Landslide Monitoring Based on Geospatial Technologies Integration: A Case Study of the Southwest Arabian Peninsula

Landslide monitoring is a challenging problem faced by different services for territory management, infrastructure development, and safety management. Apart from the threats t...that landslides create for people and urban facilities, their collapses have a significant socioeconomic impact. This is why landslide monitoring is essential for management in urban and suburban territories. The southwest territories of the Kingdom of Saudi Arabia are characterized by plenty of landslides that are classified as having low or medium threats. The ongoing Kingdom’s program for infrastructure development must account for the possible threats of landslide development and their collapses. Estimation of the landslide stability by monitoring results is one of the top goals of disaster prevention. Recently, new monitoring methods and technologies have been developed. Integrating terrestrial and satellite technologies has allowed for achieving a prominent accuracy and quality of monitoring. The satellite-based remote sensing data occasionally provide the necessary information for monitoring. However, the vegetation or heavy rains may hamper the precise monitoring, while the low frequency of image updates can lead to data gaps. Thus, satellite data must be accompanied by terrestrial observations. Terrestrial and satellite technologies, such as satellite radar interferometry, UAV lidar scanning, and UAV photogrammetry, will ensure a reliable solution for the monitoring task. State-of-the-art landslide susceptibility estimation and forecasting methods are based on the latest achievements in mathematics and physics. Among the various approaches, machine learning methods, structural mechanics, and fuzzy logic are worth mentioning. The central premise of the correct model construction is the proper interpretation of the obtained values. The measurement results may mislead researchers and make them accept the wrong decision. For such a complex problem as landslide monitoring, finding a single model describing the deformation process is often impossible. The reason is the complexity of an even small landslide to which different points may undergo displacements with different values and directions. Therefore, the prediction of landslide activity is also a challenging task. The study will comprise the data analysis of precise geospatial technologies, InSAR and UAV photogrammetry, for examining landslides. The research includes geological data and models of geodynamics. These data will be integrated with geospatial data for prediction model creation. The suggested research is an excellent opportunity to develop, test, and disseminate various math models. Among those are machine learning, group method for data handling, and structural mechanics, particularly the finite element method. The output is an invaluable contribution to the problem of landslide prediction and respective protection measures organization.