A Genetic-Programming-Based Method for Hyperspectral Data Information Extraction: Agricultural Applications

Created by W.Langdon from gp-bibliography.bib Revision:1.4202

  author =       "Clement Chion and Jacques-Andre Landry and 
                 Luis {Da Costa}",
  title =        "A Genetic-Programming-Based Method for Hyperspectral
                 Data Information Extraction: Agricultural
  journal =      "IEEE Transactions on Geoscience and Remote Sensing",
  year =         "2008",
  month =        aug,
  volume =       "46",
  number =       "8",
  pages =        "2446--2457",
  keywords =     "genetic algorithms, genetic programming, CASI sensor,
                 agricultural application, band selection, canopy
                 nitrogen content, crop biophysical variable, feature
                 selection, genetic programming-spectral vegetation
                 index, hyperspectral data information extraction,
                 hyperspectral remote sensing, pixel reflectance,
                 precision farming, crops, farming, feature extraction,
                 geophysical signal processing, vegetation mapping",
  DOI =          "doi:10.1109/TGRS.2008.922061",
  ISSN =         "0196-2892",
  abstract =     "A new method, called genetic programming-spectral
                 vegetation index (GP-SVI), for the extraction of
                 information from hyperspectral data is presented. This
                 method is introduced in the context of precision
                 farming. GP-SVI derives a regression model describing a
                 specific crop biophysical variable from hyperspectral
                 images (verified with in situ observations). GP-SVI
                 performed better than other methods [multiple
                 regression, tree-based modeling, and genetic
                 algorithm-partial least squares (GA-PLS)] on the task
                 of correlating canopy nitrogen content in a cornfield
                 with pixel reflectance. It is also shown that the band
                 selection performed by GP-SVI is comparable with the
                 selection performed by GA-PLS, a method that is
                 specifically designed to deal with hyperspectral
  notes =        "Also known as \cite{4559746}",

Genetic Programming entries for Clement Chion Jacques-Andre Landry Luis E Da Costa