Using visualization method to guide us to explore data in environmental system science

Increasing availability of environmental data, as well as the evolution of hardware and software technology, and the growth of living standard are the main reasons for the current research and development activities in the field of environmental system science. In particular, with the establishment of an environmental database, vast data sets were collected together, and usually characterized by quite high dimensions. However, how to effectively and efficiently detect trends, correlations, and anomalies from these data is still problematic. In this paper, we attempted to utilize value and relation display, a newly visual exploration technology to explore data in environmental system science. Firstly, the visual display of environmental data was implemented after data converting and filtering; and then the closely related factors were extracted by setting interesting dimension and different thresholds; in addition, the associations of risk factors were further detected by using rainfall mode of value and relation display; finally, the results were verified by correlated coefficients that generated from the scatter-plots of related dimensions. The results indicated that. visual exploration is a viable approach for rapidly and effectively detecting the hidden clues from massive data in environmental system science, especially in identifying environmental risk factors from lots of variables of environmental data. Meanwhile, the results also suggested that the development of a visual exploration analytical tool, in field of environmental system science, is a challenging, but necessary work.