Cross-sensor quality assurance for marine observatories

Roee Diamant, Ilan Shachar, Yizhaq Makovsky, Bruno Miguel Ferreira, Nuno Alexandre Cruz

Research output: Contribution to journalArticlepeer-review


Measuring and forecasting changes in coastal and deep-water ecosystems and climates requires sustained long-term measurements from marine observation systems. One of the key considerations in analyzing data from marine observatories is quality assurance (QA). The data acquired by these infrastructures accumulates into Giga and Terabytes per year, necessitating an accurate automatic identification of false samples. A particular challenge in the QA of oceanographic datasets is the avoidance of disqualification of data samples that, while appearing as outliers, actually represent real short-term phenomena, that are of importance. In this paper, we present a novel cross-sensor QA approach that validates the disqualification decision of a data sample from an examined dataset by comparing it to samples from related datasets. This group of related datasets is chosen so as to reflect upon the same oceanographic phenomena that enable some prediction of the examined dataset. In our approach, a disqualification is validated if the detected anomaly is present only in the examined dataset, but not in its related datasets. Results for a surface water temperature dataset recorded by our Texas A&M—Haifa Eastern Mediterranean Marine Observatory (THEMO)—over a period of 7 months, show an improved trade-off between accurate and false disqualification rates when compared to two standard benchmark schemes.

Original languageEnglish
Article number3470
Pages (from-to)1-16
Number of pages16
JournalRemote Sensing
Issue number21
StatePublished - 1 Nov 2020

Bibliographical note

Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.


  • Change detector
  • Data validation
  • Ocean observatories
  • Ocean remote sensing
  • Prediction of data
  • Quality assurance
  • Quality control
  • Regression

ASJC Scopus subject areas

  • General Earth and Planetary Sciences


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