Articles | Volume 10, issue 3
https://doi.org/10.5194/essd-10-1527-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-10-1527-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Diversity II water quality parameters from ENVISAT (2002–2012): a new global information source for lakes
Odermatt & Brockmann GmbH, Zurich, 8005, Switzerland
Brockmann Consult GmbH, Geesthacht, 20502, Germany
Eawag, Swiss Federal Institute of Aquatic Science and Technology, Dübendorf, 8600, Switzerland
Olaf Danne
Brockmann Consult GmbH, Geesthacht, 20502, Germany
Petra Philipson
Brockmann Geomatics Sweden AB, Kista, 164 40, Sweden
Carsten Brockmann
Brockmann Consult GmbH, Geesthacht, 20502, Germany
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- The impact of water quality on GDP growth: Evidence from around the world J. Russ et al. 10.1016/j.wasec.2022.100130
- An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data A. Vundo et al. 10.3390/rs11030279
- From Slide Rule to Big Data: How Data Science is Changing Water Science and Engineering J. Hering 10.1061/(ASCE)EE.1943-7870.0001578
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- Spatiotemporal Variability of the Lake Tana Water Quality Derived from the MODIS-Based Forel–Ule Index: The Roles of Hydrometeorological and Surface Processes N. Abegaz et al. 10.3390/atmos14020289
- Remote sensing of chlorophyll-a concentrations in coastal oceans of the Greater Bay Area in China: Algorithm development and long-term changes Y. Tong et al. 10.1016/j.jag.2022.102922
- Research of chlorophyll-a concentration inversion at different depths in Hong Kong offshore waters based on gaussian process regression J. Zhang et al. 10.1088/1755-1315/1087/1/012034
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- Using a Remote-Sensing-Based Piecewise Retrieval Algorithm to Map Chlorophyll-a Concentration in a Highland River System Y. Ma et al. 10.3390/rs14236119
- Water Optical Property of High-Altitude Lakes in the Tibetan Plateau W. Shi & M. Wang 10.1109/TGRS.2021.3065637
- Merging of the Case 2 Regional Coast Colour and Maximum-Peak Height chlorophyll-a algorithms: validation and demonstration of satellite-derived retrievals across US lakes B. Schaeffer et al. 10.1007/s10661-021-09684-w
24 citations as recorded by crossref.
- AquaSat: A Data Set to Enable Remote Sensing of Water Quality for Inland Waters M. Ross et al. 10.1029/2019WR024883
- A Review of Remote Sensing for Water Quality Retrieval: Progress and Challenges H. Yang et al. 10.3390/rs14081770
- Complementary water quality observations from high and medium resolution Sentinel sensors by aligning chlorophyll-a and turbidity algorithms M. Warren et al. 10.1016/j.rse.2021.112651
- Dive Into the Unknown: Embracing Uncertainty to Advance Aquatic Remote Sensing M. Werther & O. Burggraaff 10.34133/remotesensing.0070
- The NSERC Canadian Lake Pulse Network: A national assessment of lake health providing science for water management in a changing climate Y. Huot et al. 10.1016/j.scitotenv.2019.133668
- Analyzing short term spatial and temporal dynamics of water presence at a basin-scale in Mexico using SAR data A. López-Caloca et al. 10.1080/15481603.2020.1840106
- Seamless retrievals of chlorophyll-a from Sentinel-2 (MSI) and Sentinel-3 (OLCI) in inland and coastal waters: A machine-learning approach N. Pahlevan et al. 10.1016/j.rse.2019.111604
- Regime shifts, trends, and variability of lake productivity at a global scale L. Gilarranz et al. 10.1073/pnas.2116413119
- The impact of water quality on GDP growth: Evidence from around the world J. Russ et al. 10.1016/j.wasec.2022.100130
- An Overall Evaluation of Water Transparency in Lake Malawi from MERIS Data A. Vundo et al. 10.3390/rs11030279
- From Slide Rule to Big Data: How Data Science is Changing Water Science and Engineering J. Hering 10.1061/(ASCE)EE.1943-7870.0001578
- A new approach to quantify chlorophyll-a over inland water targets based on multi-source remote sensing data J. Wang & X. Chen 10.1016/j.scitotenv.2023.167631
- Development of an algal bloom satellite and in situ metadata hub with case studies in Canada D. Beaulne & G. Fotopoulos 10.1016/j.ecoinf.2023.102447
- A database of chlorophyll and water chemistry in freshwater lakes A. Filazzola et al. 10.1038/s41597-020-00648-2
- A generalized machine learning approach for dissolved oxygen estimation at multiple spatiotemporal scales using remote sensing H. Guo et al. 10.1016/j.envpol.2021.117734
- A Bayesian approach for remote sensing of chlorophyll-a and associated retrieval uncertainty in oligotrophic and mesotrophic lakes M. Werther et al. 10.1016/j.rse.2022.113295
- Supervised Classifications of Optical Water Types in Spanish Inland Waters M. Pereira-Sandoval et al. 10.3390/rs14215568
- Spatiotemporal Variability of the Lake Tana Water Quality Derived from the MODIS-Based Forel–Ule Index: The Roles of Hydrometeorological and Surface Processes N. Abegaz et al. 10.3390/atmos14020289
- Remote sensing of chlorophyll-a concentrations in coastal oceans of the Greater Bay Area in China: Algorithm development and long-term changes Y. Tong et al. 10.1016/j.jag.2022.102922
- Research of chlorophyll-a concentration inversion at different depths in Hong Kong offshore waters based on gaussian process regression J. Zhang et al. 10.1088/1755-1315/1087/1/012034
- A data-driven approach to flag land-affected signals in satellite derived water quality from small lakes D. Jiang et al. 10.1016/j.jag.2023.103188
- Using a Remote-Sensing-Based Piecewise Retrieval Algorithm to Map Chlorophyll-a Concentration in a Highland River System Y. Ma et al. 10.3390/rs14236119
- Water Optical Property of High-Altitude Lakes in the Tibetan Plateau W. Shi & M. Wang 10.1109/TGRS.2021.3065637
- Merging of the Case 2 Regional Coast Colour and Maximum-Peak Height chlorophyll-a algorithms: validation and demonstration of satellite-derived retrievals across US lakes B. Schaeffer et al. 10.1007/s10661-021-09684-w
Latest update: 03 May 2024
Short summary
The Diversity II inland water database consists of remotely sensed water quality information for more than 300 lakes in the whole world. It was derived from optical and thermal imagery acquired by the ESA ENVISAT satellite between 2002 and 2012. The database consists of spatially resolved monthly, yearly and 9-year averages for 10 geophysical parameters. Its practical usage is demonstrated by means of several case studies on lake-specific processes and regime shifts.
The Diversity II inland water database consists of remotely sensed water quality information for...
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