AUTOMATED ROAD BREACHING TO ENHANCE EXTRACTION OF NATURAL DRAINAGE NETWORKS FROM ELEVATION MODELS THROUGH DEEP LEARNING

6 citations as recorded by crossref.

1. Automated Mapping of Transportation Embankments in Fine-Resolution LiDAR DEMs N. Van Nieuwenhuizen et al. 10.3390/rs13071308
2. Classification of drainage crossings on high-resolution digital elevation models: A deep learning approach D. Wu et al. 10.1080/15481603.2023.2230706
3. GeoAI in the US Geological Survey for topographic mapping E. Usery et al. 10.1111/tgis.12830
4. Extracting a Connected River Network from DEM by Incorporating Surface River Occurrence Data and Sentinel-2 Imagery in the Danjiangkou Reservoir Area L. Lu et al. 10.3390/rs15041014
5. Deep learning methods applied to digital elevation models: state of the art J. Ruiz-Lendínez et al. 10.1080/10106049.2023.2252389
6. Drainage ditch network extraction from lidar data using deep convolutional neural networks in a low relief landscape L. Du et al. 10.1016/j.jhydrol.2023.130591