Multispectral Remote Sensing and Spatiotemporal Mapping of the Environment and Natural Disasters Using Small UAS

Abstract

This dissertation focuses on development of new methods for multispectral remote sensing, measurement, and mapping of the environment and natural disasters using small Unmanned Aircraft Systems (UAS). Small UAS equipped with multispectral cameras such as true color (RGB), near infrared (NIR), and thermal can gather important information about the environment before, during, and after a disaster without risking pilots or operators. Additionally, small UAS are generally inexpensive, easy to handle, and can detect features at small spatiotemporal scales that are not visible in manned aircraft or satellite imagery. Four important problems in UAS remote sensing and disaster data representation are focused in this dissertation. First, key considerations for the development of UAS disaster sensing systems are provided, followed by detailed descriptions of the KHawk system and representative environment and disaster data sets. Second, a new method is proposed and demonstrated for accurate mapping and measurement of grass fire evolution using multitemporal thermal orthomosaics collected by a fixed-wing UAS flying at low altitudes. Third, a low-cost and effective solution is further developed for spatiotemporal representation and measurement of grass fire evolution using time-labeled UAS NIR orthomosaics and a novel Intensity Variance Thresholding (IVT) method is proposed for grass fire front extraction to support fire spread metrics measurement of fire front location and rate of spread (ROS). A UAS grass fire observation data set is also presented including thermal and NIR orthomosaics and supporting weather and fuel data. Fourth, a new Satellite-based Cross Calibration (SCC) method is proposed for surface reflectance estimation of UAS images in digital numbers (DN) using free and open calibrated satellite reflectance data. This also serves as a solid foundation for data-enabled multiscale remote sensing and large scale environmental observations. Finally, the main conclusions and future research considerations are summarized.