Next Article in Journal
A Novel Divisive Hierarchical Clustering Algorithm for Geospatial Analysis
Previous Article in Journal
An Automatic Matcher and Linker for Transportation Datasets
Article Menu
Issue 1 (January) cover image

Export Article

Open AccessArticle
ISPRS Int. J. Geo-Inf. 2017, 6(1), 32; doi:10.3390/ijgi6010032

Using Remote Sensing Products to Identify Marine Association Patterns in Factors Relating to ENSO in the Pacific Ocean

1
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2
Key Laboratory of the Earth Observation, Sanya 572029, Hainan, China
*
Authors to whom correspondence should be addressed.
Academic Editor: Wolfgang Kainz
Received: 9 October 2016 / Revised: 16 January 2017 / Accepted: 18 January 2017 / Published: 23 January 2017
View Full-Text   |   Download PDF [4028 KB, uploaded 23 January 2017]   |  

Abstract

El Niño–Southern Oscillation (ENSO) and its relationships with marine environmental parameters comprise a very complicated and interrelated system. Traditional spatiotemporal techniques face great challenges in dealing with which, how, and where the marine environmental parameters in different zones help to drive, and respond to, ENSO events. Remote sensing products covering a 15-year period from 1998 to 2012 were used to quantitatively explore these patterns in the Pacific Ocean (PO) by a prevail quantitative association rule mining algorithm, that is, a priori, within a mining framework. The marine environmental parameters considered were monthly anomaly of sea surface chlorophyll-a (CHLA), monthly anomaly of sea surface temperature (SSTA), monthly anomaly of sea level anomaly (SLAA), monthly anomaly of sea surface precipitation (SSPA), and monthly anomaly of sea surface wind speed (WSA). Four significant discoveries are found, namely: (1) Association patterns among marine environmental parameters and ENSO events were found primarily in five sub-regions of the PO: the western PO, the central and eastern tropical PO, the middle of the northern subtropical PO, offshore of the California coast, and the southern PO; (2) In the western and the middle and east of the equatorial PO, the association patterns are more complicated than other regions; (3) The following factors were found to be predicators of and responses to La Niña events: abnormal decrease of SLAA and WSA in the east of the equatorial PO, abnormal decrease of SSPA and WSA in the middle of the equatorial PO, abnormal decrease of SSTA in the eastern and central tropical PO, and abnormal increase of SLAA in the western PO; (4) Only abnormal decrease of CHLA in the middle of the equatorial PO was found to be a predicator of and response to El Niño events. These findings will help to improve our abilities to identify the marine association patterns in factors relating to ENSO events. View Full-Text
Keywords: marine association patterns; ENSO; marine remote sensing products; Pacific Ocean; data mining marine association patterns; ENSO; marine remote sensing products; Pacific Ocean; data mining
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Xue, C.; Fan, X.; Dong, Q.; Liu, J. Using Remote Sensing Products to Identify Marine Association Patterns in Factors Relating to ENSO in the Pacific Ocean. ISPRS Int. J. Geo-Inf. 2017, 6, 32.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
ISPRS Int. J. Geo-Inf. EISSN 2220-9964 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top