Global Ecosystem Dynamics Investigate (GEDI) is a spaceborne laser altimeter system used for earth observation in many areas such as forest canopy, water level and terrain height estimation. GEDI data is affected by atmospheric effects due to the sensor used while observing. In this study, we propose a 7-step, multi-variable strategy for determining the elevation of the terrain with GEDI. These steps involve both different geoid models, GEDI ancillary data, and topographic features. We evaluated the effect of each step using high quality DEM data obtained by Airborne LiDAR over the central part of Puerto Rico, where building areas and forests are dominant, while the terrain has an average slope of 24%. The GEDI data of the test area consists of 3 different orbits (O06225, O07933, O08061) with different solar elevation and cloudiness rates. While the raw data of orbit O06225, obtained during a solar elevation of 8.4 and cloudy conditions, has a Root Mean Square Error (RMSE) of 418.67 m., the RMSE is reduced to 4.59 m. after applying all seven filtering steps. The raw data of orbit O07933, obtained with a solar elevation of 50.5 during cloud free conditions, has a RMSE of 10.04 m., and is reduced to a similar value of 4.8 m. as a result of the filtering steps. On the other hand, orbit O08061 was obtained with little clouds during a near-dawn solar elevation of -0.7. Its raw RMSE of 50,34 m could only be reduced to 12.41 m. by the proposed filtering procedure. It is concluded that although there are many outliers in data acquired during cloudy conditions, the accuracy of the data remaining after applying our filtering strategy can be as high as the accuracy obtained during cloud free conditions. Better results than 5 m were obtained according to the RMSE in areas with low solar elevation. In addition, it is observed that accuracy decreases strongly when the solar elevation is close to 0. Overall, it is concluded that appropriate filtering is required when determining terrain height with GEDI data.