Reflectance estimation of canopy nitrogen content in winter wheat using optimised hyperspectral spectral indices and partial least squares regression
Tóm tắt
Từ khóa
Tài liệu tham khảo
Barnes, 2000, Coincident detection of crop water stress nitrogen status and canopy density using ground based multispectral data
Broge, 2000, Comparing prediction power and stability of broad band and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density, Remote Sensing of Environment, 76, 156, 10.1016/S0034-4257(00)00197-8
Chen, 2006, Synchronizing N supply from soil and fertilizer and N demand of winter wheat by an improved Nmin method, Nutrient Cycling in Agroecosystems, 74, 91, 10.1007/s10705-005-1701-9
Cho, 2006, A new technique for extracting the red edge position from hyperspectral data: the linear extrapolation method, Remote Sensing of Environment, 101, 181, 10.1016/j.rse.2005.12.011
Cho, 2008, Towards red-edge positions less sensitive to canopy biophysical parameters for leaf chlorophyll estimation using properties optique spectrales des feuilles (PROSPECT) and scattering by arbitrarily inclined leaves (SAILH) simulated data, International Journal of Remote Sensing, 29, 2241, 10.1080/01431160701395328
Dash, 2004, The MERIS terrestrial chlorophyll index, International Journal of Remote Sensing, 25, 5403, 10.1080/0143116042000274015
Daughtry, 2000, Estimating corn leaf chlorophyll concentration from leaf and canopy reflectance, Remote Sensing of Environment, 74, 229, 10.1016/S0034-4257(00)00113-9
Delegido, 2010, Estimating chlorophyll content of crops from hyperspectral data using a normalized area over reflectance curve (NAOC), International Journal of Applied Earth Observation and Geoinformation, 12, 165, 10.1016/j.jag.2010.02.003
Delegido, 2011, Remote estimation of crop chlorophyll content by means of high-spectral-resolution reflectance techniques, Agronomy Journal, 103, 1834, 10.2134/agronj2011.0101
Erdle, 2011, Comparison of active and passive spectral sensors in discriminating biomass parameters and nitrogen status in wheat cultivars, Field Crops Research, 124, 74, 10.1016/j.fcr.2011.06.007
Fava, 2009, Identification of hyperspectral vegetation indices for Mediterranean pasture characterization, International Journal of Applied Earth Observation and Geoinformation, 11, 233, 10.1016/j.jag.2009.02.003
Gislum, 2004, Quantification of nitrogen concentration in perennial ryegrass and red fescue using near-infrared reflectance spectroscopy (NIRS) and chemometrics, Field Crops Research, 88, 269, 10.1016/j.fcr.2004.01.021
Gitelson, 2005, Remote estimation of canopy chlorophyll content in crops, Geophysical Research Letters, 32, L08403, 10.1029/2005GL022688
Green, 2003, Foliar morphology and canopy nitrogen as predictors of light-use efficiency in terrestrial vegetation, Agricultural and Forest Meteorology, 115, 163, 10.1016/S0168-1923(02)00210-1
Guyot, 1988, High spectral resolution: determination of spectral shifts between the red and the near infrared, International Archives of Photogrammetry and Remote Sensing, 11, 750
Haboudane, 2002, Integrated narrowband vegetation indices for prediction of crop chlorophyll content for application to precision agriculture, Remote Sensing of Environment, 81, 416, 10.1016/S0034-4257(02)00018-4
Haboudane, 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, 10.1016/j.rse.2003.12.013
Haboudane, 2008, Remote estimation of crop chlorophyll content using spectral indices derived from hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, 46, 423, 10.1109/TGRS.2007.904836
Hansen, 2003, Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression, Remote Sensing of Environment, 86, 542, 10.1016/S0034-4257(03)00131-7
Hatfield, 2008, Application of spectral remote sensing for agronomic decisions, Agronomy Journal, 100, 117, 10.2134/agronj2006.0370c
Herrmann, 2011, LAI assessment of wheat and potato crops by VEN mu S and Sentinel-2 bands, Remote Sensing of Environment, 115, 2141, 10.1016/j.rse.2011.04.018
Jasper, 2009, 23
Jordan, 1969, Derivation of leaf-area index from quality of light on the forest floor, Ecology, 50, 663, 10.2307/1936256
Justes, 1994, Determination of a critical nitrogen concentration dilution curve for winter wheat, Annals of Botany, 74, 397, 10.1006/anbo.1994.1133
Kim, 1994, The use of high spectral resolution bands for estimating absorbed photosynthetically active radiation (APAR)
Lemaire, 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, 10.1016/j.eja.2008.01.005
Li, 2010, Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages, Precision Agriculture, 11, 335, 10.1007/s11119-010-9165-6
Li, 2012, Remotely estimating aerial N status of phenologically differing winter wheat cultivars grown in contrasting climatic and geographic zones in China and Germany, Field Crops Research, 138, 21, 10.1016/j.fcr.2012.09.002
Mistele, 2008, Estimating the nitrogen nutrition index using spectral canopy reflectance measurements, European Journal of Agronomy, 29, 184, 10.1016/j.eja.2008.05.007
Mistele, 2010, Tractor-based quadrilateral spectral reflectance measurements to detect biomass and total aerial nitrogen in winter wheat, Agronomy Journal, 102, 499, 10.2134/agronj2009.0282
Mutanga, 2004, Narrow band vegetation indices overcome the saturation problem in biomass estimation, International Journal of Remote Sensing, 25, 3999, 10.1080/01431160310001654923
Nguyen, 2006, Assessment of rice leaf growth and nitrogenstatus by hyperspectral canopy reflectance and partial least square regression, European Journal of Agronomy, 24, 349, 10.1016/j.eja.2006.01.001
Ollinger, 2011, Sources of variability in canopy reflectance and the convergent properties of plants, New Phytologist, 189, 375, 10.1111/j.1469-8137.2010.03536.x
Ollinger, 2008, Canopy nitrogen, carbon assimilation, and albedo in temperate and boreal forests: functional relations and potential climate feedbacks, Proceedings of the National Academy of Sciences USA, 105, 19335, 10.1073/pnas.0810021105
Oppelt, 2004, Hyperspectral monitoring of physiological of wheat during a vegetation period using AVIS data, International Journal of Remote Sensing, 25, 145, 10.1080/0143116031000115300
Pearson, 1972, Remote mapping of standing crop biomass for estimation of the productivity of the short grass prairie, 1357
Pinter, 2003, Remote sensing for crop management, Photogrammetric Engineering & Remote Sensing, 69, 647, 10.14358/PERS.69.6.647
Rodriguez-Moreno, 2011, Evaluating spectral vegetation indices for a practical estimation of nitrogen concentration in dual-purpose (forage and grain) triticale, Spanish Journal of Agricultural Research, 9, 681, 10.5424/sjar/20110903-265-10
Rouse, 1974
Schmidhalter, 2005, Development of a quick on-farm test to determine nitrate levels in soil, Journal Plant Nutrition and Soil Science, 168, 432, 10.1002/jpln.200520521
Serrano, 2002, Remote sensing of nitrogen and lignin in Mediterranean vegetation from AVIRIS data: decomposing biochemical from structural signals, Remote Sensing of Environment, 81, 355, 10.1016/S0034-4257(02)00011-1
Smith, 2003, Analysis of hyperspectral data for estimation of temperate forest canopy nitrogen concentration: comparison between an airborne (AVIRIS) and space borne (Hyperion) sensor, IEEE Transactions on Geoscience and Remote Sensing, 41, 1332, 10.1109/TGRS.2003.813128
Soderstrom, 2010, Prediction of protein content in malting barley using proximal and remote sensing, Precision Agriculture, 11, 587, 10.1007/s11119-010-9181-6
Stroppiana, 2009, Plant nitrogen concentration in paddy rice from field canopy hyperspectral radiometry, Field Crops Research, 111, 119, 10.1016/j.fcr.2008.11.004
Tarpley, 2000, Reflectance indices with precision and accuracy in predicting cotton leaf nitrogen concentration, Crop Science, 40, 1814, 10.2135/cropsci2000.4061814x
Thenkabail, 2000, Hyperspectral vegetation indices and their relationships with agricultural crop characteristics, Remote Sensing of Environment, 71, 158, 10.1016/S0034-4257(99)00067-X
Tian, 2011, Assessing newly developed and published vegetation indices for estimating rice leaf nitrogen concentration with ground- and space-based hyperspectral reflectance, Field Crops Research, 120, 299, 10.1016/j.fcr.2010.11.002
Van Der Heijden, 2007, Combining close-range and remote sensing for local assessment of biophysical characteristics of arable land, International Journal of Remote Sensing, 28, 5485, 10.1080/01431160601105892
Viscarra Rossel, 2008, ParLeS: software for chemometric analysis of spectroscopic data, Chemometrics and Intelligent Laboratory Systems, 90, 72, 10.1016/j.chemolab.2007.06.006
Wang, 2012, Estimating leaf nitrogen concentration with three-band vegetation indices in rice and wheat, Field Crops Research, 129, 90, 10.1016/j.fcr.2012.01.014
Winterhalter, 2011, High throughput phenotyping of canopy water mass and canopy temperature in well-watered and drought stressed tropical maize hybrids in the vegetative stage, European Journal of Agronomy, 35, 22, 10.1016/j.eja.2011.03.004
Wold, 2001, PLS-regression: a basic tool of chemometrics, Chemometrics and Intelligent Laboratory Systems, 58, 109, 10.1016/S0169-7439(01)00155-1
Zarco-Tejada, 2001, Scaling up and model inversion methods with narrow-band optical indices for chlorophyll content estimation in closed forest canopies with hyperspectral data, IEEE Transactions on Geoscience and Remote Sensing, 39, 1491, 10.1109/36.934080