RAPID: Critical Wildfire Monitoring Utilizing the National Ecological Observatory Network Mobile Deployment Platform with Edge-computing Cyberinfrastructure

RAPID：利用国家生态观测站网络移动部署平台和边缘计算网络基础设施进行关键野火监测

• 批准号: 2137769
• 负责人: Eugene Kelly
• 金额: $ 19.99万
• 依托单位: Colorado State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-07-15 至 2022-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2137769&HistoricalAwards=false
• 关键词: RAPID; Critical; Wildfire; Monitoring; Utilizing

Wildfire frequency and intensity are highly likely to increase in forests of the U.S. Intermountain West, a region that is experiencing the worst drought in over a century. This RAPID project will utilize the Mobile Deployment Platform (MDP) of the National Ecological Observatory Network (NEON) coupled with high-performance computing resources to enable responsive and real-time, data-driven soil sample collection during and immediately following wildfire activity. This rapid response is vital to enable researchers to characterize changes in soil microbial community structure and carbon metabolizing ability during and following fire disturbance. The information obtained will be used for modelling the impact of wildfire and climate change, and to help guide forest land management. The project will mount thermal imaging cameras equipped with the edge-enabled, intelligent sensor network known as "SAGE" on the NEON MDP along with in-situ edge computing resources to guide location of manual observational sampling in and adjacent to fire-exposed forest. Soil microbiota across a range of soil temperatures will be studied to examine their heterogeneity guided by thermal sensing. Metagenomoic DNA sequence analysis will be used to study soil microbiome functional traits in the immediate aftermath of wildfire, and determine the impacts of shifts on carbon cycling and sequestration. The results will test whether real time data acquisition can effectively guide sensor placement and human observational sampling during and immediately following disturbance and test the coupled ability of the NEON platform and SAGE cyber-infrastructure to support real-time alerts when edge-based and artificial intelligence (AI)-enabled algorithms detect anomalous conditions (e.g. additional smoke plumes). This will be the first such use of the NEON MDP with SAGE cyber tools, and represents an urgent advance to enable scientists and managers to better understand the impacts of climate change, drought and wildfire disturbances.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

野火的频率和强度极有可能增加美国西部森林的森林，该地区正在经历一个多世纪以来最严重的干旱。这个快速的项目将利用国家生态观测网络（NEON）的移动部署平台（MDP）以及高性能计算资源，在野火活动期间和之后，在野火活动期间和立即收集了响应式和实时，实时的，数据驱动的土壤样本。这种快速反应对于使研究人员能够表征土壤微生物群落结构的变化以及在火灾干扰期间和之后的碳代谢能力的变化至关重要。获得的信息将用于建模野火和气候变化的影响，并帮助指导林地管理。该项目将安装配备有边缘的，智能传感器网络的热成像摄像机在霓虹灯MDP上被称为“ Sage”，以及原位边缘计算资源，以指导在火灾暴露的森林中和毗邻的手动观察性采样的位置。将研究跨多种土壤温度的土壤微生物群，以检查其以热感应为指导的异质性。 元基因组DNA序列分析将用于研究野火后立即研究土壤微生物组功能性状，并确定转移对碳循环和隔离的影响。 结果将测试实时数据获取是否可以有效指导传感器放置和在干扰期间和之后的人类观察性采样，并测试NEON平台和SAGE网络基础设施的耦合能力，以支持基于边缘的基于边缘的和人工智能（AI）算法 - 可启用算法的实时警报。这将是霓虹灯MDP与SAGE网络工具的首次使用，并代表了使科学家和经理能够更好地了解气候变化，干旱和野火障碍的影响的紧急进步。这项奖项反映了NSF的法定任务，并被认为是通过基金会的知识绩效和广泛的影响来评估的。