GLaSS flyer - version February 2016
GLaSS policy brief - version February 2016
GLaSS-S3VT introduction presentation of the GLaSS-S3VT team
Data, algorithms and tools
Deliverable 3.1: Initial test datasets
Deliverable 3.2: Atmospheric correction harmonisation
Deliverable 3.3: Optical pre-classification method
Deliverable 3.4: Adapted water quality algorithms
Deliverable 3.5 Automatic ROI & time series generation tool
Deliverable 3.6 Data mining BEAM module
The OWT tool (D3.3) and the prediction tool (D3.6) are available as plugin in the BEAM software
Validation
Deliverable 4.2 Validation report for nearby lakes
Deliverable 4.3 Validation report for European lakes (HYPE model)
Global Lakes case studies
Deliverable 5.1 Selection of case study lakes based on Socio Economic context;
Deliverable 5.2 Shallow lakes with high eutrophication and potentially toxic algae;
Deliverable 5.3 Deep clear lakes with increasing eutrophication;
Deliverable 5.4 Shallow lakes with low transparency due to sediment resuspension;
Deliverable 5.5 Boreal lakes case study results;
Deliverable 5.6 Mine tailing ponds;
Deliverable 5.7 Water Framework Directive reporting case studies;
The core system is accessible via this url
The in situ data of GLaSS is (in the process of being) submitted to LIMNADES
The simulated data (D3.1) is available on request.
Alikas, K., Kangro, K. Randoja, R. Philipson, P., Asuküll, E., Pisek, J., Reinart, A., 2015. Satellite based products for monitoring optically complex inland waters in support of EU Water Framework Directive. International Journal of Remote Sensing, 36(17), 4446 - 4468.
Alikas, Krista; Kratzer, Susanne; Reinart, Anu; Kauer, Tuuli; Paavel, Birgot., 2015. Robust remote sensing algorithms to derive the diffuse attenuation coefficient for lakes and coastal waters. Limnology and Oceanography: Methods, 13, 402 - 415.
Broszeit, A. (2015): Assessing long-term inland water quality using satellite imagery: A feasibility and validation study of different lake types. Master thesis Julius-Maximilian University Würzburg
Di Nicolantonio W., Cazzaniga I., Cacciari A., Bresciani M., Giardino C., 2015. Synergy of multi-spectral and multi-sensors satellite observations to evaluate desert aerosol transport and impact of dust deposition on inland waters: study case of Lake Garda. Journal of Applied Remote Sensing 095980-1 Vol. 9.
Giardino, C., Bresciani, M.,Stroppiana, D., Oggioni, A., Morabito, G. (2014). Optical remote sensing of lakes: an overview on Lake Maggiore. Journal of Limnology 73(s1): 201-214. DOI: 10.4081/jlimnol.2014.817
Giardino, C., Bresciani, M., Cazzaniga, I., Schenk, K., Rieger, P., Braga, F., Matta, E., Brando, V.E., 2014. Evaluation of Multi-Resolution Satellite Sensors for Assessing Water Quality and Bottom Depth of Lake Garda. Sensors 14, 24116-24131; Doi:10.3390/s141224116
Lenstra W.K., Hahn-Woernle L., Matta E., Bresciani M., Giardino C., Salmaso N., Musanti M., Fila G., Uittenbogaard R., Genseberger M., van der Woerd H.J. & Dijkstra H.A., 2014. Diurnal variation of turbulence-related quantities in Lake Garda, Advances in Oceanography and Limnology, 5:2, 184-203, DOI: 10.1080/19475721.2014.971870.
Matta E., Bresciani M., Giardino C., Boggero A., Use of satellite and in-situ reflectance data for lake water color characterization in the Everest Himalayan Region. Submitted in July 2015 to ‘Mountain research and Development’.
Alikas, K., Kangro, K., Randoja, R., Asuküll, E., Reinart, A. 2014. Satelliidi-info kasutamise võimalused veekogude seisundi määramiseks Eesti suurtes järvedes. Anne Aan, Kirke Narusk (Toim.). Kaugseire Eestis 2014 (59 - 68).Keskkonnaagentuur (In Estonian) (Popular science article)
Marieke A. Eleveld, Ana B. Ruescas, Annelies Hommersom, Timothy S. Moore, Steef W. M. Peters, and Carsten Brockmann. An Optical Classification Tool for Global Lake Waters. Remote Sens. 2017, 9, 420; doi:10.3390/rs9050420
GLaSS Newsletter 2, December 2014
GLaSS Newsletter 4, December 2015
GLaSS Newsletter 5, April 2016
Presentation Evaluating the Feasibility of Systematic Inland Water Quality - Monitoring with Satellite Remote Sensing by Advisory Board member Prof. Dekker