Newsletter 2
December 2014

GLaSS newsletter banner
Dear reader,

Almost holidays, so we would like to provide you some nice reading material, for during a long trip, for in a cosy chair during a cold winter day or for when you are the only one in your office still working. Since our last newsletter, a lot of work has been done and nice results have been obtained within the GLaSS project.

We have finished all preparatory work: the core system to obtain imagery is up and running, algorithms were tested, and various tools have been developed and tested. There is a pre-classification tool, a region of interest tool, various statistical tools and a prediction data mining tool, currently available to the GLaSS team and soon also to the public. Also, some very interesting field campaigns took place. You can read more about all of this below.
 
GLaSS is ready for 2015, the year in which the first Sentinels 2 and 3 will be launched, and when we will start with our global lakes use cases. We wish you happy holidays and a great launch of 2015!

The GLaSS team

Adapted water quality algorithms
 
The aim of this study was to prepare water quality parameter retrieval algorithms for Sentinel-2 and -3 satellite data. Since these satellites are not launched yet, a large in situ database was aggregated to MERIS, Landsat 8, S2 MSI and S3 OLCI band settings. The performance of the algorithms was analysed on this database. The analysis especially focused on the different performance of algorithms in different types of inland water, ranging from clear blue to highly absorbing and/or scattering water.
 
Click here to download the report (pdf)

Optical pre-classification method
 

As found in the algorithm study, not each water quality algorithm is suitable for each lake because the constituents of lakes can show large optical variation. The purpose of the pre-classification tool is to facilitate pre-selection of an atmospheric correction and water quality retrieval algorithm for a lake with unknown optical properties. The tool (OWT-GLaSS) was developed together with Prof. Tim Moore and implemented in the BEAM software. It maps the water type of the class spectrum that matches the remotely sensed spectrum best. For GLaSS, the existing classification tool was updated to include lakes with (extremely) high TSM and CDOM concentrations.
 
Click here to download the report (pdf). The GLaSS version of the OWT tool is currently available upon request.
 
 
Field campaign in Nepal

At the time of the large snow storm in October, Erica Matte (CNR) was in Nepal to measure optical properties of different glacial lakes. Due to melting of the glaciers, the lakes are changing, providing a source of freshwater to the villages, but also forming a potential danger. Find more photos, details and initial results of the campaign in this presentation.
 
Last summer, also field campaigns were performed in lake Peipsi and lake Garda. For lake Garda, the most recent GLaSS related results were published in Sensors and Advances in Oceanography and Limnology.

Automatic ROI and time series generation tool
 
 
A tool was developed to aggregate valid lake pixels for time series production. The developments are based on existing elements already implemented in BEAM that provide functionality for definition of valid pixels based on external or predefined masks. The tool extracts/calculates basic statistics for Regions Of Interest (ROIs) provided by the user. The output of the new tool -called ROIStats- provides times series of spatial-temporal statistics for further production of time series plots in different aggregation levels. The tool runs with python and surrounds the BEAM GPT StatisticOp.
 
Click here to download the report (pdf). ROIStats is currently available upon request.
 
Data mining BEAM module
 
To be able to work with the large quantities of data that will be available from the Sentinel satellites, data mining becomes necessary. Tools for finding special features or lake types within the data set, without opening every product, could be very useful. For GLaSS a prediction tool is developed, currently supporting a supervised classification operator. This tool allows the user to select specific pixels (e.g. lake, land, cloud), train a model and let the model select similar pixels from other imagery. Additionally, a Time Series Tool was set up, to download data and statistics from a certain location (pixel wise) directly from the core system. This tool can be used to extract time series of TOA reflectances from a location of interest for further processing for retrieval water constituents.
 
 
Click here to download the report (pdf). These tools are currently available upon request, and will be incorporated in the SNAP Sentinel toolboxes.
 
Plans for 2015: global case studies


 
Starting in January and lasting over summer, GLaSS will work on global lake case studies. Using a combination of fieldwork, the results of the (atmospheric correction) algorithm tests, the new GLaSS tools and hopefully data of Sentinel-2, we will work on four types of lakes:
    1) shallow eutrophic lakes;
    2) deep clear lakes;
    3) shallow lakes with high resuspension rates;
    4) lakes with high absorption, usually due to high organic matter content.
 
The focus will be on aspects of eutrophication, light attenuation, and changes over time, but also atmospheric correction improvement.  We will investigate remote sensing products of lakes can be used for Water Framework Directive reporting.  Next to these natural lakes we will work on mine tailing ponds. 

From now on, you will find a growing amount of information about these use cases on our website: here.
To download the report on socio economic context of the globally selected lakes click here (pdf).
 
More information and contact
 
If you want to read more about the content of the project, check out our website, follow us on twitter (@glass_project) or simply reply to this email.