SCC-Planning: Developing a Sensor-driven, Citizen Science Approach to Hazard Detection and Warning in Rural Communities

对许多社区来说，山体滑坡代表着灾难性和难以预测的危险。预测滑坡是一项重大挑战，因为土壤条件、局部降雨、人类发展模式和许多其他因素汇聚在一起，引发滑坡的方式仍未被地球科学界很好地理解。与此同时，滑坡预警与应对工作也充满了挑战。市民可能会对太多的“假警报”或与他们所在地区无关的警告变得麻木。此外，不同的社会群体对政府当局、科学和彼此的信任程度也不同。因此，风险管理需要大大提高对如何向不同社区传达警告以及如何使他们做好准备对这些信息作出充分反应的理解。以阿拉斯加州锡特卡为例，这项规划拨款将扩大全国物理和社会科学合作者网络，并将他们与我们在锡特卡和阿拉斯加其他地方现有的科学和社区联系联系起来。计划工作将加深团队？对灾害预测的自然科学以及预警和响应系统的社会科学和信息技术有共同的认识。为了提高对滑坡预测、预警和响应的必要的共同理解，物理和社会科学领域必须耦合和共同发展，有效的预警系统依赖于准确的预测能力。该项目将把地球科学家、社会科学家和当地利益相关者联系在一起，围绕有效的、基于需求的灾害预测、预警和响应，确定关键的研究问题。通过这项工作，我们将实现以下目标：(1)准备部署滑坡监测系统；(2)计划利用传感器数据来提高滑坡预测能力；(3)创建一个框架，以提高对偏远和多样化社区社会网络风险感知和沟通的理解；(4)为一个项目奠定基础，该项目将利用改进的滑坡预测能力，增加对风险感知和沟通的理解来实施预警系统。该项目将采用以下方法来完成这项工作：(1)与当地和国家地球科学家的会议和接触，(2)公民科学和分布式传感器的方法和技术调查，(3)应用健康研究中的风险感知、社会网络和文化测量方法，以及(4)合作撰写拨款。我们期望对规划拨款和后续工作产生以下影响：(1)改进与灾害相关的公民科学技术；(2)在不同社区采用更好的技术和社会方法来建立灾害预警系统；(3)提高了农村和偏远社区（包括印第安人社区）的风险认知和社区对自然灾害的抵御能力；(4)通过将科学与区域和国家数据集联系起来，提高了对滑坡灾害预测的认识。

For many communities, landslides represent catastrophic and difficult-to-predict hazard. Predicting landslides is a significant challenge, as soil conditions, localized rainfall, patterns of human development, and many other factors converge to trigger slides in ways still not well understood by the geoscience community. Meanwhile, landslide warning and response is fraught with challenges. Citizens can become desensitized by too many "false alarms", or warnings not relevant to their locale. Also, different social groups have different levels of trust in governmental authorities, science, and each other. Risk management thus requires significantly improved understanding of how to communicate warning to diverse communities and how to prepare them to respond adequately to this information. Using Sitka, Alaska as our example, this planning grant will expand a national network of physical and social scientific collaborators and link them to our existing science and community connections in Sitka and elsewhere in Alaska. The planning effort will deepen the team?s shared understanding of the natural science of hazard prediction and the social science and information technology of warning and response systems.In order to improve the necessary shared understanding of landslide prediction, warning, and response, the physical and social science domains must be coupled and co-evolve as effective warning systems depend on accurate predictive capabilities. This project will connect geoscientists, social scientists, and local stakeholders together to determine the critical research questions around effective, needs-based hazard prediction, warning, and response. Through this work, we will accomplish the following goals: (1) prepare to deploy a landslide monitoring system, (2) plan to leverage data from sensors to improve predictive power for landslides, (3) create a framework to improve understanding of risk perception and communication across social networks in remote and diverse communities, and (4) lay the groundwork for a project that would leverage improved landslide prediction capacity and increased understanding of risk perception and communication to implement a warning system. The project will use the following approaches to accomplish this work: (1) meetings and engagements with local and national geoscientists, (2) methodological and technological survey of citizen science and distributed sensors, (3) application of risk perception, social network, and cultural measurement methods from health research, and (4) collaborative grant-writing. We expect the following impact for the planning grant and follow-on work: (1) improved techniques for hazard-related citizen science; (2) better technical and social approaches to hazard warning systems in diverse communities; (3) improved understanding of risk perception and community resilience to natural hazards in rural and remote communities, including those with Native American populations; (4) improved understanding of landslide hazard prediction through connecting science with regional and national datasets.