Consistency analysis of forest height retrievals between GEDI and ICESat-2

Abstract

Two space-borne LiDAR missions (Global Ecosystem Dynamics Investigation, GEDI; Ice, Cloud, and land Elevation Satellite-2, ICESat-2) have unique advantages in retrieving forest heights. Fusing these two missions will greatly increase the number of forest height samples and realize their geographical complementarity, providing unprecedented opportunities for global forest height mapping. However, ICESat-2 and GEDI use different LiDAR technologies, which may lead to inconsistencies in the forest height estimation between the two missions. This study aims to explore the potential of obtaining consistent forest heights from ICESat-2 and GEDI data in support of global forest height mapping. First, the accuracies of GEDI and ICESat-2 forest heights in four different scenarios (nigh/daytime and strong/weak beam) were validated and compared utilizing airborne LiDAR data. Second, we quantitatively evaluated the differences in the forest heights derived from the GEDI and ICESat-2 data within their overlapping footprints and analyzed the effects of the terrain slope, forest coverage, forest type and study site on these differences. Third, the forest height consistency models were built based on GEDI-derived forest heights and ICESat-2 feature parameters using stepwise regression (SR) and random forest (RF) algorithms as well as a combination of both SR and RF algorithms. Finally, we evaluated the transferability of forest height consistency models to different forest types and study sites, and further analyzed the potential of building a universally consistent model. The results showed that the accuracies of both GEDI and ICESat-2 derived forest heights differ among four different scenarios, and the accuracy of forest heights extracted from GEDI data (R2 = 0.93, RMSE = 2.99 m for power beams at night) is higher than that extracted from ICESat-2 data (R2 = 0.78, RMSE = 4.62 m for strong beams at night) regardless of scenarios. The forest height differences exist between these two missions, and show an apparent change trend with increasing forest coverage. By establishing the consistency models, the forest height difference between GEDI and ICESat-2 can be reduced. Compared to the forest height consistency models built by SR or RF algorithms, the consistency models established by combining the RF and SR algorithms have higher accuracy (average R2 = 0.86, RMSE = 2.56 m for ATL08). Additionally, the consistency models developed specifically for one forest type or study site are less transferable, while a universal consistency model is applicable for various vegetation types and study sites. After building a universal consistency model based on both SR and RF algorithms, the consistent forest heights were obtained from GEDI and ICESat-2 data. Overall, this study demonstrates the possibility of combining different modes of space-borne LiDAR data to obtain consistent forest height datasets.