Visualisation in environmental sciences

In recent years, the amount of environmental data that is measured, collected and analysed has risen in staggering amounts. The reason for this is largely the desire and need of both science and politics to better understand the reasons, effects and possible consequences of climate change. This includes topics as diverse as the behaviour of groundwater regimes in arid regions, the migration of animal species, or the wide range of ecosystem services. In addition, this trend is reinforced by observation methods getting more and more refined: satellites can measure data in the sub-metre range, eddy covariance systems analyse high-frequency atmospheric data such as wind, heat or gas fluxes and weather surveillance radar creates high-resolution data of precipitation parameters every few minutes, to name just a few examples. Vital insight is gained from correlating such data or simulating certain processes based on the collected information. Examples range from devising water management schemes for arid and humid regions, feasible plans for the transition from fossil to renewable energy sources, finding adequate storage sites for nuclear waste, or the effects of chemicals discharged into the atmosphere by industry or into the water in the form of agricultural fertilisers. Developing effective visualisation techniques is the key to improving the understanding of complex data sets and communicate findings to the public in general and stakeholders in particular. This process requires collaboration of researchers from environmental sciences (geology, meteorology, hydrology, etc.) and computer scientists with experience in handling and visualising large amounts of heterogenous data. While this has previously worked well in other domains, e.g. for the visualisation of complex medical data (Preim and Botha 2013; Deserno 2011), in environmental sciences visualisation is often viewed as an addendum. Once the field work and simulations are done, results are visualised to show the results to other interested parties. The possibilities for visualisation in assisting scientists in their research for verification, integration and analysis of the data are often neglected outside of the established domains of timeseries analysis or cartographic data in geographic information systems. In addition, visualisation is an excellent means of communication between researchers from different disciplines and facilitating support for basic workflows such as model creation. This thematic issue includes expanded and new articles based on presentations of the workshop ‘‘Visualisation in Environmental Sciences’’, which took place as a co-located event of EuroVis 2013, the EuroGraphics conference on visualisation. Contributions included applications from the domains of biodiversity (Slingsby and van Loon 2013), migration ecology (Kolzsch et al. 2013), ecosystem restoration (Eligehausen et al. 2013), flood analysis (Schlegel et al. 2013), 3D geological modelling (Lidal et al. 2013) and urban climate simulation (Rober et al. 2013). The intent is to give readers a notion about the multitude of possibilities for visualisation in the scope of environmental sciences. K. Rink (&) O. Kolditz Department of Environmental Informatics, Helmholtz Centre for Environmental Research, Leipzig, Germany e-mail: karsten.rink@ufz.de