Flare Parameters Estimation from VIIRS NtL Remote Sensing Data: Improving Classical Approach by Spectral Unmixing

Researchers in the oil and gas industry, academia and governments use different approaches for determining ways to measure and significantly reduce gas flaring and its emissions. However, the lack of a unique method poses a continuing problem in determining the impacts and roles of these in environmental degradation on both local and global levels. Satellite sensors are an attractive option for local and global monitoring of gas flares, particularly Night time Light (NtL) satellite data. Indeed, it is possible to extract, from NtL data, some physical parameters of flames produced by gas flares, and these parameters can later be used to estimate the annual volumes of gas flared and will make it possible to achieve greenhouse gas reduction goals. In this work, two approaches are used to estimate such parameters (temperature, emissivity and power radiated by flare gas) from, publicly available, NtL Visible Infrared Imaging Radiometer Suite (VIIRS) data. The second approach, based on spectral unmixing applied on the considered NtL VIIRS data, is expected to improve, by providing a pure spectrum of flames, obtained results by the classical one, which uses Planck law curve modeling applied on the considered observed mixed data.