In this article, we validate Ice, Cloud, and Land Elevation Satellite2 (ICESat-2)-derived interpolated terrain elevations (h_te_interp), top of canopy elevations (h_canopy_abs), and estimated canopy heights (h_canopy) in dense tropical forests of Mexico, Belize, Guatemala, and Honduras. Data from close to 30 000 ICESat-2 ATL-08 segments are compared against parameters derived from high-density (>15 pulses/m 2 ) topographic airborne lidar (HDL) data from seven different sites with a variety of forest structure and terrain conditions, totaling 3742 km 2 of validated area. Our results indicate that in these high closure forests the range of errors (within the 5th to 95th percentiles) for these parameters vary widely, but their median and interquartile range (IQR) grow proportionally to the HDL-derived reference canopy height (rCH). The errors in h_te_interp retrieval grow in proportion to the rCH from ±2.5 m for areas with fairly low rCH (5-10 m) all the way to −10 to 24 m for areas with rCH of 40-45 m. The median of h_te_interp errors also grows proportionally to rCH and is consistently overestimated with regards to the reference. With respect to h_canopy_abs, it was observed that the errors also grow with increasing rCH but a much lower rate; the IQR is generally constrained between −5.5 and 6.0 m, while the median remains mostly uniform and independent of the rCH and underestimates the reference by −0.5-−2.0 m. The IQR of the errors in h_canopy normalized to rCH exhibits a mostly uniform behavior across the range of rCH between −33.5% and 7.0%, with the median fluctuating around an underestimation level of -16.5%.
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