HydroQual: Visual analysis of river water quality

Pierre Accorsi 1, 2 Arnaud Sallaberry 2, 3 Nathalie Lalande 4 Sandra Bringay 2, 3 Florence Le Ber 5 Pascal Poncelet 2, 1 Mickaël Fabrègue 5, 4 Flavie Cernesson 4 Agnès Braud 5 Maguelonne Teisseire 4, 2
1 UM - Université de Montpellier
2 ADVANSE - ADVanced Analytics for data SciencE
LIRMM - Laboratoire d'Informatique de Robotique et de Microélectronique de Montpellier
3 UM3 - Université Paul-Valéry - Montpellier 3
4 UMR TETIS - Territoires, Environnement, Télédétection et Information Spatiale
5 ICube - Laboratoire des sciences de l'ingénieur, de l'informatique et de l'imagerie
Abstract : Economic development based on industrialization, intensive agriculture expansion and population growth places greater pressure on water resources through increased water abstraction and water quality degradation [40]. River pollution is now a visible issue, with emblematic ecological disasters following industrial accidents such as the pollution of the Rhine river in 1986 [31]. River water quality is a pivotal public health and environmental issue that has prompted governments to plan initiatives for preserving or restoring aquatic ecosystems and water resources [56]. Water managers require operational tools to help interpret the complex range of information available on river water quality functioning. Tools based on statistical approaches often fail to resolve some tasks due to the sparse nature of the data. Here we describe HydroQual, a tool to facilitate visual analysis of river water quality. This tool combines spatiotem-poral data mining and visualization techniques to perform tasks defined by water experts. We illustrate the approach with a case study that illustrates how the tool helps experts analyze water quality. We also perform a qualitative evaluation with these experts.
Keywords : Visual analytics Spatiotemporal data mining and visualization Water quality
Type de document :
Communication dans un congrès
VAST: Visual Analytics Science and Technology, Nov 2014, Paris, France. IEEE Conference on Visual Analytics Science and Technology, pp.123-132, 2014, 〈http://ieeevis.org/year/2014/info/call-participation/vast-papers〉. 〈10.1109/VAST.2014.7042488〉
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Pierre Accorsi, Arnaud Sallaberry, Nathalie Lalande, Sandra Bringay, Florence Le Ber, et al.. HydroQual: Visual analysis of river water quality. VAST: Visual Analytics Science and Technology, Nov 2014, Paris, France. IEEE Conference on Visual Analytics Science and Technology, pp.123-132, 2014, 〈http://ieeevis.org/year/2014/info/call-participation/vast-papers〉. 〈10.1109/VAST.2014.7042488〉. 〈lirmm-01275383〉

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