Monitoring nutrient concentrations in Tampa Bay with MODIS images and machine learning models

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Ni-Bin Chang and Zhemin Xuan",
  booktitle =    "10th IEEE International Conference on Networking,
                 Sensing and Control (ICNSC 2013)",
  title =        "Monitoring nutrient concentrations in {Tampa Bay} with
                 MODIS images and machine learning models",
  year =         "2013",
  month =        apr,
  pages =        "702--707",
  keywords =     "genetic algorithms, genetic programming, environmental
                 science computing, geophysical image processing,
                 learning (artificial intelligence), phosphorus, remote
                 sensing, water treatment, GP model, MODIS image, TP,
                 Tampa Bay, aquatic environment, coastal bay, machine
                 learning model, moderate resolution imaging
                 spectroradiometer, nutrient concentration monitoring,
                 remote sensing reflectance band, short-term seasonality
                 effect, total phosphorus, MODIS, Remote sensing,
                 coastal bay, nutrient monitoring, wastewater
  DOI =          "doi:10.1109/ICNSC.2013.6548824",
  abstract =     "This paper explores the spatiotemporal nutrient
                 patterns in Tampa Bay, Florida with the aid of Moderate
                 Resolution Imaging Spectroradiometer (MODIS) images and
                 Genetic Programming (GP) models that are designed to
                 link Total Phosphorus (TP) levels and remote sensing
                 reflectance bands in aquatic environments. In-situ data
                 were drawn from a local database to support the
                 calibration and validation of the GP model. The GP
                 models show the effective capacity to demonstrating the
                 snapshots of spatio-temporal distributions of TP across
                 the Bay, which helps to delineate the short-term
                 seasonality effect and the global trend of TP in the
                 coastal bay. The model output can provide informative
                 reference for the establishment of contingency plans in
                 treating nutrients-rich runoff.",
  notes =        "Also known as \cite{6548824}",

Genetic Programming entries for Ni-Bin Chang Zhemin Xuan