Artificial neural networks to predict corn yield from Compact Airborne Spectrographic Imager data

[1]  Paolo Ferrazzoli,et al.  Retrieving soil moisture and agricultural variables by microwave radiometry using neural networks , 2003 .

[2]  Shiv O. Prasher,et al.  Potential of airborne hyperspectral remote sensing to detect nitrogen deficiency and weed infestation in corn , 2003 .

[3]  J. Pulliainen,et al.  Application of an empirical neural network to surface water quality estimation in the Gulf of Finland using combined optical data and microwave data , 2002 .

[4]  Elizabeth Pattey,et al.  Impact of nitrogen and environmental conditions on corn as detected by hyperspectral reflectance , 2002 .

[5]  Gary E. Varvel,et al.  Use of Remote-Sensing Imagery to Estimate Corn Grain Yield , 2001 .

[6]  M. A. Pizarro,et al.  Variations in Reflectance of Tropical Soils: Spectral-Chemical Composition Relationships from AVIRIS data , 2001 .

[7]  S. Islam,et al.  Estimation of Soil Physical Properties Using Remote Sensing and Artificial Neural Network , 2000 .

[8]  J. V. Stafford,et al.  Implementing precision agriculture in the 21st century. , 2000 .

[9]  B. R. Roberts,et al.  RELATIONSHIPS BETWEEN REMOTELY SENSED REFLECTANCE DATA AND COTTON GROWTH AND YIELD , 2000 .

[10]  Giampiero Maracchi,et al.  Processing of GAC NDVI data for yield forecasting in the Sahelian region , 2000 .

[11]  Sylvie Thiria,et al.  Applying artificial neural network methodology to ocean color remote sensing , 1999 .

[12]  Xiao‐Hai Yan,et al.  A Neural Network Model for Estimating Sea Surface Chlorophyll and Sediments from Thematic Mapper Imagery , 1998 .

[13]  James Lowenberg-DeBoer,et al.  Evaluating the profitability of site-specific farming , 1998 .

[14]  J. C. Ceballos,et al.  Technical note The discrimination of scenes by principal components analysis of multi-spectral imagery , 1997 .

[15]  John R. Miller,et al.  Atmospheric Correction Validation of casi Images Acquired over the Boreas Southern Study Area , 1997 .

[16]  George Alan Blackburn,et al.  An ecological survey of deciduous woodlands using airborne remote sensing and geographical information systems (GIS). , 1997 .

[17]  Yaqiu Jin,et al.  Biomass retrieval from high-dimensional active/passive remote sensing data by using artificial neural networks , 1997 .

[18]  P. Atkinson,et al.  Introduction Neural networks in remote sensing , 1997 .

[19]  J. V. Stafford,et al.  Mapping and interpreting the yield variation in cereal crops , 1996 .

[20]  H. D. Kutzbach,et al.  Investigations on a particular yield mapping system for combine harvesters , 1996 .

[21]  George Simpson,et al.  Crop yield prediction using a CMAC neural network , 1994, Remote Sensing.

[22]  Tsuyoshi Akiyama,et al.  Estimating grain yield of maturing rice canopies using high spectral resolution reflectance measurements , 1991 .

[23]  Paul M. Mather,et al.  Computer Processing of Remotely-Sensed Images: An Introduction , 1988 .

[24]  B. Manly.  Multivariate Statistical Methods : A Primer , 1986 .

[25]  B. S. Duran,et al.  Statistical Methods for Engineers and Scientists. , 1985 .

[26]  T. M. Lillesand,et al.  Remote Sensing and Image Interpretation , 1980 .

[27]  E. C. Barrett,et al.  Introduction to Environmental Remote Sensing. , 1978 .

[28]  B. Brown.  Proceedings of the Society of Photo-optical Instrumentation Engineers, Seminar-in-depth, 'Solving Problems in Security, Surveillance and Law Enforcement with Optical Instrumentation' , 1974 .

[29]  Kenneth A. Sudduth,et al.  STATISTICAL AND NEURAL METHODS FOR SITE–SPECIFIC YIELD PREDICTION , 2003 .

[30]  Shiv O. Prasher,et al.  ESTIMATION OF CROP BIOPHYSICAL PARAMETERS THROUGH AIRBORNE AND FIELD HYPERSPECTRAL REMOTE SENSING , 2003 .

[31]  J. Schepers,et al.  Use of Spectral Radiance to Estimate In-Season Biomass and Grain Yield in Nitrogen- and Water-Stressed Corn. , 2002, Crop science.

[32]  C. Yang,et al.  Airborne multispectral imagery for mapping variable growing conditions and yields of cotton, grain sorghum, and corn , 2001 .

[33]  J. Araus,et al.  Spectral vegetation indices as nondestructive tools for determining durum wheat yield. , 2000 .

[34]  Jing Liu,et al.  Neural networks for setting target corn yields , 2000 .

[35]  Chenghai Yang,et al.  Mapping grain sorghum growth and yield variations using airborne multispectral digital imagery. , 2000 .

[36]  F. Volpe,et al.  The influence of principal component analysis on the spatial structure of a multispectral dataset , 1999 .

[37]  Michael T. Manry,et al.  Attributes of neural networks for extracting continuous vegetation variables from optical and radar , 1998 .

[38]  R. Earl,et al.  Precision farming--the management of variability , 1996 .

[39]  Claude Brezinski,et al.  Numerical Methods for Engineers and Scientists , 1992 .