Abstract
The goal of the study is to test a methodology that outputs continuous sets of data by integrating forest canopy height satellite measurements in a Random Forest (RF) algorithm. We assess the performance of the two spaceborne LiDAR missions by comparing them to field measurements taken with a mobile LiDAR scanner (MLS), then we test the compatibility of the sensors as an input for an RF model. The Spearman analysis showed a significant correlation between the MLS height and the GEDI height (p = 0.00015), but not for the ICEsat-2 height measurements (p = 0.3). The same analysis proved to be inconclusive for the RF output, where, although the p-value was 0.00025, the R value was only 0.38. Although the method studied in this paper proved to be only fit for estimation purposes, the integration of spaceborne LiDAR sensors in the RF shows high potential for obtaining homogenous, continuous sets of data.
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