CHABMAP (Cyanobacterial Harmful Algal Bloom Mapping and Analyses Platform) technology automates the quantification of toxic CyanoHABs exposure epochs for any waterbody.

CHABMAP（蓝藻有害藻华绘图和分析平台）技术可自动量化任何水体的有毒 CyanoHAB 暴露时间。

• 批准号: 9906581
• 负责人: Nathan Torbick
• 金额: $ 50.42万
• 依托单位: APPLIED GEOSOLUTIONS, LLC
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-01-15 至 2022-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9906581
• 关键词: Address; Algae; Amyotrophic Lateral Sclerosis; Archives; Big Data; Centers for Disease Control and Prevention (U.S.); Chlorophyll; Clinic; Color; Communication; Computer software; Custom; Cyanobacterium; Data; Development; Environment; Epidemiology; Etiology; Frequencies; Genes; Geography; Machine Learning; Measurement; Medical center; Molecular Biology; Monitor; Neurodegenerative Disorders; Neurodevelopmental Disorder; Neuromuscular Diseases; North America; Outcome; Patients; Phase; Planets; Poison; Public Health; Public Health Applications Research; Recording of previous events; Registries; Research; Resolution; Retrieval; Risk Assessment; Risk Factors; Role; Sentinel; Services; Solid; Stream; System; Techniques; Technology; Time; Toxic effect; Toxin; United States National Aeronautics and Space Administration; United States National Institutes of Health; Universities; Work; application programming interface; base; cloud based; data exchange; design; disease registry; drug development; drug discovery; harmful algal blooms; image processing; indexing; innovation; nervous system disorder; parallelization; population based; remote sensing; spatiotemporal; support tools

Specific Aim #1: Operationalize spatio-temporal CyanoHAB exposure epoch metrics • Fuse multi-scale and disparate satellite remote sensing platforms and automate retrievals over space and time to derive CyanoHAB exposure metrics. We will build enterprise software to fully automate the harmonization and fusion of NASA’s Landsat-8 OLI and ESA’s Sentinel-2 and Sentinel-3 satellite platforms to provide long-term (1984-present) moderate spatial resolution (30meter pixels) and high temporal frequency CyanoHAB exposure metrics (Cyanobacteria Intensity, Color Dissolved Organic Matter, Total Suspended Solids, Floating Algae Index, Chlorophyll-a Concentration, & toxins). The decision support tool automates epoch synthesis to understand incubation periods and exposure triggers for neurodegenerative diseases. Specific Aim #2: Scale on-demand CHABMAP commercial product services • Scale and implement CHABMAP data services for infinite scalability using BigData cloud technologies. This Aim involves three main development efforts: adapting our proprietary Geospatial Image and Processing System (GIPS) capabilities to an AWS-deployable auto-scaling cluster, creation of user interfaces and application programming interfaces (APIs) to interact with these services, and enhancements to the base GIPS framework to facilitate intercommunication between remote GIPS-enabled archives and the cloud processing streams. This includes the creation of deployable compute instances, optimization of computation and parallelization specific to AWS deployment, optimization of temporary and long-term storage of intermediate products, and optimization of communication and data transfer with end users. Ultimately, this Aim will allow for the assessment and monitoring of CyanoHAB conditions for any waterbody or region (i.e., North America) on the planet. Specific Aim #3: Execute risk assessment frameworks with public health partners • We will work in partnership with Cleveland Clinic, Dartmouth Hitchcock Medical Center, University of Miami, Macquarie University, NIH’s Neuromuscular Diseases Research Section and CDC’s Agency for Toxic Substances and Disease Registry (National ALS Registry) to assess the role of CyanoHABs exposure as a risk factor for Amyotrophic lateral sclerosis (ALS) using patients, clinic-, and population-based controls across diverse settings and geographies. Each application end user has ongoing risk assessment frameworks (i.e., Gene-Environment, Residential History Machine Learning, eco-epidemiological, molecular biology) which our CHABMAP technology will integrate exposure epoch metrics to understand the etiology or ALS and support drug discovery. Proposed Innovation CHABMAP technology automates the quantification of toxic Cyanobacterial Harmful Algal Bloom (CHAB) exposure epochs for any waterbody or catchment in the world for the past four decades using multi-scale harmonized satellites. We use custom and proprietary techniques combined with BigData software to generate historical exposure (“exposome”) profiles as well provide Decision Support Tools services for CHAB monitoring in near-real time. During Phase 2 and beyond we work with world experts to integrate our commercial products and services into neurodegenerative disease Gene-Environment (GxE) risk assessment frameworks. Proposed Products, Services, Outcomes • Develop historical CHAB exposure measurements working with environmental agency partners • Assessment of CyanoHABs as a risk factor for ALS across multiple, independent study regions • CHABMAP on-demand Analytics-as-a-Service platform operating at end of Phase 2 • Support discovery of etiology and drug development for neurological disorders and diseases

具体目标#1：实施时空 CyanoHAB 暴露时期指标 • 融合多尺度和不同的卫星遥感平台并自动检索 获得 CyanoHAB 暴露指标的空间和时间 我们将充分构建企业软件。 自动协调和融合 NASA 的 Landsat-8 OLI 和 ESA 的 Sentinel-2 以及 Sentinel-3 卫星平台提供长期（1984 年至今）中等空间分辨率 （30 米像素）和高时间频率 CyanoHAB 暴露指标（蓝细菌 强度、颜色溶解有机物、总悬浮固体、漂浮藻类指数、 叶绿素-a 浓度和毒素）决策支持工具可自动进行纪元合成。 了解神经退行性疾病的潜伏期和暴露触发因素。 具体目标 #2：扩展按需 CHABMAP 商业产品服务 • 使用 BigData 云扩展和实施 CHABMAP 数据服务以实现无限可扩展性 该目标涉及三项主要开发工作： 采用我们的专有技术。 地理空间图像和处理系统 (GIPS) 功能可用于 AWS 可部署的自动扩展 集群，创建用户界面和应用程序编程接口 (API) 进行交互 这些服务以及对基础 GIPS 框架的增强以促进相互通信 支持 GIPS 的远程档案和云处理流之间。 创建可部署的计算实例、优化计算和并行化 针对AWS部署，中间件临时和长期存储的优化 最终，这就是产品的优化以及与最终用户的通信和数据传输的优化。 Aim 将允许评估和监测任何水体或 地球上的地区（即北美）。 具体目标#3：与公共卫生合作伙伴一起执行风险评估框架 • 我们将与克利夫兰诊所、达特茅斯希区柯克医疗中心、 迈阿密大学、麦考瑞大学、NIH 神经肌肉疾病研究部和 CDC 有毒物质和疾病登记机构（国家 ALS 登记处）评估其作用 CyanoHAB 暴露作为患者肌萎缩侧索硬化症 (ALS) 的危险因素， 跨不同环境和地域的基于临床和人群的控制。 最终用户拥有持续的风险评估框架（即基因环境、居住历史 机器学习、生态流行病学、分子生物学）我们的 CHABMAP 技术将 整合暴露时期指标以了解病因或 ALS 并支持药物发现。 拟议的创新 CHABMAP 技术可自动定量有毒蓝藻有害藻华 (CHAB) 使用多尺度计算过去四十年世界上任何水体或流域的暴露时期 我们使用定制和专有技术与大数据软件相结合。 生成历史暴露（“暴露组”）概况，并提供决策支持工具服务 在第二阶段及之后，我们与世界各地的专家合作进行近乎实时的 CHAB 监控。 我们的商业产品和服务涉及神经退行性疾病基因环境 (GxE) 风险 评估框架。 提议的产品、服务、成果 • 与环境机构合作伙伴合作开发历史 CHAB 暴露测量 • 在多个独立研究区域评估 CyanoHAB 作为 ALS 的危险因素 • CHABMAP 按需分析即服务平台在第 2 阶段结束时运行 • 支持神经系统疾病的病因学发现和药物开发