Anomaly Gas Remote Sensing and Tracking Using a Field-Portable Imaging Thermal Radiometric Spectrometer

Abstract

Using a set of radiometric thermal hyperspectral data cubes, we developed an algorithm which detects the formation of an anomalous gas cloud. Once we've established the presence of the cloud in the latter images, we determine the origin of the cloud in the earlier ones and track its propagation. Gas usually expands from point sources and it is difficult to know whether it is significant when it occupies merely a few pixels in the image. After the gas size expands, it is easier to analyze as an interesting anomalous feature. Our algorithm includes techniques such as the improved K-Means classification, Spectral Angle Mapper (SAM), match filter and tracking; in the paper we will show results based on real data taken by the "FIRST" camera (Field-portable Imaging Radiometric Spectrometer Technology).