Maestri, T. and Holz, R.E. (2009) Retrieval of Cloud Optical Properties from Multiple Infrared Hyperspectral Measurements: A Methodology Based on a Line-By-Line Multiple-Scattering Code. IEEE Transactions on Geoscience and Remote Sensing, 47, 2413-2426.
https://doi.org/10.1109/TGRS.2009.2016105

has been cited by the following article:

• TITLE: New Cloud Detection Index (CDI) for Forecasting the Extreme Rain Events

  AUTHORS: Niket Shastri, Kamlesh Kamlesh Pathak

  KEYWORDS: Cloud Detection Index, Water Vapor, Remote Sensing

  JOURNAL NAME: Advances in Remote Sensing, Vol.8 No.1, March 11, 2019

  ABSTRACT: The water vapor content and clouds play a very significant role in atmospheric conditions. This paper is derived from the new cloud detection index (CDI) which is useful to forecast extreme weather events like heavy or extreme rain. The CDI is retrieved using two crucial elements of cloud formation, the critical humidity and critical water vapor. The cloud thickness is determined by using CDI for a radiosonde site (VABB) located in Mumbai, the western part of India. The obtained results are compared with the cloud thickness required for extreme rain. The outcome of the comparison is discussed in this paper. The cloud detection index is also useful in establishing the atmospheric stability along with another four atmospheric stability indices.