https://doi.org/10.1088/2515-7620/acc56d

Marsh C.B., Harder P., Pomeroy J.W. (2023). Validation of FABDEM, a global bare-earth elevation model, againstUAV-lidar derived elevation in a complex forested mountain catchment. Environmental Research Communications.

Space-based, global-extent digital elevation models (DEMs) are key inputs to many Earth sciences applications. However, many of these applications require the use of a ‘bare-earth’ DEM versus a digital surface model (DSM), the latter of which may include systematic positive biases due to tree canopies in forested areas. Critical topographic features may be obscured by these biases. Vegetation-free datasets have been created by using statistical relationships and machine learning to train on local-scale datasets (e.g., lidar) to debias the global-extent datasets. Recent advances in satellite platforms coupled with an increased availability of computational resources and lidar reference products has allowed for a new generation of vegetation- and urban-canopy removals. One of these is the Forest And Buildings removed Copernicus DEM (FABDEM), based on the most recent and most accurate global DSM Copernicus-30. Amongst the more challenging landscapes to quantify surface elevations are dense forested mountain catchments where even airborne lidar applications struggle to capture surface returns. The increasing affordability and availability of UAV-based lidar platforms has resulted in new capacity to fly modest spatial extents with unrivalled point densities. These data allow an unprecedented ability to validate global sub-canopy DEMs against representative UAV-based lidar data. In this work, the FABDEM is validated against an up-scaled lidar data in a steep and forested mountain catchment considering elevation, slope, and Terrain Position Index (TPI) metrics. Comparisons of FABDEM with SRTM, MERIT, and the Copernicus-30 dataset are made. It was found that the FABDEM had a 24% reduction in elevation RMSE and 135% reduction in bias compared to the Copernicus-30 dataset. Overall, the FABDEM provides a clear improvement over existing de-forested DEM products in complex mountain topography such as the MERIT DEM. This study supports the use of FABDEM in forested mountain catchments as the current best-in-class data product.

Key Points
-Reproducible, transparent modeling increases confidence in model simulations and requires careful tracking of all model configuration steps
-We show an example of model configuration code applied globally that is traced and shared through a version control system
-Standardizing file formats and sharing of code can increase efficiency and reproducibility of modeling studies

Modelling-Core, Refereed Publications

https://doi.org/10.1088/2515-7620/acc56d