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

对于许多社区来说，山体滑坡是灾难性的、难以预测的危险。预测滑坡是一个巨大的挑战，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，以一种地球科学界仍然不太了解的方式触发滑坡。与此同时，滑坡预警和应对充满了挑战。公民可能会因为太多的“假警报”或与他们所在地区无关的警告而变得麻木。此外，不同的社会群体对政府当局、科学以及彼此之间的信任程度也不同。因此，风险管理要求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充分应对这一信息的准备的理解。以阿拉斯加州锡特卡为例，这笔规划赠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的现有科学和社区联系联系起来。规划工作将深化团队？S分享了对灾害预测自然科学和预警与响应系统的社会科学和信息技术的理解。为了提高对滑坡预测、预警和响应的必要共享理解，物理和社会科学领域必须耦合并共同发展，因为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攸关方联系在一起，以确定围绕有效的、基于需求的危险预测、预警和响应的关键研究问题。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)计划利用传感器的数据来提高对山体滑坡的预测能力；(3)创建一个框架，以改善对偏远和多样化社区中社会网络中的风险感知和沟通的理解；以及(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和对风险感知和沟通的更多了解来实施预警系统。该项目将使用以下方法来完成这项工作：(1)与地方和国家地球科学家举行会议和接触，(2)对公民科学和分布式传感器进行方法学和技术调查，(3)应用卫生研究中的风险感知、社会网络和文化测量方法，以及(4)合作编写赠款。我们预计规划赠款和后续工作将产生以下影响：(1)改进与灾害有关的公民科学技术；(2)在不同的社区采用更好的灾害预警系统的技术和社会办法；(3)提高对农村和偏远社区，包括美洲原住民社区对自然灾害的风险认知和社区复原力的了解；(4)通过将科学与区域和国家数据集联系起来，提高对山体滑坡危险预测的理解。

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.