Spectral Bioindicators of Photosynthetic Efciency and Vegetation Stress
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[1] F. Baret,et al. Potentials and limits of vegetation indices for LAI and APAR assessment , 1991 .
[2] Yuxin Miao,et al. Combining chlorophyll meter readings and high spatial resolution remote sensing images for in-season site-specific nitrogen management of corn , 2008, Precision Agriculture.
[3] 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 .
[4] José M. Matías,et al. Functional statistical techniques applied to vine leaf water content determination , 2010, Math. Comput. Model..
[5] Francisca López Granados. Weed detection for site-specific weed management: Mapping and real-time approaches , 2011 .
[6] P. Thenkabail,et al. Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .
[7] Morris Goldberg,et al. Hierarchy in Picture Segmentation: A Stepwise Optimization Approach , 1989, IEEE Trans. Pattern Anal. Mach. Intell..
[8] George Alan Blackburn,et al. Wavelet decomposition of hyperspectral data: a novel approach to quantifying pigment concentrations in vegetation , 2007 .
[9] Georg Bareth,et al. Evaluating hyperspectral vegetation indices for estimating nitrogen concentration of winter wheat at different growth stages , 2010, Precision Agriculture.
[10] Emmanuel Arzuaga-Cruz,et al. Integration of spatial and spectral information by means of unsupervised extraction and classification for homogenous objects applied to multispectral and hyperspectral data , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[11] J. Schjoerring,et al. Reflectance measurement of canopy biomass and nitrogen status in wheat crops using normalized difference vegetation indices and partial least squares regression , 2003 .
[12] John R. Miller,et al. Assessing vineyard condition with hyperspectral indices: Leaf and canopy reflectance simulation in a row-structured discontinuous canopy , 2005 .
[13] L. Tian,et al. A Review on Remote Sensing of Weeds in Agriculture , 2004, Precision Agriculture.
[14] John R. Miller,et al. Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture , 2002 .
[15] K. Staenz,et al. Potential of Hyperion EO-1 hyperspectral data for wheat crop chlorophyll content estimation , 2008 .
[16] Francisca López-Granados,et al. Weed detection for site-specific weed management: mapping and real-time approaches , 2011 .
[17] 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.
[18] Sushma Panigrahy,et al. Use of hyperspectral data to assess the effects of different nitrogen applications on a potato crop , 2007, Precision Agriculture.
[19] Y. Govaerts. Correction of the Meteosat-5 and -6 radiometer solar channel spectral response with the Meteosat-7 sensor spectral characteristics , 1999 .
[20] Arnon Karnieli,et al. Wheat and maize monitoring based on ground spectral measurements and multivariate data analysis , 2007 .
[21] Elizabeth Pattey,et al. Variability of seasonal CASI image data products and potential application for management zone delineation for precision agriculture , 2005 .
[22] S. Wold,et al. The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses , 1984 .
[23] George Alan Blackburn,et al. Retrieval of chlorophyll concentration from leaf reflectance spectra using wavelet analysis. , 2008 .
[24] Y. Cohen,et al. Use of thermal and visible imagery for estimating crop water status of irrigated grapevine. , 2006, Journal of experimental botany.
[25] R. M. Lark,et al. Forming Spatially Coherent Regions by Classification of Multi-Variate Data: An Example from the Analysis of Maps of Crop Yield , 1998, Int. J. Geogr. Inf. Sci..
[26] M. Ashton,et al. Accuracy assessments of hyperspectral waveband performance for vegetation analysis applications , 2004 .
[27] Prasad S. Thenkabail,et al. Evaluation of Narrowband and Broadband Vegetation Indices for Determining Optimal Hyperspectral Wavebands for Agricultural Crop Characterization , 2002 .
[28] W. Cohen,et al. Hyperspectral versus multispectral data for estimating leaf area index in four different biomes , 2004 .
[29] Christian Nansen,et al. Variogram Analysis of Hyperspectral Data to Characterize the Impact of Biotic and Abiotic Stress of Maize Plants and to Estimate Biofuel Potential , 2010, Applied spectroscopy.
[30] A. Skidmore,et al. Leaf Area Index derivation from hyperspectral vegetation indicesand the red edge position , 2009 .
[31] D. Smart,et al. Evaluation of Hyperspectral Reflectance Indexes to Detect Grapevine Water Status in Vineyards , 2007, American Journal of Enology and Viticulture.
[32] Michael E. Schaepman,et al. Estimating canopy water content using hyperspectral remote sensing data , 2010, Int. J. Appl. Earth Obs. Geoinformation.
[33] W. R. Windham,et al. Partial Least Squares Regression of Hyperspectral Images for Contaminant Detection on Poultry Carcasses , 2006 .
[34] P. Groves,et al. Methodology For Hyperspectral Band Selection , 2004 .
[35] J. Moreno,et al. Retrieval of chlorophyll content and LAI of crops using hyperspectral techniques: application to PROBA/CHRIS data , 2008 .
[36] Paul Scheunders,et al. Generic wavelet-based hyperspectral classification applied to vegetation stress detection , 2005, IEEE Transactions on Geoscience and Remote Sensing.
[37] Jon Atli Benediktsson,et al. Recent Advances in Techniques for Hyperspectral Image Processing , 2009 .
[38] N. Elliott,et al. Original papers: Differentiating stress induced by greenbugs and Russian wheat aphids in wheat using remote sensing , 2009 .
[39] A. Gitelson. Wide Dynamic Range Vegetation Index for remote quantification of biophysical characteristics of vegetation. , 2004, Journal of plant physiology.
[40] L. Godfrey,et al. Remotely Sensing Arthropod and Nutrient Stressed Plants: A Case Study with Nitrogen and Cotton Aphid (Hemiptera: Aphididae) , 2010, Environmental entomology.
[41] J. Araus,et al. Spectral vegetation indices as nondestructive tools for determining durum wheat yield. , 2000 .
[42] C. Tucker. Red and photographic infrared linear combinations for monitoring vegetation , 1979 .