SCC-RCN: Smart Civic Engagement in Rapidly Urbanizing Regions

SCC-RCN：快速城市化地区的智慧公民参与

• 批准号: 1737563
• 负责人: Ross Meentemeyer
• 金额: $ 49.98万
• 依托单位: North Carolina State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1737563&HistoricalAwards=false
• 关键词: SCC; RCN; Smart; Civic; Engagement

Solutions for large-scale problems like stormwater management in urbanizing regions require input from a variety of stakeholders and coordination between nearby cities and towns. However, institutional barriers commonly prevent open discussion for collaborative decision-making. The team envisions a new way to enhance smart connections among communities and break down barriers across geographic space, levels of governance, and types of expertise: a collaborative platform for knowledge-sharing that suits diverse stakeholder needs, a mutually developed environment called TomorrowNow. This Research Collaboration Network (RCN) will unite regional stakeholders from government, industry, academia, watershed associations, and other community groups to guide the development of TomorrowNow, advancing the contribution of diverse perspectives to stormwater management and decision-making. The publicly available, multi-userenvironment conceptualized by the RCN will be transformative for crowdsourcing the opinions of a wide range of stakeholders and local residents in the Triangle region of North Carolina. Residents will be able to explore and visualize intervention strategies in the very places where they live and work, to inform management decisions regarding stormwater and improve quality of life. Ultimately, the online game conceptualized by the RCN will not only provide an engaging, intuitive platform in the Triangle, but will serve as a model to empower smart and connected communities elsewhere.This RCN will collaboratively explore whether multi-user, web-based collaborative decision making using real data and scientific models to show the connectedness of locations could increase equitable participation in local decision-making, elevating the voices of underprivileged groups and diverse perspectives. The RCN will unite researchers and stakeholders to plan the design of a collaborative decision environment, TomorrowNow, which enables people to interact with spatially explicit models of urbanization and associated changes to stormwater hydrology (quantity) and biogeochemistry (quality), problems of increasing concern across urbanizing regions in the US. The RCN will convene leaders from local and regional governments, non-governmental organizations, and research teams specializing in natural, social, and computer sciences in the Research Triangle region of North Carolina; these leaders will collaboratively identify needs and approaches for improving inclusive participation and allowing a wider range of stakeholders to explore and visualize intervention strategies in the places where they live and work. Development of the network will advance the science of co-producing actionable solutions among researchers, policymakers, and residents, as well as identify research directions that advance new genres of urbanization and stormwater models (hydrologic and biogeochemical) needed to underlie the user-friendly interface of a serious game. TomorrowNow will enable communities connected by shared water networks (and their associated problems of stormwater runoff, surface water contamination, and groundwater quantity/quality) to collaboratively design alternative futures that optimize management of those water networks. The input of diverse communities will be collected via surveys, semi-structured interviews, panels, discussions during in-person workshops and symposia, and through discussion threads in an open-source online community.

针对城市化地区雨水管理等大规模问题的解决方案需要各种利益相关者的意见以及附近城镇之间的协调。但是，机构障碍通常阻止公开讨论协作决策。该团队设想了一种新的方式来增强社区之间的智能连接，并打破跨地理空间，治理水平和专业知识类型的障碍：知识共享的协作平台，适合各种利益相关者需求，这是一个相互发展的环境，称为Tomornowow。该研究合作网络（RCN）将团结来自政府，工业，学术界，分水岭协会和其他社区团体的区域利益相关者，以指导明天的发展，推进各种观点对雨水管理和决策的贡献。 RCN概念化的公开可用的多用户环境将具有变革性的变革性，可以使北卡罗来纳州三角地区的各种利益相关者和当地居民的观点进行变革。居民将能够在生活和工作的地方探索和可视化干预策略，以告知管理层有关雨水的决策并改善生活质量。最终，RCN概念化的在线游戏不仅将在三角形中提供一个引人入胜的直觉平台，而且将作为一个模型，以增强其他地方的智能和连接的社区的能力。此RCN将在多多用户，基于Web的基于网络的协作决策中使用真实的数据和科学模型来探索各种位置的参与度，并在本地的参与度中增加了各种各样的参与度，以探索各种各样的决策，以提高本地决策，以促进范围的参与度，以促进范围的参与度，以促进范围的参与度，以促进范围的参与度，以促进范围的社交决策。观点。 RCN将团结研究人员和利益相关者，计划协作决策环境Tomornowow的设计，这使人们能够与空间明确的城市化模型以及雨水水文（数量）和生物地质化学（质量）的相关变化，美国越来越多的城市化区域越来越多的问题。 RCN将召集来自地方和地区政府，非政府组织以及专门从事北卡罗来纳州研究三角地区自然，社会和计算机科学的研究团队的领导人；这些领导者将协作确定改善包容性参与的需求和方法，并允许更多的利益相关者在他们生活和工作的地方探索和可视化干预策略。该网络的发展将推进研究人员，决策者和居民共同生产可行解决方案的科学，并确定研究方向，这些方向推进了所需的新型城市化和雨水模型（水文和生物地球化学）的新类型，以构成认真游戏的用户友好界面。 Tomornowow将使通过共享水网络（及其相关的雨水径流问题，地表水污染和地下水数量/质量的问题）连接的社区，以协作设计替代期货，以优化这些水网络的管理。各种社区的输入将通过调查，半结构化访谈，小组讨论，在面对面讲习班和研讨会期间的讨论以及开源在线社区中的讨论线索收集。

项目成果

High Resolution Viewscape Modeling Evaluated Through Immersive Virtual Environments

• DOI: 10.3390/ijgi9070445
• 发表时间: 2020-07
• 期刊: ISPRS Int. J. Geo Inf.
• 作者: Payam Tabrizian;A. Petrasova;Perver K. Baran;Jelena Vukomanovic;H. Mitásová;R. Meentemeyer

Making It Spatial Makes It Personal: Engaging Stakeholders with Geospatial Participatory Modeling

使其空间化，使其个性化：让利益相关者参与地理空间参与式建模

• DOI: 10.3390/land8020038
• 发表时间: 2019
• 期刊: Land
• 影响因子: 3.9
• 作者: Vukomanovic, Jelena;Skrip, Megan;Meentemeyer, Ross
• 通讯作者: Meentemeyer, Ross

Spatially Explicit Fuzzy Cognitive Mapping for Participatory Modeling of Stormwater Management

用于雨水管理参与式建模的空间显式模糊认知绘图

• DOI: 10.3390/land10111114
• 发表时间: 2021
• 期刊: Land
• 影响因子: 3.9
• 作者: White, Corey T.;Mitasova, Helena;BenDor, Todd K.;Foy, Kevin;Pala, Okan;Vukomanovic, Jelena;Meentemeyer, Ross K.
• 通讯作者: Meentemeyer, Ross K.

Impacts of Urbanization on Watershed Water Balances Across the Conterminous United States

• DOI: 10.1029/2019wr026574
• 发表时间: 2020-06
• 期刊: Water Resources Research
• 影响因子: 5.4
• 作者: Cheng Li;G. Sun;P. Caldwell;E. Cohen;Yuan Fang;Yindan Zhang;L. Oudin;G. Sanchez;R. Meentemeyer

Projecting Urbanization and Landscape Change at Large Scale Using the FUTURES Model

使用 FUTURES 模型预测大规模的城市化和景观变化

• DOI: 10.3390/land8100144
• 发表时间: 2019
• 期刊: Land
• 影响因子: 3.9
• 作者: Van Berkel, Derek;Shashidharan, Ashwin;Mordecai, Rua;Vatsavai, Raju;Petrasova, Anna;Petras, Vaclav;Mitasova, Helena;Vogler, John;Meentemeyer, Ross
• 通讯作者: Meentemeyer, Ross