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Guo, F., Shen, X., Zou, L., Ren, Y., Qin, Y., Wang, X. and Wu, J. (2015) Cloud Detection Method Based on Spectral Area Ratios in MODIS Data. Canadian Journal of Remote Sensing, 41, 561-576.
https://doi.org/10.1080/07038992.2015.1112729

has been cited by the following article:

• TITLE: Efficient Application of the Radiance Enhancement Method for Detection of the Forest Fires Due to Combustion-Originated Reflectance

  AUTHORS: Rehan Siddiqui, Rajinder K. Jagpal, Sanjar M. Abrarov, Brendan M. Quine

  KEYWORDS: Radiance Enhancement, Clouds, Forest Fire, Radiative Transfer Model, Line-By-Line Calculation, Micro-Spectrometer

  JOURNAL NAME: Journal of Environmental Protection, Vol.12 No.10, October 21, 2021

  ABSTRACT: The existing methods for detection of the cloud scenes are applied at relatively small spectral range within shortwave upwelling radiative wavelength flux. We have reported a new method for detection of the cloud scenes based on the Radiance Enhancement (RE). This method can be used to cover a significantly wider spectral range from 1100 nm to 1700 nm by using datasets from the space-orbiting micro-spectrometer Argus 1000. Due to high sunlight reflection of the smoke originated from the forest or field fires the proposed RE method can also be implemented for detection of combustion aerosols. This approach can be a promising technique for efficient detection and continuous monitor of the seasonal forest and field fires. To the best of our knowledge this is the first report showing how a cloud method can be generalized for efficient detection of the forest fires due to combustion-originated reflectance.