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The Geoscience Laser Altimeter System (GLAS) onboard the Ice, Cloud, and land Elevation satellite (ICESat) provides a useful dataset for characterizing tropical forests. However, some GLAS data are not viable for science processing. This work aims at quantifying GLAS data viability at a global scale over all tropical forests and determining the parameters that affect this viability. The percentage of nonviable data was analyzed according to several parameters: latitude, longitude, transmitted energy, GLAS mission, local hour of acquisition, and cloud parameters. Results show that only 79.9% of all GLAS data acquired between 2003 and 2009 is viable for tropical forests characterization. By applying additional filters used by scientists in the GLAS data processing for forestry applications, only 32.8% of GLAS data acquired over tropical forests becomes exploitable. The percentage of nonviable data seems higher over the equator, for low transmitted energy, for acquisition time between 10 and 13 local hour, for high cloud humidity, and for some geographical areas. Finally, in a multifactor approach, the Random Forest regression method demonstrated that the parameters that most significantly influence the returned LiDAR signal are transmitted energy and cloud presence index.