期刊
REMOTE SENSING OF ENVIRONMENT
卷 212, 期 -, 页码 273-287出版社
ELSEVIER SCIENCE INC
DOI: 10.1016/j.rse.2018.02.043
关键词
Chlorophyll-a (chl-a); Earth Observation (EO); Baltic Sea; Coastal waters; Status assessment; Water body; Water Framework Directive (WFD); FUB
资金
- Finnish Environment Institute
Earth Observation (EO) offers spatially and temporally unique data for generating information required under various environmental regulations for assessing the status of surface waters. These requirements, which are laid down in, for example, European Union directives and the Clean Water Act in the United States, share two core elements with respect to status assessments: 1) the status assessment is done using discrete classes, typically for water bodies, sub-areas or critical sites representative for certain area of interest, and 2) phytoplankton chlorophyll a (chl-a) is one of the main variables considered. We analysed the benefits of using chl-a concentrations derived from EO data for the status assessments specified in the EU Water Framework Directive (WFD). Our study focused especially on EO observations' ability to capture extreme and transient events (such as instances of cyanobacteria blooms) more frequently than the monitoring-station data conventionally employs. The accuracy of EO-based chl-a assessment was studied for, in all, 129 Finnish water bodies in the area of the Baltic Sea, in Northern Europe. Natural conditions in this coastal area particularly its multitude of small bays, numerous estuaries, and mosaic of islands impose exceptionally strict requirements for an EO instrument's spatial resolution. The analysis revealed that an instrument with a 300 m resolution, such as the MEdium Resolution Imaging Spectrometer (MERIS) or Ocean and Land Colour Instrument (OLCI), can be used to estimate the water quality in 62% of these water bodies. Processing of MERIS data into chl-a concentrations by means of a FUB inversion model demonstrated good accuracy relative to monitoring stations' measurements for the open-water season in 2003-2011. This extensive dataset showed a 23% difference in modal values between EO- and station sampling -based chl-a concentrations. The bias in EO chl-a estimates was found to increase with low Secchi disk depth, elevated turbidity, and the presence of intensive phytoplankton blooms. The monitoring-station and EO data showed similar distributions of chl-a observations for a given day and location, a finding that supports the comprehensive use of EO-derived chl-a concentrations in assessment. For determination of a water body's status, the EO data required but also allowed for statistical analysis that differs from what has typically been utilised with sparse measurements from monitoring-station data. The geometric mean or the mode of the EO observations was found to represent the main bulk of the chl-a concentrations well statistically. In contrast, the arithmetic mean of EO observations yields chl-a concentrations that are roughly 1.1-1.6 mu g/I higher and hence can lead to over-estimation in the associated status assessment. This paper also presents a new approach applicable for evaluating the validity of EO-based algorithms for any coastal water area requiring assessment. With this quality-grade (QG) method, the EO chl-a estimation accuracy is rated in terms of three grades, with water bodies taken as the evaluation units. For this, the method utilises statistical differences between EO and station-sampling chl-a concentrations and applies background information on optical properties obtained from measurements at routine-monitoring stations. The QG method showed the EO-based chl-a accuracy to suffice for assessing the status of 65% of the coastal water bodies examined. At concentrations representing the threshold for the target of good status under the WFD, the EO approach produced 0. 6 mu g/I higher chl-a values than the stations' sampling did. The MERIS results point to clear benefits of using OLCI-based status assessment throughout the Sentinel-3 era.
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