A Wavelet-Enhanced Inversion Method for Water Quality Retrieval From High Spectral Resolution Data for Complex Waters
| Autor: | Els Knaeps, Maarten Jansen, Okke Batelaan, Eva Ampe, Erin L. Hestir, Dries Raymaekers |
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| Přispěvatelé: | Hydrology and Hydraulic Engineering |
| Rok vydání: | 2015 |
| Předmět: |
water quality retrieval
high spectral resolution data Inverse transform sampling Inversion (meteorology) wavelet-enhanced inversion method Finite element method Uncorrelated Spectral line Wavelet complex waters General Earth and Planetary Sciences Environmental science Electrical and Electronic Engineering Spectral resolution Zenith Remote sensing |
| Zdroj: | IEEE Transactions on Geoscience and Remote Sensing. 53:869-882 |
| ISSN: | 1558-0644 0196-2892 |
| DOI: | 10.1109/tgrs.2014.2330251 |
| Popis: | Optical remote sensing in complex waters is challenging because the optically active constituents may vary independently and have a combined and interacting influence on the remote sensing signal. Additionally, the remote sensing signal is influenced by noise and spectral contamination by confounding factors, resulting in ill-posedness and ill-conditionedness in the inversion of the model. There is a need for inversion methods that are less sensitive to these changing or shifting spectral features. We proposeWaveIN, a wavelet-enhanced inversion method, specifically designed for complex waters. It integrates wavelettransformed high-spectral resolution reflectance spectra in a multiscale analysis tool. Wavelets are less sensitive to a bias in the spectra and can avoid the changing or shifting spectral features by selecting specific wavelet scales. This paper applied WaveIN to simulated reflectance spectra for the Scheldt River. We tested different scenarios, where we added specificnoise or confounding factors, specifically uncorrelated noise, contamination due to spectral mixing, a different sun zenith angle, and specific inherent optical property (SIOP) variation.WaveIN improved the constituent estimation in case of the reference scenario, contamination due to spectral mixing, and a different sun zenith angle. WaveIN could reduce, but not overcome, the influence of variation in SIOPs. Furthermore, it is sensitive to wavelet edge effects. In addition, it still requires in situ data for the wavelet scale selection. Future research should therefore improve the wavelet scale selection. Index Terms--Chlorophyll-a, continuous wavelet transforms, dissolved organic matter, hyperspectral remote sensing, multiscale, optically complex waters, suspended matter. |
| Databáze: | OpenAIRE |
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