Grünfeld Katrin
Department of Land- and Water Resources Engineering, Royal Institute of Technology, Teknikringen 72, 100 44 Stockholm, Sweden.
Sci Total Environ. 2005 Jul 15;347(1-3):1-20. doi: 10.1016/j.scitotenv.2004.12.054.
Large-scale environmental monitoring data being sparse and collected on irregular grids, which may differ from year to year, are difficult to analyse and present. The traditional techniques from statistics and Geographic Information Systems (GIS) may not be useful given the often relatively small sample size combined with varying sampling density. In this study, the freeware visualization package XmdvTool was used for integration and exploration of monitoring data from three surveys of terrestrial mosses. Data on contents of Cu, Ni, Pb, V and Zn in mosses within an area of 300x300 km in southern Sweden, sampled in 1985 (177 samples), 1990 (156 samples) and 1995 (188 samples), were integrated and visualized using parallel coordinate and scatterplot display techniques. Several interesting findings about multi-element composition of samples, as well as changing temporal trends in the relations of five metals were made during interactive visual discovery. Visualization techniques for high-dimensional data may have limitations considering, for example, number of variables, ranges of data values, and spatial scales. Nevertheless, interactive data manipulation tools encourage the process of visual exploration, and the unique way of integrating spatial, temporal and multi-element components of moss data provided visual insights that are not possible to gain with traditional analysis tools.
大规模环境监测数据稀疏且采集于不规则网格，这些网格可能逐年不同，因而难以分析和呈现。鉴于样本量通常相对较小且采样密度各异，传统的统计技术和地理信息系统（GIS）技术可能并不适用。在本研究中，免费可视化软件包XmdvTool被用于整合和探索来自三次陆生苔藓调查的监测数据。瑞典南部一个300×300公里区域内苔藓中铜、镍、铅、钒和锌含量的数据，于1985年（177个样本）、1990年（156个样本）和1995年（188个样本）采集，采用平行坐标和散点图显示技术进行整合和可视化。在交互式视觉发现过程中，得出了关于样本多元素组成以及五种金属关系随时间变化趋势的若干有趣发现。考虑到例如变量数量、数据值范围和空间尺度等因素，高维数据的可视化技术可能存在局限性。然而，交互式数据操作工具促进了视觉探索过程，并且整合苔藓数据的空间、时间和多元素成分的独特方式提供了传统分析工具无法获得的视觉见解。
