A Review of Data Sources and Techniques used for Landslide Visualization
DOI:
https://doi.org/10.11113/jagst.v3n2.74Keywords:
Visualization, Landslides, Slope Failures, Techniques, 3D Visualization, 2D VisualizationAbstract
Landslides are slope failure disasters threatening human life and destroying infrastructures. Landslides happen suddenly and cause huge losses. Landslide visualization can provide information and an overview of slope movement and landslides. This study reviews the visualization of landslides by analyzing literature published on this topic from 2018 until February 2023. This study used publications from the ‘Web of Science’ (WOS) and ‘Scopus’ in the last five years to get the latest information on this topic. This study has examined trends in the number of publications and sources of publication, study areas, visualization techniques and datasets used, and visualizations produced in either 2D or 3D. The number of publications shows an increasing trend, and the journal that publishes the most articles is ‘Remote Sensing’. Areas from China are often chosen as study areas in this topic, followed by Slovenia. There were 19 visualization techniques identified through the article, and Electrical Resistivity Tomography (ERT) was used frequently in 3 publications. Digital Elevation Model (DEM) data is used in most articles (8 articles) compared to the other 10 data, which are Digital Terrain Model (DTM), Knowledge Template, Electromagnetic VLF-R Data, Cloud Data of Discrete Points, Ground-Penetrating Radar (GPR) Data, Electric Resistivity Tomography (ERT) Data, Airborne Lidar, Target Ground Sampling Distance (GSD), Area of Interest, and in situ Data. Landslide visualization in 3D form is produced in most articles compared to 2D. The analysis shows a preference for 3D visualization over 2D, although both techniques are employed due to their unique advantages. The review exercise reveals a rising publication trend, highlighting the prominence of 3D visualization techniques and the popularity of DEM data in landslide visualization studies, while also suggesting the need for more recent and comprehensive research in this field.