Lidar Processing for Defining Sinkhole Characteristics under Dense Forest Cover: A Case Study in the Dinaric Mountains

12 citations as recorded by crossref.

1. The Impact of Digital Elevation Model Preprocessing and Detection Methods on Karst Depression Mapping in Densely Forested Dinaric Mountains R. Ciglič et al. https://doi.org/10.3390/rs14102416
2. Fabrication of Three-Dimensional Scanning System for Inspection of Massive Sinkhole Disaster Sites S. Kim et al. https://doi.org/10.7746/jkros.2020.15.4.341
3. Novel parameters for sinkhole mapping in the anthropocene: Example from a karst-dominated landscape of the Missouri Ozarks, USA T. Jerin et al. https://doi.org/10.1177/03091333251409572
4. A general method for searching customized depressions for large radio telescopes using digital elevation models S. Zhang et al. https://doi.org/10.1080/17538947.2026.2631243
5. Geomorphological Dating of Pleistocene Conglomerates in Central Slovenia Based on Spatial Analyses of Dolines Using LiDAR and Ground Penetrating Radar T. Čeru et al. https://doi.org/10.3390/rs9121213
6. Detection and automatic identification of loess sinkholes from the perspective of LiDAR point clouds and deep learning algorithm Z. Jiang et al. https://doi.org/10.1016/j.geomorph.2024.109404
7. Recharge landforms in a semi-confined karst aquifer revealed by geophysical and high-resolution UAV-based LiDAR surveys P. Assunção et al. https://doi.org/10.1016/j.geomorph.2026.110453
8. Morphometric properties of dolines in Matarsko podolje, SW Slovenia T. Verbovšek & L. Gabor https://doi.org/10.1007/s12665-019-8398-6
9. Enclosed Karst Depression Identification and Analysis for the Pumped Storage Power Station Reservoir Construction Using DEM Y. Bo et al. https://doi.org/10.1155/2023/4794665
10. Evaluating susceptibility of karst dolines (sinkholes) for collapse in Sango, Tennessee, USA P. Siska et al. https://doi.org/10.1177/0309133316638816
11. Data for the geoecology of solution karst dolines, with particular attention to climatic, soil and biogenic environment I. Bárány Kevei et al. https://doi.org/10.14232/acta.clim.2021.55.4
12. Detecting Terrain Stoniness From Airborne Laser Scanning Data † P. Nevalainen et al. https://doi.org/10.3390/rs8090720