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Digital elevation model correction in urban areas using extreme gradient boosting, land cover and terrain parameters
The accuracy of digital elevation models (DEMs) in urban areas is influenced by numerous factors including land cover and terrain
irregularities. Moreover, building artefacts in global DEMs cause artificial blocking of surface flow pathways. This compromises
their quality and adequacy for hydrological and environmental modelling in urban landscapes where precise and accurate terrain
information is needed. In this study, the extreme gradient boosting (XGBoost) ensemble algorithm is adopted for enhancing the
accuracy of two medium-resolution 30-metre DEMs over Cape Town, South Africa: Copernicus GLO-30 and ALOS World 3D
(AW3D). XGBoost is a scalable, portable and versatile gradient boosting library that can solve many environmental modelling
problems. The training datasets are comprised of eleven predictor variables including elevation, urban footprints, slope, aspect,
surface roughness, topographic position index, terrain ruggedness index, terrain surface texture, vector roughness measure, forest
cover and bare ground cover. The target variable (elevation error) was calculated with respect to highly accurate airborne LiDAR.
After training and testing, the model was applied for correcting the DEMs at two implementation sites. The corrections achieved
significant accuracy gains which are competitive with other proposed methods. There was a 46 – 53% reduction in the root mean
square error (RMSE) of Copernicus DEM, and a 72 - 73% reduction in the RMSE of AW3D DEM. These results showcase the
potential of gradient-boosted decision trees for enhancing the quality of global DEMs, especially in urban areas.
Description:
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVIII-4/W9-2024
GeoAdvances 2024 – 8th International Conference on GeoInformation Advances, 11–12 January 2024, Istanbul, Türkiye.
LIDAR data for the
City of Cape Town was provided by the Information and
Knowledge Management Department, City of Cape Town.