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Graphical excellence in environmental impact statements: applying data visualisation principles to environmental impact assessments

机译:环境影响陈述的图形卓越:将数据可视化原理应用于环境影响评估

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摘要

Graphical Excellence in Environmental Impact Statementsudapplying data visualisation principles to environmental impact assessmentsudPlanning and development involves balancing potentially conflicting goals. Developmentudcontrol systems attempt to optimise the trade-offs between ecology, economy and society.udEnvironmental impact assessment (EIA) is one o f the tools used to improve the way inudwhich decisions to develop are made. E IA is now well established in national andudinternational legislation and declarations, and in policy and practice. As implemented inudIreland, E IA is carried out by statutory planning and licensing authorities, with theudassessment based on the information provided in Environmental Impact Statements (EIS).udThere is scope for improvement in the effectiveness o f communication o f graphic, text andudtabular information, which would benefit the assessment and decision-making process.udData visualisation theory is considered in the context o f the prediction o f environmentaludimpacts, and the following suggestions are made for best-practice in graphical presentationudin EISs:udUse horizontally-oriented histograms to illustrate impact significance.udCompile the predicted impacts in ‘small multiples’ o f histograms.udUse sequential colour schemes.udAvoid tones that cannot be differentiated by colour blind viewers.udUse double-ended colour schemes to encode the adverse-to-beneficial data range.udUse techniques such as ‘TableLens’ to aggregate and summarise the data.udIllustrate additional characteristics, such as uncertainty, using bullet graphs.
机译:环境影响报告书中的图形卓越表现将数据可视化原理应用于环境影响评估 ud计划和开发涉及平衡潜在冲突的目标。开发控制系统试图优化生态,经济和社会之间的权衡。环境影响评估(EIA)是用于改进制定决策方式的工具之一。现在,EI IA在国家和/或国际法规和宣言以及政策和实践中均已确立。正如在 udreland中实施的那样,EIA是由法定规划和许可机构根据《环境影响声明书〗中提供的信息,“评估”进行,,, ud数据可视化理论是在预测环境 ud影响的背景下考虑的,并为图形表示 udin EIS的最佳实践提出了以下建议: ud使用水平方向的直方图来说明影响的重要性。 ud以直方图的“小倍数”编译预测的影响。 ud使用顺序配色方案。 ud请避免色盲观看者无法区分的色调。 ud使用双端配色方案编码有害数据到有益数据范围。 ud使用“ TableLens”之类的技术来汇总和汇总数据。 ud说明其他数据子弹图等特性,例如不确定性。

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    Garvey Daniel.;

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  • 年度 2008
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  • 正文语种 en
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