Improved algorithm for routine monitoring of cyanobacteria and eutrophication in inland and near-coastal waters
This short communication describes several previously undocumented processing steps, pixel flagging procedures, and improvements made to the maximum peak height (MPH) algorithm, which is aimed at the operational detection of chlorophyll a (chl-a) and cyanobacteria blooms in inland and near-coastal w...
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Published in | Remote sensing of environment Vol. 156; pp. 374 - 382 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
Elsevier Inc
01.01.2015
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Subjects | |
Online Access | Get full text |
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Summary: | This short communication describes several previously undocumented processing steps, pixel flagging procedures, and improvements made to the maximum peak height (MPH) algorithm, which is aimed at the operational detection of chlorophyll a (chl-a) and cyanobacteria blooms in inland and near-coastal waters. The improvements reduce false-positive cyanobacteria detection in oligotrophic waters; enable pixels in clear waters affected by environmental radiances (stray light) to be identified; and enhance detection of floating aquatic vegetation. Several case studies from around the globe are used to illustrate these improvements, and demonstrate new pixel flagging procedures and algorithm operation. The algorithm was validated using a large in situ dataset for chl-a from a wide range of inland water types. The MPH chl-a estimates were more stable than the fluorescence line height (FLH) and maximum chlorophyll index (MCI) values. The results demonstrate the potential for using the MPH algorithm, now released as a plug-in for the Basic ENVISAT A(ATSR) and MERIS (BEAM) processing toolbox, as a standard product for estimating chl-a (and trophic status) in inland and near-coastal waters using MERIS and the forthcoming Sentinel-3 Ocean and Land Colour Instrument.
•An improved maximum peak height (MPH) algorithm for the BEAM toolbox•Improved detection of cyanobacterial blooms in eutrophic waters•Improved detection of dense floating aquatic vegetation•Novel flagging of adjacency effect affected pixels•Validation of the MPH algorithm chlorophyll-a using a large global in situ database |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0034-4257 1879-0704 |
DOI: | 10.1016/j.rse.2014.10.010 |