Cluster analysis of hyperspectral optical data for discriminating phytoplankton pigment assemblages in the open ocean
16 pages, 13 figures, 2 tables Optical measurements including remote sensing provide a potential tool for the identification of dominant phytoplankton groups and for monitoring spatial and temporal changes in biodiversity in the upper ocean. We examine the application of an unsupervised hierarchical...
| Published in: | Remote Sensing of Environment |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
Elsevier
2011
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| Subjects: | |
| Online Access: | http://hdl.handle.net/10261/56495 https://doi.org/10.1016/j.rse.2011.05.014 |
| Summary: | 16 pages, 13 figures, 2 tables Optical measurements including remote sensing provide a potential tool for the identification of dominant phytoplankton groups and for monitoring spatial and temporal changes in biodiversity in the upper ocean. We examine the application of an unsupervised hierarchical cluster analysis to phytoplankton pigment data and spectra of the absorption coefficient and remote-sensing reflectance with the aim of discriminating different phytoplankton assemblages in open ocean environments under non-bloom conditions. This technique is applied to an optical and phytoplankton pigment data set collected at several stations within the eastern Atlantic Ocean, where the surface total chlorophyll-a concentration (TChla) ranged from 0.11 to 0.62 mg m− 3. Stations were selected on the basis of significant differences in the ratios of the two most dominant accessory pigments relative to TChla, as derived from High Performance Liquid Chromatography (HPLC) analysis. The performance of cluster analysis applied to absorption and remote-sensing spectra is evaluated by comparisons with the cluster partitioning of the corresponding HPLC pigment data, in which the pigment-based clusters serve as a reference for identifying different phytoplankton assemblages. Two indices, cophenetic and Rand, are utilized in these comparisons to quantify the degree of similarity between pigment-based and optical-based clusters. The use of spectral derivative analysis for the optical data was also evaluated, and sensitivity tests were conducted to determine the influence of parameters used in these calculations (spectral range, smoothing filter size, and band separation). The results of our analyses indicate that the second derivative calculated from hyperspectral (1 nm resolution) data of the phytoplankton absorption coefficient, aph(λ), and remote-sensing reflectance, Rrs(λ), provide better discrimination of phytoplankton pigment assemblages than traditional multispectral band-ratios or ordinary (non-differentiated) hyperspectral data of absorption and remote-sensing reflectance. The most useful spectral region for this discrimination extends generally from wavelengths of about 425-435 nm to wavelengths within the 495–540 nm range, although in the case of phytoplankton absorption data a broader spectral region can also provide satisfactory results This study was supported by the NASA Biodiversity and Ecological Forecasting Program (Grant NNX09AK17G), the NASA Ocean Biology and Biogeochemistry Program (Grant NNG04GO02G), and the Spanish National Research Council CSIC (projects ANERIS PIF08-015 and HIDRA 2006-301102). Part of this study was performed during a visit of E. T. at Scripps Institution of Oceanography supported also by CSIC (ProgramI3P). The Alfred Wegener Institute for Polar and Marine Research (Bremerhaven, Germany) kindly made it possible for us to participate in the cruise in the eastern Atlantic Peer reviewed |
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