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The GLaSS Project

diagram of GLaSS training

Monitoring of water quality of inland waters is important in every days life, for drinking water, transport, recreation, agriculture (including drinking water for cattle and or irrigation) and for ecology. Water samples provide detailed information, but are limited in time and space. Earth Observation (EO) can provide a great spatial overview, which is very useful for ecologists and water mangers. The high spatial resolution of Sentinel-2 and the high overpass frequency of Sentinel-3, combined with their high locational accuracy, will provide unprecedented monitoring capabilities for inland waters.

The EU collaborative project Global Lakes Sentinel Services developed a a core system to ingest and process Sentinel data of the lakes of interest. Algorithm tests have been performed and many tools were developed to work with the data. Global lakes use cases demonstrate what can be done with the new Sentinel and other EO data with regard to monitoring, trend analysis and classification such as for the Water Framework Directive.

Training materials

The GLaSS training material (10 lesson) builds on the global lakes use cases of GLaSS. It allows students (((Bsc), Msc, PhD) and professionals in fields as aquatic ecology, environmental technology, remote sensing and GIS to learn about the possibilities of optical remote sensing of water quality, by using the Sentinel-2 and Sentinel-3 satellites and Landsat 8.
 

Sentinel 2 satellite
Lesson 1: EO data handling

The Sentinel 2 and 3 data handling session introduces the spatial, temporal, spectral and format specifications of the European multispectral high resolution sensors Sentinel 2 and 3 of the Copernicus programme as well as for Landsat operated by USGS. The lesson provides information about access mechanisms and image importing software solutions, all demonstrated with exercises on selected test data sets in order to learn how to select and handle satellite data for water quality monitoring purposes.

Suitable for university students or continued professional development training (beginner level).
Screenshot from the lesson
Lesson 2: Tools for GLaSS data analysis

Lesson designed to familiarize EO data users with the tools developed for the GLaSS project that are available in BEAM/SNAP. These tools are focused on image classification and statistical analysis of data. The training material is prepared for the understanding of the optical water tool (GLaSS Deliverable 3.3, 2014), and the image classification method (Magic Wand and Prediction tool, (GLaSS Deliverable 3.6, 2014) included currently in BEAM 5, and that will be transfer into SNAP in the short term.

Suitable for university students or continued professional development training (beginner level).
Lesson 3: Eutrophic lakes

There is a world-wide need to monitor eutrophication and algal blooms. Earth observation give good coverage both in spatial and temporal scale for evaluation of in-water constituents in the water bodies. The lessons shows how to analyse the spatial variability in algal concentrations in Lake Peipsi, Estonia, using MERIS satellite data. This includes some basic handling of the image, atmospheric correction, application of a concentration-retrieval algorithm and finally validation of the results with in situ measurements.

Suitable for university students or continued professional development training (beginner level).
Lesson 4. Assessing trophic status tendency from 10-years observation from MERIS

Deep clear lakes are less vulnerable to eutrophication than small shallow lakes, but a continuous input of nutrients can lead to increasing eutrophication. This lesson shows how we can use satellite data to assess the trend of trophic level in Lake Tanganyika, the third largest lake in the world by volume, and one of the richest freshwater ecosystems supplying fish to one million people living around the lake.

Suitable for university students or continued professional development training (beginner level).
Lesson 5. Phytoplankton phenology in deep clear lakes

Phytoplankton are at the base of aquatic food webs, so their biomass is coupled to all upper trophic levels. However, phytoplankton biomass is sensitive to environmental change, with shifts in the seasonality of blooms (phenology). This lesson covers how satellite data allow phytoplankton phenology investigations for Lake Constance.";

Suitable for university students or continued professional development training (intermediate level).
Lesson 6. Shallow turbid lakes

In shallow lakes waves can easily mix this bottom material up into the water column. High turbidity can make these lakes less attractive for recreation, and for fish and birds that need to see their prey. The turbidity reduces underwater light intensity and therefore the amount of submerged vegetation. This lesson shows how to use satellite data to monitor the effect of waves and other disturbances (such as dredging).

Suitable for university students or continued professional development training (beginner level).
Lesson 7. Assessing colour of lakes influenced by glacier dynamics in the Mount Everest Region

Glacial lakes are strongly influenced by glacier dynamics that are sensitive to climate change. Increasing melting rates can increase both the number and size of glacial lakes. Melt-water increases lake volume and can make lake waters grey and very turbid. This lesson covers how we can use satellite data to classify lakes in the Sagarmatha National Park (SNP) using lake colour and turbidity derived from reflectance brightness in order to find potentially dangerous lakes with risk of outburst flood.

Suitable for university students or continued professional development training (intermediate level).
Lesson 8. Lakes with a high concentration of humic substances

High concentrations of humic substances leads to strong absorption of light in the blue and green parts of the spectrum, so that the remaining colour is yellow/red/brownish and dark. This leads to a low signal-to-noise ratio, so that small errors, for example in the atmospheric correction might lead to relatively large errors in the retrieval of water quality parameters. This lesson gives an overview of issues that limit remote sensing of water, with a focus on the effects of high absorption.

Suitable for university students or continued professional development training (beginner level).
Lesson 9. Mine tailing ponds

World wide there are hundreds of thousands of mine tailing ponds, some well maintained, others abandoned and not well documented. The first step in monitoring the risk from such ponds is to locate them all. This lesson shows how to select suitable satellite data, apply masks and designing the first step towards a tool to automatically locate mine tailing ponds in large remote areas based on Earth Observation data.

Suitable for university students or continued professional development training (intermediate level).
Lesson 10. Assessing ecological status according to the WFD

Lakes are valuable resources whose protection in the European Union is regulated by the Water Framework Directive (WFD). This forces Member States to systematically monitor all natural and artificial lakes with surface area larger than 0.5 km2. based on multiple components and parameters. Some of these can be determined by remote sensing, and this lesson shows how we can use satellite data to assess the ecological status oflakes in southern Sweden.

Suitable for university students or continued professional development training (intermediate level).
Copernicus EU 7th framework programme Water Insight Syke EOMAP Vrie Universitat Amsterdam Brockmann Consult CNR-IREA Tartu Observatorium Brockmann Consult