SCIRP Mobile Website
Paper Submission

Why Us? >>

  • - Open Access
  • - Peer-reviewed
  • - Rapid publication
  • - Lifetime hosting
  • - Free indexing service
  • - Free promotion service
  • - More citations
  • - Search engine friendly

Free SCIRP Newsletters>>

Add your e-mail address to receive free newsletters from SCIRP.

 

Contact Us >>

WhatsApp  +86 18163351462(WhatsApp)
   
Paper Publishing WeChat
Book Publishing WeChat
(or Email:book@scirp.org)

Article citations

More>>

Eppley, R.W., Stewart, E., Abbott, M.R. and Heyman, U. (1985) Estimating Ocean Primary Production from Satellite Chlorophyll. Introduction to Regional Differences and Statistics for the Southern California Bight. Journal of Plankton Research, 7, 57-70.
https://doi.org/10.1093/plankt/7.1.57

has been cited by the following article:

  • TITLE: Estimating Ocean Chlorophyll Using the Penalized Three Dimensional (3D) Blending Technique

    AUTHORS: Mathias A. Onabid, Simon Wood

    KEYWORDS: Integrated Least Squares, Integrated Squared Derivative, Basis Function, Penalty Matrix, Penalized Model, In-Situ, Satellite

    JOURNAL NAME: Open Journal of Marine Science, Vol.8 No.3, July 18, 2018

    ABSTRACT: The Thin Plate Regression Spline (TPRS) was introduced as a means of smoothing off the differences between the satellite and in-situ observations during the two dimensional (2D) blending process in an attempt to calibrate ocean chlorophyll. The result was a remarkable improvement on the predictive capabilities of the penalized model making use of the satellite observation. In addition, the blending process has been extended to three dimensions (3D) since it is believed that most physical systems exist in the three dimensions (3D). In this article, an attempt to obtain more reliable and accurate predictions of ocean chlorophyll by extending the penalization process to three dimensional (3D) blending is presented. Penalty matrices were computed using the integrated least squares (ILS) and integrated squared derivative (ISD). Results obtained using the integrated least squares were not encouraging, but those obtained using the integrated squared derivative showed a reasonable improvement in predicting ocean chlorophyll especially where the validation datum was surrounded by available data from the satellite data set, however, the process appeared computationally expensive and the results matched the other methods on a general scale. In both case, the procedure for implementing the penalization process in three dimensional blending when penalty matrices were calculated using the two techniques has been well established and can be used in any similar three dimensional problem when it becomes necessary.