論文

査読有り 国際共著 国際誌
2014年10月

Global Retrieval of Diatom Abundance Based on Phytoplankton Pigments and Satellite Data

REMOTE SENSING
  • Mariana A. Soppa
  • ,
  • Takafumi Hirata
  • ,
  • Brenner Silva
  • ,
  • Tilman Dinter
  • ,
  • Ilka Peeken
  • ,
  • Sonja Wiegmann
  • ,
  • Astrid Bracher

6
10
開始ページ
10089
終了ページ
10106
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.3390/rs61010089
出版者・発行元
MDPI AG

Diatoms are the major marine primary producers on the global scale and, recently, several methods have been developed to retrieve their abundance or dominance from satellite remote sensing data. In this work, we highlight the importance of the Southern Ocean (SO) in developing a global algorithm for diatom using an Abundance Based Approach (ABA). A large global in situ data set of phytoplankton pigments was compiled, particularly with more samples collected in the SO. We revised the ABA to take account of the information on the penetration depth (Z(pd)) and to improve the relationship between diatoms and total chlorophyll-a (TChla). The results showed that there is a distinct relationship between diatoms and TChla in the SO, and a new global model (ABA(Zpd)) improved the estimation of diatoms abundance by 28% in the SO compared with the original ABA model. In addition, we developed a regional model for the SO which further improved the retrieval of diatoms by 17% compared with the global ABA(Zpd) model. As a result, we found that diatom may be more abundant in the SO than previously thought. Linear trend analysis of diatom abundance using the regional model for the SO showed that there are statistically significant trends, both increasing and decreasing, in diatom abundance over the past eleven years in the region.

リンク情報
DOI
https://doi.org/10.3390/rs61010089
Web of Science
https://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=JSTA_CEL&SrcApp=J_Gate_JST&DestLinkType=FullRecord&KeyUT=WOS:000344458000042&DestApp=WOS_CPL
URL
http://www.mdpi.com/2072-4292/6/10/10089
ID情報
  • DOI : 10.3390/rs61010089
  • ISSN : 2072-4292
  • Web of Science ID : WOS:000344458000042

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