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.

面对重要的决策时，我们试图将决策基于理性框架，该框架通常包括多个决策标准。多标准决策分析（MCDA）将近20年前首次引入地理信息系统（GIS）领域。总部位于GIS的MCDA现在在各个应用领域进行，包括环境，运输和城市/区域计划，废物管理以及水文学，农业和林业。 矛盾的是，除了可视化地图上的评估结果外，基于GIS的MCDA中的位置特征几乎没有使用。例如，在空间上明确的决策标准也没有公认的框架，也没有一种系统的方法来将空间变化纳入标准权重或决策规则。 MCDA计算通常基于非空间标准，不包括空间明确的参数或决策者的偏好。 拟议的研究旨在缩小这一概念上的差距，并证明在选定的应用程序中对多标准决策的空间明确方法的实用性。我的团队将将GeoVisalization和MCDA工具与空间统计数据相结合，并开发全面的以地图为中心的方法，该方法可以通过在社区服务计划和环境评估等领域的有效决策任务来指导用户。我们还将研究空间变化对决策标准，标准标准化和标准加权对基于GIS的MCDA结果的影响，并为时空MCDA开发框架。 这项研究有助于地理学知识体系。它有可能使基于GIS的MCDA更有效，并解决空间决策支持中的概念问题，这可能会阻碍其更广泛的接受。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，而决策具有地理空间组成部分。