RII Track-4: @NASA: Next Generation Hyperspectral Approaches to Detect Harmful Algal Blooms

RII Track-4：@NASA：检测有害藻华的下一代高光谱方法

• 批准号: 2327287
• 负责人: Khalid Ali
• 金额: $ 30万
• 依托单位: College of Charleston
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2024
• 资助国家: 美国
• 起止时间: 2024-01-01 至 2025-12-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2327287&HistoricalAwards=false
• 关键词: RII; Track; NASA; Next; Generation

This Research Infrastructure Improvement Track-4 EPSCoR Research Fellows (RII Track-4) project will provide a fellowship to an Associate Professor and training for a graduate student at the College of Charleston. This work would be conducted in collaboration with researchers at the NASA Ames Research Center (ARC). The project aims to address Harmful Algal Blooms (HABs) in coastal regions by utilizing state-of-the-art satellite technology and innovative algorithms. HABs pose significant threats to marine ecosystems, human health, and local economies. By leveraging new-generation satellite sensors and advanced data analysis, the project seeks to provide accurate information on the spatial and temporal distribution of HABs. This project's significance lies in its potential to revolutionize HAB monitoring and management. Traditional methods have limitations in resolution, hindering effective responses. Advancing satellite remote sensing and data analysis contributes to scientific progress. Furthermore, the project serves the national interest by promoting environmental health, prosperity, and welfare. HABs disrupt coastal communities, affecting fisheries, tourism, and human health due to harmful toxins. Timely monitoring can mitigate these impacts. The project supports education and diversity by fostering collaboration among researchers from diverse backgrounds. Interdisciplinary opportunities attract scholars, advancing scientific knowledge. Ultimately, the project benefits society by enabling effective environmental policies and management. Understanding HAB dynamics will lead to healthier coastal ecosystems, safer drinking water sources, and improved public health, benefiting the nation's well-being and prosperity.Harmful algal blooms (HABs) are causing one of the most important environmental crises in aquatic environments and are of growing concern worldwide due to their serious impacts on public health as well as on the aquaculture and fisheries industry. HABs occur in response to rising surface water temperatures and increased flux of nutrients into streams and lakes. Over the past few decades, earth-observation satellite-based tools have been developed for tracking the development and movement of HABs and algal blooms. This has traditionally been done using estimates of chlorophyll-a concentration (Chl-a, mg m−3), a proxy for phytoplankton biomass. However, Chl-a alone does not provide a full description of the inherent phytoplankton community structure or information regarding specific HAB species. Thus, high-resolution satellite ocean color products that go beyond universal Chl-a and provide information on specific HAB species are critically needed for accurate HAB tracking and forecasting models. The goal of the project is to utilize new-generation hyperspectral sensors and support the continued effort of developing robust algorithms that can accurately provide spatially and temporally explicit data on the distribution of HABs. The project will merge multiple classes of data products to develop HAB products that are best suited for use with next-generation hyperspectral sensors. We will work on NASA’s semi-analytical optimization method, the Generalized Inherent Optical Property and new machine learning-based HAB mapping algorithms which can be used to characterize the optical properties of water and retrieve HAB products from several existing and future ocean color satellites.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.

该研究基础设施改进Track-4 Epscor Research Fellows（RII Track-4）项目将为查尔斯顿学院的一名研究生的副教授和培训提供奖学金。这项工作将与NASA AMES研究中心（ARC）的研究人员合作进行。该项目旨在通过利用最先进的卫星技术和创新算法来解决沿海地区有害的藻华（HAB）。哈布斯对海洋生态系统，人类健康和地方经济构成了重大威胁。通过利用新的卫星传感器和高级数据分析，该项目旨在提供有关HAB的空间和临时分布的准确信息。该项目的意义在于它有可能改变HAB监测和管理的潜力。传统方法在解决方案方面有局限性，阻碍了有效的响应。促进卫星遥感和数据分析有助于科学进步。此外，该项目通过促进环境健康，繁荣和福利来为国家利益提供服务。哈布斯因有害毒素而影响渔业，旅游业和人类健康，破坏了沿海社区。及时监视可以减轻这些影响。该项目通过促进来自潜水员背景的研究人员的合作来支持教育和多样性。跨学科的机会吸引学者，促进科学知识。最终，该项目通过实现有效的环境政策和管理来使社会受益。了解HAB动力学将导致更健康的沿海生态系统，安全的饮用水源并改善公共卫生，从而使国家的福祉和繁荣受益。豪华的藻类血液（HABS）正在造成水生环境中最重要的环境犯罪之一，并且由于其对公共健康以及对水上和Fisheries和Fisheries and Fisheries and Fisheries and and Aquies and and and Aquies and and and and and and and venter and in tond Charting the Worlding。 HAB发生在响应地表水温上升以及养分通量增加到溪流和湖泊中。在过去的几十年中，已经开发了基于地球观察卫星的工具来跟踪HAB和藻类血液的发展和运动。传统上，这是使用叶绿素-A浓度（CHL-A，MG M-3）的估计值，这是浮游植物生物量的代理。但是，仅CHL-A并未提供有关遗传浮游植物社区结构或有关特定HAB物种的信息的完整描述。这是，对于准确的HAB跟踪和预测模型，至关重要的是，高分辨率的卫星海洋色产品超出了通用CHL-A并提供有关特定HAB物种的信息。该项目的目的是利用新一代的高光谱传感器，并支持开发可靠的算法的持续努力，这些算法可以准确地提供有关HABS分布的显着明确数据。该项目将合并多种数据产品，以开发最适合与下一代高光谱传感器一起使用的HAB产品。我们将采用NASA的半分析优化方法，是广义的固有光学特性和新的基于机器学习的HAB映射算法，可用于表征水的光学特性，并从几种现有和未来的海洋色卫星上检索HAB产品。该奖项通过评估了NSF的法定措施，反映了NSF的Internia Inffectia Infectia the Internitia infortial and Founlitial的支持。