Remote Sensing Leaf Chlorophyll Content Using a Visible Band Index
暂无分享,去创建一个
C. Daughtry | E. Hunt | J. Eitel | D. Long
[1] J. Hanway. How a corn plant develops , 1966 .
[2] C. Jordan. Derivation of leaf-area index from quality of light on the forest floor , 1969 .
[3] H. Gausman,et al. Interaction of Isotropic Light with a Compact Plant Leaf , 1969 .
[4] L. D. Miller,et al. Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie, Pawnee National Grasslands, Colorado , 1972 .
[5] J. A. Schell,et al. Monitoring vegetation systems in the great plains with ERTS , 1973 .
[6] H. Gausman,et al. Leaf Reflectance vs. Leaf Chlorophyll and Carotenoid Concentrations for Eight Crops1 , 1977 .
[7] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .
[8] W. Verhoef. Light scattering by leaf layers with application to canopy reflectance modelling: The SAIL model , 1984 .
[9] A. Huete. A soil-adjusted vegetation index (SAVI) , 1988 .
[10] S. Goward,et al. Vegetation canopy PAR absorptance and the normalized difference vegetation index - An assessment using the SAIL model , 1992 .
[11] J. Schepers,et al. Comparison of corn leaf nitrogen concentration and chlorophyll meter readings , 1992 .
[12] A. Huete,et al. A Modified Soil Adjusted Vegetation Index , 1994 .
[13] A. Wellburn. The Spectral Determination of Chlorophylls a and b, as well as Total Carotenoids, Using Various Solvents with Spectrophotometers of Different Resolution* , 1994 .
[14] A. Gitelson,et al. Quantitative estimation of chlorophyll-a using reflectance spectra : experiments with autumn chestnut and maple leaves , 1994 .
[15] F. Castelli,et al. Non-destructive determination of leaf chlorophyll content in four crop species , 1996 .
[16] H. R. Duke,et al. Remote Sensing of Plant Nitrogen Status in Corn , 1996 .
[17] S. Ustin,et al. Estimating leaf biochemistry using the PROSPECT leaf optical properties model , 1996 .
[18] J. Schepers,et al. Analysis of Aerial Photography for Nitrogen Stress within Corn Fields , 1996 .
[19] G. Rondeaux,et al. Optimization of soil-adjusted vegetation indices , 1996 .
[20] A. Gitelson,et al. Use of a green channel in remote sensing of global vegetation from EOS- MODIS , 1996 .
[21] J. Schepers,et al. Transmittance and reflectance measurements of corn leaves from plants with different nitrogen and water supply , 1996 .
[22] J. L. Anderson,et al. Assessing corn yield and nitrogen uptake variability with digitized aerial infrared photographs , 1997 .
[23] Barry R. Masters,et al. The Image Processing Handbook , 1999 .
[24] P. Pinter,et al. Measuring Wheat Senescence with a Digital Camera , 1999 .
[25] Moon S. Kim,et al. Estimating Corn Leaf Chlorophyll Concentration from Leaf and Canopy Reflectance , 2000 .
[26] M. Louhaichi,et al. Spatially Located Platform and Aerial Photography for Documentation of Grazing Impacts on Wheat , 2001 .
[27] N. Broge,et al. Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density , 2001 .
[28] John R. Miller,et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .
[29] A. Gitelson,et al. Novel algorithms for remote estimation of vegetation fraction , 2002 .
[30] P. Scharf,et al. Remote sensing for nitrogen management , 2002 .
[31] Yadvinder Singh,et al. Chlorophyll Meter– and Leaf Color Chart–Based Nitrogen Management for Rice and Wheat in Northwestern India , 2002 .
[32] P. Scharf,et al. Calibrating Corn Color from Aerial Photographs to Predict Sidedress Nitrogen Need , 2002 .
[33] A. Huete,et al. Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .
[34] M. Richardson,et al. Quantifying Turfgrass Color Using Digital Image Analysis , 2003 .
[35] Ronnie W. Heiniger,et al. Quantitative Approaches for Using Color Infrared Photography for Assessing In‐Season Nitrogen Status in Winter Wheat , 2003 .
[36] Yuri A. Gritz,et al. Relationships between leaf chlorophyll content and spectral reflectance and algorithms for non-destructive chlorophyll assessment in higher plant leaves. , 2003, Journal of plant physiology.
[37] James E. McMurtrey,et al. Assessing crop residue cover using shortwave infrared reflectance , 2004 .
[38] John R. Miller,et al. Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture , 2004 .
[39] J. Markwell,et al. Calibration of the Minolta SPAD-502 leaf chlorophyll meter , 2004, Photosynthesis Research.
[40] N. Oppelt,et al. Hyperspectral monitoring of physiological parameters of wheat during a vegetation period using AVIS data , 2004 .
[41] J. Dash,et al. The MERIS terrestrial chlorophyll index , 2004 .
[42] A. Viña,et al. Remote estimation of canopy chlorophyll content in crops , 2005 .
[43] J. G. White,et al. Aerial Color Infrared Photography for Determining Early In‐Season Nitrogen Requirements in Corn , 2005 .
[44] C. Daughtry,et al. Evaluation of Digital Photography from Model Aircraft for Remote Sensing of Crop Biomass and Nitrogen Status , 2005, Precision Agriculture.
[45] H. Pleijel,et al. Evaluating the relationship between leaf chlorophyll concentration and SPAD-502 chlorophyll meter readings , 2007, Photosynthesis Research.
[46] Benoit Rivard,et al. Foliar spectral properties following leaf clipping and implications for handling techniques , 2006 .
[47] Andreas Buerkert,et al. Optimum Nitrogen Fertilization of Winter Wheat Based on Color Digital Camera Images , 2007 .
[48] J. Schepers,et al. An Algorithm for Corn Nitrogen Recommendations Using a Chlorophyll Meter Based Sufficiency Index , 2007 .
[49] Jeffrey G. White,et al. Aerial Color Infrared Photography to Optimize In‐Season Nitrogen Fertilizer Recommendations in Winter Wheat , 2007 .
[50] H. P. W. Jayasuriya,et al. Suitability of low-altitude remote sensing images for estimating nitrogen treatment variations in rice cropping for precision agriculture adoption , 2007 .
[51] J. Eitel,et al. Using in‐situ measurements to evaluate the new RapidEye™ satellite series for prediction of wheat nitrogen status , 2007 .
[52] Brigitte Leblon,et al. Non-destructive estimation of potato leaf chlorophyll from canopy hyperspectral reflectance using the inverted PROSAIL model , 2007, International Journal of Applied Earth Observation and Geoinformation.
[53] Troy Jensen,et al. Detecting the attributes of a wheat crop using digital imagery acquired from a low-altitude platform , 2007 .
[54] Roberta E. Martin,et al. PROSPECT-4 and 5: Advances in the leaf optical properties model separating photosynthetic pigments , 2008 .
[55] C. Daughtry,et al. Mitigating the effects of soil and residue water contents on remotely sensed estimates of crop residue cover , 2008 .
[56] G. Meyer,et al. Verification of color vegetation indices for automated crop imaging applications , 2008 .
[57] John R. Miller,et al. Remote Estimation of Crop Chlorophyll Content Using Spectral Indices Derived From Hyperspectral Data , 2008, IEEE Transactions on Geoscience and Remote Sensing.
[58] M. Vincini,et al. A broad-band leaf chlorophyll vegetation index at the canopy scale , 2008, Precision Agriculture.
[59] Rasmus Houborg,et al. Utility of an Image-Based Canopy Reflectance Modeling Tool for Remote Estimation of LAI and Leaf Chlorophyll Content in Crop Systems , 2008, IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium.
[60] E. Hunt,et al. Combined Spectral Index to Improve Ground‐Based Estimates of Nitrogen Status in Dryland Wheat , 2008 .
[61] A. Gitelson,et al. Application of Spectral Remote Sensing for Agronomic Decisions , 2008 .
[62] W. Verhoef,et al. PROSPECT+SAIL models: A review of use for vegetation characterization , 2009 .
[63] Paul E. Gessler,et al. Sensitivity of Ground‐Based Remote Sensing Estimates of Wheat Chlorophyll Content to Variation in Soil Reflectance , 2009 .
[64] R. A. Marenco,et al. Relationship between specific leaf area, leaf thickness, leaf water content and SPAD-502 readings in six Amazonian tree species , 2009, Photosynthetica.
[65] Rasmus Houborg,et al. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at regional scales , 2009 .
[66] J. Thomasson,et al. Cotton Leaf Reflectance Changes after Removal from the Plant , 2009 .
[67] Martha C. Anderson,et al. Utility of an image-based canopy reflectance modeling tool for remote estimation of LAI and leaf chlorophyll content at the field scale , 2009 .
[68] Humberto Bustince,et al. New method to assess barley nitrogen nutrition status based on image colour analysis , 2009 .
[69] Craig S. T. Daughtry,et al. Acquisition of NIR-Green-Blue Digital Photographs from Unmanned Aircraft for Crop Monitoring , 2010, Remote. Sens..
[70] Geert Verhoeven,et al. It's all about the format – unleashing the power of RAW aerial photography , 2010 .