  The description, imagery and interpretation of cloud scenes by remote sensing
datasets from Earth-orbiting satellites have become a great debate for several
decades. Presently, there are many models for cloud detection and its
classifications have been reported. However, none of the existing models can
efficiently detect the clouds within the small band of shortwave upwelling
radiative wavelength flux (SWupRF) in the spectral range from 1100 to 1700 nm.
Therefore, in order to detect the clouds more effectively, a method known as
the radiance enhancement (RE) can be implemented (Siddiqui et al., 2015). This
article proposes new approaches how with RE and SWupRF methods to distinguish
cloud scenes by space orbiting Argus 1000 micro-spectrometer utilizing the
GENSPECT line-by-line radiative transfer model (Quine and Drummond, 2002;
Siddiqui, 2017). This RE approach can also be used within the selected
wavelength band for the detection of combustion-originated aerosols due to
seasonal forest fires.
