopies. Agronomy Journal,74, 677-683[56]Willmott C J, Ackleson S G, Davis R E, Feddema J J, Klink KM, Legates D R, O扗onnell J, Rowe C M. 1985. Statisticsfor the evaluation and comparison of models. Journalof Geophysical Research, 90, 8995-9005[57]Xue L, Cao W, Luo W, Dai T, Zhu Y. 2004. Monitoring leafnitrogen status in rice with canopy spectral reflectance.Agronomy Journal, 96, 135-142[58]Yao X, Zhu Y, Tian Y C, Feng W, Cao W X. 2010. Exploringhyperspectral bands and estimation indices for leafnitrogen accumulation in wheat. International Journalof Applied Earth Observation and Geoinformation,12, 89-100[59]Zhao D H, Li J L, Qi J G. 2005. Identification of red and NIRspectral regions and vegetative indices fordiscrimination of cotton nitrogen stress and growthstage. Computers and Electronics in Agriculture, 48,155-169[60]Zhu Y, Zhou D, Yao X, Tian Y, Cao W. 2007. Quantitativerelationships of leaf nitrogen status to canopy spectralreflectance in rice. Australian Journal of AgriculturalResearch, 58, 1077-1085. |