Developing spatially explicit methods to enhance geovisual analytics and decision support

开发空间显式方法以增强地理视觉分析和决策支持

• 批准号: 288140-2011
• 负责人: Rinner, Claus
• 金额: $ 1.38万
• 依托单位: Ryerson University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=571347
• 关键词: Developing; spatially; explicit; methods; enhance

When faced with important decisions, we try to base our decision-making on a rational framework which often includes multiple decision criteria. Multi-criteria decision analysis (MCDA) was first introduced to the field of Geographic Information Systems (GIS) nearly 20 years ago. GIS-based MCDA is now conducted in various fields of application, including environmental, transportation, and urban/regional planning, in waste management, as well as in hydrology, agriculture, and forestry. Paradoxically, there has been little use of the locational characteristics in GIS-based MCDA besides the visualization of evaluation results on maps. For example, there is neither a generally accepted framework for spatially explicit decision criteria nor a systematic approach to incorporating spatial variations in criterion weights or decision rules. MCDA calculations are typically based on non-spatial criteria and do not include spatially explicit parameters or decision-maker preferences. The proposed research aims at closing this conceptual gap and demonstrating the utility of spatially explicit methods for multi-criteria decision-making in selected applications. My team will integrate geovisualization and MCDA tools with spatial statistics and develop a comprehensive map-centred methodology that guides users through valid sequences of decision-making tasks in fields such as community service planning and environmental assessments. We will also study the effects of spatial variations in decision criteria, criterion standardization, and criterion weighting on GIS-based MCDA results, and develop a framework for spatio-temporal MCDA. This research contributes to the body of knowledge in Geomatics. It has the potential to make GIS-based MCDA more effective and addresses conceptual issues in spatial decision support that may have hampered its broader acceptance. Ultimately, this research program will improve strategic decision-making by government, non-profit organizations, and businesses, where decisions have a geospatial component.

当面临重要决策时，我们尝试将决策建立在一个理性框架之上，该框架通常包含多个决策标准。多标准决策分析 (MCDA) 于近 20 年前首次引入地理信息系统 (GIS) 领域。基于 GIS 的 MCDA 现在已应用于各个应用领域，包括环境、交通、城市/区域规划、废物管理以及水文、农业和林业。 矛盾的是，除了在地图上可视化评估结果外，基于 GIS 的 MCDA 很少使用位置特征。例如，既没有普遍接受的空间明确决策标准框架，也没有将空间变化纳入标准权重或决策规则的系统方法。 MCDA 计算通常基于非空间标准，并且不包括空间明确的参数或决策者偏好。 拟议的研究旨在缩小这一概念差距，并证明空间显式方法在选定应用中进行多标准决策的实用性。我的团队将把地理可视化和 MCDA 工具与空间统计相结合，并开发一种以地图为中心的综合方法，指导用户完成社区服务规划和环境评估等领域的有效决策任务序列。我们还将研究决策标准、标准标准化和标准权重的空间变化对基于 GIS 的 MCDA 结果的影响，并开发时空 MCDA 框架。 这项研究有助于丰富测绘学知识体系。它有可能使基于 GIS 的 MCDA 更加有效，并解决空间决策支持中可能阻碍其更广泛接受的概念问题。最终，该研究计划将改善政府、非营利组织和企业的战略决策，这些决策都包含地理空间成分。