Hybrid model for estimating forest canopy heights using fused multimodal spaceborne LiDAR data and optical imagery

Abstract

The forest canopy height is a key indicator for measuring global forest carbon stocks. Spaceborne LiDAR, a satellite remote sensing technology, plays an essential role in large-scale canopy height estimations. However, there are still some problems with existing methods of the spaceborne LiDAR canopy height estimates: the retrieval accuracy is degraded by the topographic relief and vegetation cover, as well as uneven spatial distribution of mapping height uncertainties. In this paper, we investigated the possibility of fusing multimodal spaceborne LiDAR and optical images to improve these above problems. We proposed a hybrid model fusing spaceborne full-waveform and photon-counting LiDAR data with optical imagery. Specifically, our approach divided the regional extent into multiple fusion patterns based on the spatial distribution of the LiDAR footprints in an object-oriented method. We then constructed canopy height models corresponding to each pattern and finally integrated the model results using a weighting scheme considering geospatial distances. We used GEDI (full-waveform LiDAR), ICESat-2 (photon-counting LiDAR) and Sentinel-2 (optical imagery) products as the input data and validated the model accuracy in four representative biomes of global forest ecosystems (i.e., evergreen broadleaf forests, deciduous broadleaf forests, savannas and coniferous forests). The experimental results demonstrated that fusing multisource spaceborne LiDAR data and optical images can not only enhance the canopy height estimation accuracy (R2 0.65 ∼ 0.90 and RMSE 0.57 ∼ 4.15 m in four biomes) but also maintain stable accuracy under undulating slope and large vegetation cover. Moreover, the uncertainty of canopy height estimation was low (meanerror −0.20 ∼ 0.03 m) and uniformly distributed in space (stdev 0.71 ∼ 4.45 m). We also compared the performances with two other advanced canopy height models, as well as two global canopy height products, and our model showed significant advantages in each test region. Our study demonstrates the effectiveness of fusing multimodal spaceborne LiDAR data and optical imagery for canopy height estimation accuracy improvement.