Location, Time, and Scale in GIS-Based Multi-Criteria Decision Analysis - Advancing the Agenda

基于GIS的多标准决策分析（MCDA）用于环境、交通、土地利用规划、废物管理、水文、农业和林业等领域的决策。然而，有关地理信息系统-军事和民防资源的空间，时间和规模组成部分的重要概念问题仍然在很大程度上没有得到回答。拟议的研究计划旨在扩大我目前在这一领域的NSERC资助的研究。 地理信息系统-军事和民防资源分析中输入数据的位置部分往往没有得到充分利用。在最近的工作中，一些研究人员已经尝试了空间显式MCDA技术，如局部加权线性组合（LWLC）。LWLC技术通过局部权重表示标准结果的局部变化。因此，LWLC创建了一个更分散的MCDA分数模式，突出了地方差异，而不是一般的空间模式。这一方法的效用仍有待在实际应用中证明，这是本提案的一个目标。 地理信息系统军事和民防资源评估的时间部分是指一段时间内的重复评估。由于军事和民防资源评估分数没有单位，不能直接比较，因此在使用综合指数跟踪社会经济或环境系统长期业绩时会出现问题。在最近NSERC资助的工作中，我提出了“联合标准化”，以使在不同时间点计算的分数具有可比性。类似于全局与局部加权，联合标准化可以与全局（在时间上）方法相关联，而个体（特定时间）标准化表示局部方法。因此，单独的标准化产生更大的变化的结果，而联合标准化产生一般的时间模式的信息。这两种方法将在本研究中进一步研究，并探讨其在实际应用中的有用性。 最后，GIS-MCDA中的尺度部分涉及空间和时间要素，尽管本研究的重点是空间尺度。比例尺与地理空间分析中著名的可修改面积单位问题（MAUP）有关。MAUP的尺度效应和分区效应都会影响GIS-MCDA的结果。在不同的分析尺度和使用不同的分区配置进行地理信息系统-军事和民防资源案例研究，将有助于更好地了解这些影响。拟议的研究旨在为决策者提供严格的指导方针，使分析规模与行动规模保持一致。 总体而言，拟议的研究有助于探索影响GIS-MCDA结果有效性的基本问题。将探讨这些影响的范围，并制定处理地理信息系统军事和民防资源的地点、时间和规模组成部分的最佳做法。最终，这项研究计划的目的是开发一个概念框架的空间和时间明确的，规模特定的，决策支持。

GIS-based multi-criteria decision analysis (MCDA) is used for decision-making in fields such as environmental, transportation, and landuse planning, waste management, hydrology, agriculture, and forestry. Yet important conceptual questions regarding the spatial, temporal, and scale components of GIS-MCDA remain largely unanswered. The proposed research program aims to expand my current NSERC-funded research in this field. The location component of input data in GIS-MCDA is often under-used. In recent work, some researchers have experimented with spatially explicit MCDA techniques such as the locally weighted linear combination (LWLC). The LWLC technique represents local variations in criterion outcomes through local weights. As a result, LWLC creates a more dispersed pattern of MCDA scores, which highlights local differences rather than general spatial pattern. The usefulness of this approach remains to be demonstrated in practical applications, which is one objective of this proposal. The time component in GIS-MCDA refers to repeated evaluations over time. Since MCDA scores are unitless and not directly comparable, issues arise when composite indices are used for tracking socio-economic or environmental system performance over time. In recent NSERC-funded work, I proposed "joint standardization" to make scores comparable when they are calculated for different points in time. Similar to global vs. local weighting, joint standardization can be associated with a global (in time) approach, while individual (time-specific) standardization represents a local approach. Consequently, individual standardization yields greater variation in results while joint standardization yields information about general temporal pattern. These two approaches will be further examined in this research, and their usefulness explored in practical applications. Finally, the scale component in GIS-MCDA involves both spatial and temporal elements, although the focus of this research will be on spatial scales. Scale is connected to the well-known Modifiable Areal Unit Problem (MAUP) in geospatial analysis. Both the scale and zoning effects of the MAUP influence the results of GIS-MCDA. Conducting GIS-MCDA case studies at different scales of analysis and using different zoning configurations will contribute to a better understanding of these effects. The proposed research aims to give decision-makers stringent guidelines for aligning the scale of analysis with the scale of action. Overall, the proposed research serves to explore fundamental questions that impact the validity of GIS-MCDA results. The scope of these effects will be explored and best-practice for handling the location, time, and scale components of GIS-MCDA developed. Ultimately, this research program aims to develop a conceptual framework for spatially and temporally explicit, and scale-specific, decision support.