Applications for Monitoring Programmes

Historical satellite records may be used to contextualise background monitoring to identify the potential for cyanobacteria occurrence problems in waterbodies and the typical timing, location and extent of the bloom at local and regional scales. Near-real-time satellite records may be used for cyanobacteria monitoring to quantify abundance in recreational and drinking waterbodies.

Retrospective Assessments

Satellite remote sensing may be used to quantify the spatial extent of the surface area covered by a cyanobacterial bloom (Urquhart et al., 2017). Relevant statistical tests and time-series analyses may be used to identify trends in satellite-derived extent of surface area covered by cyanobacteria. Trend analysis for surface area extent may be subdivided into categorical thresholds desired by the user, based on cyanobacteria concentration or chlorophyll-д, to help water managers effectively distribute resources to monitor and manage waters. Scalable assessments may permit the development of management objectives over different temporal periods and spatial scales. Improved multiscale assessment capability is desirable so that comparisons of condition may occur across local, regional and national scales to more adequately evaluate regional water quality, biological integrity and response to management actions.

The frequency of observed cyanobacteria (Figure 11.4) may be calculated as the fraction of total observations for which cyanobacteria biomass exceeded a specified threshold, for example, a Vigilance or Alert Level (sections 5.1.2 and 5.2.3; Clark et al., 2017). Values are summed for each pixel and divided by the total number of valid observations (i.e., those not flagged for clouds, land, mixed land water and lack of data). Finally, the magnitude of cyanobacteria biomass may be calculated based on the spatiotemporal mean of the biomass for a particular period of time such as a season or year. The spatial extent, temporal frequency and magnitude can all be used to rank waters in order of importance to prioritise management resources (Mishra et al, 2019).

A demonstration of how ESA’s Sentinel-3 OLCI satellite data can be used for a quantitative retrospective assessment across lakes near Dallas, Texas, USA

Figure 11.4 A demonstration of how ESA’s Sentinel-3 OLCI satellite data can be used for a quantitative retrospective assessment across lakes near Dallas, Texas, USA. Here, the frequency of detected cyanobacteria biomass is calculated as the fraction of total observations throughout 2017. A value of I indicates cyanobacteria had a 100% frequency of occurrence in valid observations through 2017, and a value of 0 indicates cyanobacteria were not detected.

Near-Real-Time Monitoring

Satellites provide a constant birds-eye view of the Earth’s surface and can be used to identify changes in the environment across geopolitical boundaries by providing updated images the same day the data is acquired. This information may be used to identify events and locations during days of data acquisition, or at weekly, monthly and seasonal intervals. Management decisions such as updating recreational beach notices or modifying drinking-water treatment methods may benefit from access to near-real-time satellite-derived occurrence information.

Satellite Support of Monitoring Programmes

The presence of cyanobacteria or chlorophyll-д biomass estimated from satellites may be used as a first-line indicator of potential ecological and human health risk that can be used to prioritise waterbodies requiring further evaluation for parameters such as visual inspection, laboratory assessment of cyanobacteria taxon composition and biomass, and assessment of cyanotoxin concentrations. Satellites have the potential to support monitoring efforts across broad geographic extents and provide improved temporal and spatial coverage at larger scales. When coupled with field-based observations, satellite data provide a more comprehensive tool to monitor, assess and detect changes in the environment. The science required for a more precise interpretation of satellite remote sensing of water quality such as in-water algorithms, atmospheric corrections and land adjacency effects will continue to mature over the coming decades. Significant progress has already been demonstrated in deriving cyanobacteria and chlorophyll-д data from inland and estuarine waters using satellite sensors.

More information on satellite remote sensing, including training webinars, and access to a community of practice are available from the Group on Earth Observations AquaWatch website (

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