sUAS Imagery

Small Unmanned Aerial Systems (sUAS) imagery analysis is a rapidly developing field focused on extracting valuable information from drone-captured images for various applications. Current research emphasizes improving the accuracy and reliability of this imagery, particularly addressing challenges like non-uniform spatial alignment errors and the impact of wind on drone stability, often leveraging computational fluid dynamics and advanced image processing techniques. These advancements are crucial for enhancing the use of sUAS imagery in disaster response, infrastructure assessment, and other critical applications requiring precise geospatial data and robust autonomous operation, particularly in challenging environments. Large, labeled datasets are being developed to support the training and evaluation of machine learning models for tasks such as building damage assessment.