Collaborative Research: CyberSEES: Type 2: A New Framework for Crowd-Sourced Green Infrastructure Design

合作研究：Cyber​​SEES：类型 2：众包绿色基础设施设计的新框架

• 批准号: 1331813
• 负责人: Lawrence Band
• 金额: $ 57.22万
• 依托单位: University of North Carolina at Chapel Hill
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-10-01 至 2017-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1331813&HistoricalAwards=false
• 关键词: Collaborative; Research; CyberSEES; Type; New

This project develops a novel computational Green Infrastructure (GI) design framework that integrates interactive, neighborhood-scale, collaborative design by multiple stakeholders ("crowd-sourced" design) with multi-scale models of ecosystem and human impacts. The following research questions are being addressed: (1) How well does coupling of site-scale ecohydrology with catchment-scale hydraulic routing improve predictions? (2) How well can stakeholder preferences be predicted using design image feature extraction and machine learning? (3) What interactive optimization and visualization techniques lead to the most rapid and complete consensus among diverse stakeholders? (4) Do stakeholders using interactive cyberinfrastructure tools consider more options and explore more of the GI design space?A "crowd-sourced" design framework is developed to enable stakeholders to interactively create and evaluate potential GI designs that reflect consideration of the full breadth of social, economic, and environmental criteria. The research questions are evaluated in diverse neighborhoods within three urban catchments in the Baltimore Ecosystem Study, working closely with environmental non-governmental organizations to ensure that the results will provide significant benefits to community stakeholders. The models developed in this project are the first to integrate criteria for human and ecosystem wellbeing with site- and watershed-scale hydrologic processes, a key advance for improving understanding and implementation of GI design. Map and image visualization identifies which visualization approaches best support improving stakeholder engagement for achieving consensus using interactive collaborative design. This makes technical advances in interactive optimization and model parameterization accessible to the broad range of stakeholders, from regulators and planners to contractors and homeowners.

该项目开发了一种新颖的计算绿色基础设施（GI）设计框架，该框架将多个利益相关者（“众包”设计）的交互式邻里规模协作设计与生态系统和人类影响的多尺度模型相结合。正在解决以下研究问题：（1）场地规模生态水文学与流域规模水力路线的耦合如何改善预测？ (2) 使用设计图像特征提取和机器学习来预测利益相关者偏好的效果如何？ (3) 哪些交互优化和可视化技术可以让不同利益相关者之间达成最快速、最完整的共识？ (4) 使用交互式网络基础设施工具的利益相关者是否考虑更多选择并探索更多地理标志设计空间？开发了“众包”设计框架，使利益相关者能够交互式地创建和评估潜在的地理标志设计，这些设计反映了对地理标志设计的全面考虑。社会、经济和环境标准。巴尔的摩生态系统研究中的研究问题在三个城市流域内的不同社区进行了评估，并与环境非政府组织密切合作，以确保结果将为社区利益相关者带来重大利益。该项目开发的模型首次将人类和生态系统福祉标准与场地和流域规模的水文过程相结合，这是提高对地理标志设计的理解和实施的关键进步。地图和图像可视化确定了哪些可视化方法最能支持提高利益相关者的参与度，从而使用交互式协作设计达成共识。这使得交互式优化和模型参数化方面的技术进步可供广大利益相关者（从监管者和规划者到承包商和房主）使用。