Research Initiation Award: Remote Sensing for Flood Modeling and Management

研究启动奖为历史悠久的黑人学院和大学的初级和职业生涯中期教师提供支持，这些教师正在建立新的研究计划或重新定向和重建现有的研究计划。预计该奖项有助于进一步提高教师的研究能力和有效性，改善所在机构的研究和教学，并让本科生参与研究经验。授予北卡罗来纳A&T；州立大学的奖项可能会在许多领域产生更广泛的影响。该项目的目标是获得对非武装飞行器(UAV)数据处理的基本了解，并在该大学开发一个用于环境管理的遥感数据处理研究计划。本科生和高中生将获得研究经验，这项研究将整合到一些本科生和研究生课程中。遥感数据越来越多地被用于开发洪水模拟；然而，由于云层的存在、卫星重访时间、视角限制和城市景观的复杂性，传统的基于卫星的技术具有挑战性。无人机的最新发展创造了一种新的工具，用于收集数据用于地理空间研究。应用无人机以适当的飞行模式和优化的传感器收集数据，提供了克服与使用基于卫星的传感器数据相关的问题的可能性。本项目旨在调查和评估无人机数据在洪水模拟和管理中的应用。更广泛地说，这将提高基于无人机对洪水、森林火灾和空气污染等3D动态现象进行模拟和建模的地理信息系统和遥感能力。拟议的项目将为科学文献作出贡献，开发一种新的方法，利用无人机数据重建和划定洪水边界和水位测量的三维水面。这些测量可以与洪水模型相结合，以确定易受未来洪水影响的地区。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Research Initiation Awards provide support for junior and mid-career faculty at Historically Black Colleges and Universities who are building new research programs or redirecting and rebuilding existing research programs. It is expected that the award helps to further the faculty member's research capability and effectiveness, improves research and teaching at the home institution, and involves undergraduate students in research experiences. The award to North Carolina A&T State University has potential broader impacts in a number of areas. The goal of the project is to gain fundamental understanding of unarmed aerial vehicle (UAV) data processing and to develop a research program on remote sensing data processing for environmental management at the university. Undergraduate students and high school students will gain research experiences and the research will be integrated in a number of undergraduate and graduate courses.Remote sensing data have increasingly been used to develop flood modeling; however, traditional satellite-based techniques are challenging due to the presence of cloud cover, satellite revisit time, viewing angle limitations, and the complexity of urban landscapes. The recent development of UAVs has created a new tool for collecting data to use in geospatial research. Applying UAVs to collect data with an appropriate flight mode and optimized sensors offers the possibility of overcoming issues associated with using satellite-based sensor data. This project aims to investigate and evaluate the application of UAV data for flood modeling and management. More generally, this will improve GIS and remote sensing capabilities for UAV-based simulation and modeling of 3D dynamic phenomena such as floods, forest fires, and air pollution. The proposed project will contribute to the scientific literature by developing a novel method for 3D water surface reconstruction and delineation of flood boundary and water level measurements using UAV data. These measurements can be integrated with flood models to identify areas vulnerable to future flooding.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.