Publications

Moradi, M (2022). Wavelet transform approach for denoising and decomposition of satellite-derived ocean color time-series: Selection of optimal mother wavelet. ADVANCES IN SPACE RESEARCH, 69(7), 2724-2744.

Abstract
Wavelet Transform (WT) has remarkable advantages for feature extraction and denoising of satellite-derived ocean color time series datasets. The selection of mother wavelet (MWT) is the main challenging issue in the wavelet transform analysis of ocean color time series, since different MWT applied to the same dataset may produce different results. In this study, 57 MWTs were investigated to find the optimal wavelet functions for WT analysis of ocean color time series datasets with particular emphasis on the quantitative approaches. The daily, weekly, and monthly averaged of MODIS Level-3 Chlorophyll-a (Chl-a) series were denoised and decomposed by Discrete Wavelet Transform (DWT) using different MWTs. The seasonal trends of all datasets were extracted using the Seasonal Trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) (STL) and Census X-11 methods, used as references. The statistical Cross Correlation Function (CCF), Signal to Noise Ratio (SNR), and Mean Standard Error (MSE), indexes, plus a Magnitude-Shape quantitative model were used to calculate the correlation and similarity between original and corresponding decomposed and denoised reference Chl-a signals. The similarity indexes were analyzed to evaluate the similarity and correlation between reconstructed denoised signals with original Chl-a series, and between DWT seasonal components with the reference seasonal trends. For a more assessment, two different weekly averaged Chl-a series of SeaWiFS satellite sensor over Bermuda Atlantic region (open ocean waters) and Chesapeake Bay (coastal waters) were evaluated using SeaBASS in situ measurements, and seasonal trends in comparison with corresponding DWT components. The results revealed that the db10 and db5 from Daubechies wavelet family were respectively the best options for denoising and decomposition of Chl-a series using WT methods. Also MWTs from Biorthogonal and Reverse biorthogonal wavelet families gave a poor performance, and therefore these functions are not recommended to use in DWT denoising and decomposition of Chl-a signals. (c) 2022 COSPAR. Published by Elsevier B.V. All rights reserved.

DOI:
10.1016/j.asr.2022.01.023

ISSN:
1879-1948