AVIRIS-NG-like smart virtual remote sensing via spectra-aware physics informed GANs

This paper aims to create a physics informed virtual replica of the hyperspectral image captured by NASA’s Airborne Visible InfraRed Imaging Spectrometer - Next Generation (AVIRIS-NG) sensor equipped on manned aircraft. Few image samples are selected from study site around New Mexico, USA from flight mission ran in 2019. Out of 425 bands, 8 bands are utilized. For each band, reflectance spectra are chosen from United States Geological Survey (USGS) based on site specific geographical features. These spectras are infused during the image generation process with the correction check using matched filters. Moreover, we include the methane plumes along with other closely related hydrocarbons during the image generation process. Generative Adversarial Networks (GANs) architecture is employed with physics informed loss function for generating realistic and physically plausible images. Additionally, we also propose a new light weight dataset for creating the virtual replica of the AVIRIS-NG sensor on selected 8 bands in the visible light spectrum and the short-wave infrared region.