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My research focuses on utilizing a range of remote sensing technologies, including LiDAR and optical sensors, deployed on satellites, aircraft, and unmanned aerial systems, to map and monitor wetland vegetation dynamics. I integrate advanced image processing techniques, photogrammetry, and machine learning algorithms to enhance the understanding of these ecosystems. Details of my current projects are provided below. If you are an undergraduate or prospective graduate student interested in discussing potential research opportunities, feel free to reach out.
Leveraging Drone-based LiDAR and Hydrodynamic Modeling to Map Wetland Dynamics in Arid Landscapes
Leveraging Drone-based LiDAR and Hydrodynamic Modeling to Map Wetland Dynamics in Arid Landscapes
Microtopography in wetlands is a critically important attribute in predicting the development and sustainability of wetland ecosystems. This project assesses the feasibility of drones equipped with multi-echo LiDAR systems to generate landscape-scale point cloud densities that are capable of retrieving microtopographic features not resolvable with other close-range remote sensing techniques (i.e. drones structure-from-motion, terrestrial scanners) or with airborne (manned) LiDAR systems.
Los Angeles River Habitat Mapping and Hydraulic Modeling
Los Angeles River Habitat Mapping and Hydraulic Modeling
There's growing interest in restoring Los Angeles River ecosystem function while maintaining existing levels of flood protection. The success of these efforts depends on understanding how changes in river flow impact water supply, quality, habitat resilience, and flood risks. Current LA River models, which rely on simplistic geometric assumptions, may not adequately represent the river's more complex, natural forms proposed in restoration projects. Additionally, data collection for accurate modeling can be costly and time-intensive. This study explores an efficient and inexpensive mapping approach that integrates Unmanned Aerial Vehicles (UAVs), Structure from Motion (SfM), and machine learning algorithms to generate ultra-high-resolution 3D maps of river habitat and geomorphic features.
Hydrodynamics, Morphological Characteristics, and Lateral Erosion Rates in Rapidly Degrading Salt Marshes
Hydrodynamics, Morphological Characteristics, and Lateral Erosion Rates in Rapidly Degrading Salt Marshes
Along salt marsh boundaries, wave action is the dominant mechanism of lateral erosion and subsequent land loss. Yet, the hydrodynamic conditions and geotechnical properties that produce high rates lateral erosion are not resolved. This research explores the use of drones and a network of in situ instruments to capture the high spatiotemporal resolution data needed to fill this knowledge gap and advance wetlands ecosystem assessment, monitoring, and modeling techniques.
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