Synthesizing multiple ecosystem service assessments for urban planning: A review of approaches, and recommendations

计算机科学 可用性 利益相关者 服务(商务) 决策支持系统 管理科学 透明度(行为) 城市规划 过程管理 数据科学 风险分析(工程) 业务 数据挖掘 工程类 政治学 计算机安全 人机交互 营销 公共关系 土木工程
作者
Chiara Cortinovis,Davide Geneletti,Katarina Hedlund
出处
期刊:Landscape and Urban Planning [Elsevier BV]
卷期号:213: 104129-104129 被引量:57
标识
DOI:10.1016/j.landurbplan.2021.104129
摘要

While ecosystem service (ES) assessments become a more and more important source of knowledge, there is a need for synthesis approaches that make the results usable to support decisions. Effective synthesis approaches can reduce the information burden produced by multiple ES assessments and help decision-makers to compare alternative options and to assess their impacts. In this review, we focus on urban planning, one of the main decision-making processes that affect ES in cities, and investigate what synthesis approaches have been applied to support planning decisions. The aim is to identify the options available and to analyze their suitability to different urban planning decisions, thus providing a guidance to potential users. We reviewed 62 studies selected through a search in two literature databases and identified six recurring synthesis approaches: diversity, average, weighted summation, multi-criteria analysis, optimization algorithms, and efficiency indicators; and a limited number of methods developed ad-hoc for specific applications. For each approach, we collected evidence about the appropriateness for different decision-making contexts, the applicability to different ES categories and types of assessment methods, and the occurrence of complementary analyses of ES interactions. Further, we built on the reviewed publications to identify pros and cons, including critical aspects related to the usability of the approaches, such as their complexity, transparency, and the level of stakeholder involvement. Based on the findings, we draw recommendations on how to select suitable synthesis approaches to support different urban planning decisions.
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