MRI RAPID: ACQUISITION OF A FIELD SPECTROSCOPY ENVIRONMENTAL ANALYSIS SYSTEM FOR GULF OIL SPILL RESEARCH

这一核磁共振快速奖是对路易斯安那州墨西哥湾英国石油公司(BP)深水地平线石油钻井平台爆炸后发生的事件的回应。这项提议的目标是获得一个现场光谱分析环境分析系统，以便能够收集关于深水地平线漏油的高度易腐烂的数据。更具体地说，该仪器将用于现场测量石油泄漏和植被在350纳米至2500纳米压力下的光谱响应。由于泄漏的石油开始与环境和石油收集工作相互作用，泄漏的石油的空间分布和物理化学成分迅速演变，迫切需要收集这些实地样本。这种大规模灾难的瞬时性和动态性要求立即和持续地努力收集数据、制定基准和进行量化分析，以监测、评估和管理这次和未来漏油的影响。新仪器将使该小组能够对不同地点(例如深水、浅水、沼泽和海滩)各种物理形式(如光泽、补丁、焦油球)的石油泄漏进行对时间敏感的现场太阳反射率测量，同时记录它们的地理空间位置。结合卫星和/或飞机获取的高光谱图像，该小组将能够在以下方面开展潜在的变革性研究：1)寻找光谱-空间解决方案，以便更准确地绘制公开水域的油类分布图；2)根据光谱和水状况估计浮油厚度；3)利用光谱分解来评估岸上焦油球的数量，以支持清理活动；4)检测复杂的、对环境敏感的生态系统中油类的存在。该团队的环境毒物学家将使用该仪器对受到原油压力的生态系统进行光谱分析。该仪器的收购将显著增强德克萨斯理工大学计算机视觉和图像分析实验室(CVIAL)的能力，使研究生和本科生能够在成像光谱学和高光谱遥感领域获得实践研究体验，这些领域在灾害应对、环境监测和国防中有着广泛的应用。

This MRI-RAPID award is in response to events subsequent to an explosion on the British Petroleum (BP) Deepwater Horizon Oil Rig in the Gulf of Mexico off the coast of Louisiana. The objective of this proposal is to acquire a Field Spectroscopy Environmental Analysis System to enable collection of highly perishable data on the Deepwater Horizon oil spill. More specifically, the instrument will be used to take in-situ measurements of the spectral response of oil spill and vegetation under stress between 350 nm and 2500 nm. The need for collecting these field samples is urgent due to the rapid evolution of spatial distribution and physical-chemical composition of leaked oil as it begins interacting with the environment and oil collection efforts. The transient and dynamic nature of such a large-scale disaster calls for both immediate and continuous efforts in data collection, benchmarking, and quantitative analysis for monitoring, assessment, and management of the impact of this and future spills. The new instrument will enable the team to take time-sensitive, in-situ measurements of solar reflectance of oil spill in various physical forms (e.g. sheen, patch, tar balls) at various sites (e.g. deep water, shallow water, marshes, and beaches) while recording their geospatial locations. In conjunction with hyperspectral images acquired by satellites and/or aircraft, the team will be able to pursue potentially transformative research in 1) seeking a spectral-spatial solution for achieving more accurate oil distribution mapping in open water; 2) estimating oil slick thickness based on its spectrum and water conditions; 3) assessing the quantity of tar balls onshore using spectral un-mixing to support clean-up activities; and 4) detecting the presence of oil in complex, environmentally sensitive ecosystems. Environmental toxicologists on the team will use the instrument to perform spectral analysis of ecosystems stressed by crude oil. The acquisition of this instrument will significantly enhance the capabilities of the Computer Vision and Image Analysis Laboratory (CVIAL) at Texas Tech University to enable hands-on research experience for graduate and undergraduate students in imaging spectroscopy and hyperspectral remote sensing with broad applications in disaster response, environmental monitoring, and national defense.