MERIS Phytoplankton Time Series Products from the SW Iberian Peninsula (Sagres) Using Seasonal-Trend Decomposition Based on Loess

被引:33
作者
Cristina, Sonia [1 ,2 ]
Cordeiro, Clara [3 ,4 ]
Lavender, Samantha [5 ]
Goela, Priscila Costa [1 ,2 ]
Icely, John [1 ,6 ]
Newton, Alice [1 ,7 ]
机构
[1] Univ Algarve, Ctr Marine & Environm Res CIMA, FCT, Campus Gambelas, P-8005139 Faro, Portugal
[2] Univ Cadiz, Fac Marine & Environm Sci, Campus Puerto Real,Poligono San Pedro S-N, Cadiz 11510, Spain
[3] Univ Algarve, Fac Sci & Technol FCT, Campus Gambelas, P-8005139 Faro, Portugal
[4] Univ Lisbon, Ctr Stat & Applicat CEAUL, Fac Sci, Bloco C6 Piso 4, P-1749016 Lisbon, Portugal
[5] Pixalyt Ltd, 1 Davy Rd,Plymouth Sci Pk, Plymouth PL6 8BX, Devon, England
[6] Sagremarisco Lda, Apartado 21, P-8650999 Vila Do Bispo, Portugal
[7] Norwegian Inst Air Res NILU IMPEC, Box 100, N-2027 Kjeller, Norway
关键词
MERIS; time series; Seasonal-Trend Decomposition; stl.fit(); Algal Pigment Index 1; water leaving reflectance; inter-annual seasonal variability; Iberian Peninsula; Sagres; OCEAN COLOR PRODUCTS; CHLOROPHYLL-A; TEMPORAL VARIABILITY; SOUTHWEST COAST; WATERS; COMMUNITY; DYNAMICS; IMPLEMENTATION; SUPPORT;
D O I
10.3390/rs8060449
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The European Space Agency has acquired 10 years of data on the temporal and spatial distribution of phytoplankton biomass from the MEdium Resolution Imaging Spectrometer (MERIS) sensor for ocean color. The phytoplankton biomass was estimated with the MERIS product Algal Pigment Index 1 (API 1). Seasonal-Trend decomposition of time series based on Loess (STL) identified the temporal variability of the dynamical features in the MERIS products for water leaving reflectance ((w)()) and API 1. The advantages of STL is that it can identify seasonal components changing over time, it is responsive to nonlinear trends, and it is robust in the presence of outliers. One of the novelties in this study is the development and the implementation of an automatic procedure, stl.fit(), that searches the best data modeling by varying the values of the smoothing parameters, and by selecting the model with the lowest error measure. This procedure was applied to 10 years of monthly time series from Sagres in the Southwestern Iberian Peninsula at three Stations, 2, 10 and 18 km from the shore. Decomposing the MERIS products into seasonal, trend and irregular components with stl.fit(), the (w)() indicated dominance of the seasonal and irregular components while API 1 was mainly dominated by the seasonal component, with an increasing effect from inshore to offshore. A comparison of the seasonal components between the (w)() and the API 1 product, showed that the variations decrease along this time period due to the changes in phytoplankton functional types. Furthermore, inter-annual seasonal variation for API 1 showed the influence of upwelling events and in which month of the year these occur at each of the three Sagres stations. The stl.fit() is a good tool for any remote sensing study of time series, particularly those addressing inter-annual variations. This procedure will be made available in R software.
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页数:16
相关论文
共 47 条
[1]   Satellite-based products for monitoring optically complex inland waters in support of EU Water Framework Directive [J].
Alikas, Krista ;
Kangro, Kersti ;
Randoja, Reiko ;
Philipson, Petra ;
Asukuell, Elar ;
Pisek, Jan ;
Reinart, Anu .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (17) :4446-4468
[2]  
Bisgaard S., 2011, BOOK TIME SERIES ANA, P155
[3]  
Brockmann C., 2006, P 2 WORK M MERIS AAT
[4]   Seasonality of oceanic primary production and its interannual variability from 1998 to 2007 [J].
Brown, Christopher W. ;
Uz, Stephanie Schollaert ;
Corliss, Bruce H. .
DEEP-SEA RESEARCH PART I-OCEANOGRAPHIC RESEARCH PAPERS, 2014, 90 :166-175
[5]   Chlorophyll a and chemical signatures during an upwelling event off the South Portuguese coast (SW Iberia) [J].
Cardeira, Sara ;
Rita, Filomena ;
Relvas, Paulo ;
Cravo, Alexandra .
CONTINENTAL SHELF RESEARCH, 2013, 52 :133-149
[6]  
Cleveland R. B., 1990, J Off Stat, V6, P3
[7]  
Cristina SV, 2009, J COASTAL RES, P1479
[8]   Using remote sensing as a support to the implementation of the European Marine Strategy Framework Directive in SW Portugal [J].
Cristina, Sonia ;
Icely, John ;
Goela, Priscila Costa ;
Angel DelValls, Tomas ;
Newton, Alice .
CONTINENTAL SHELF RESEARCH, 2015, 108 :169-177
[9]  
ESA, MERIS PROD HDB ISS 3
[10]   Using CHEMTAX to evaluate seasonal and interannual dynamics of the phytoplankton community off the South-west coast of Portugal [J].
Goela, P. C. ;
Danchenko, S. ;
Icely, J. D. ;
Lubian, L. M. ;
Cristina, S. ;
Newton, A. .
ESTUARINE COASTAL AND SHELF SCIENCE, 2014, 151 :112-123