A recent study published in Remote Sensing demonstrates multi-dated data from terrestrial laser scanning surveys and unmanned aerial vehicle (UAV) operations for accurate and immediate monitoring of a landslide. This technique provides operational information about the stability of the landslide to the local establishments.
UAV and terrestrial laser scanning point clouds were produced by processing the obtained data. The monitoring and evaluation of the landslide were conducted based on the detection of instability events between the multi-dated UAV and terrestrial laser scanning point clouds utilizing the estimation of the deviation and direct cloud-to-cloud comparison.
Harmful Effects of Landslides
Landslides are one of the most deadly and devastating tragedies in the world. They happen unexpectedly and can harm the environment, infrastructure, or human life. Model-based estimates predict that rising temperatures associated with climate change cause landslides to occur more frequently.
Remote Sensing Technology for Monitoring Landslides
Numerous researchers have studied landslides over the years, and numerous techniques based on mapping landslide vulnerability, risk analysis, or hazard zoning have been produced.
Landslide annotations have become more immediate, affordable, and systematic owing to advancements in remote sensing technologies.
Novel opportunities for accurately studying broad or difficult-to-reach landslides have been developed. Innovative approaches built on various remote sensing data are vital resources for landslide risk assessment and mitigation.
Potential of UAVs in Detecting Landslides
Unmanned aerial vehicle (UAV) utilization represents a significant advancement for landslide research and Earth observation. The initial methods relied on using UAVs equipped with small cameras to quickly identify landslides. UAVs equipped with primary single-lens cameras are subsequently employed to record and keep track of significant earth flows.
Time series of UAV images are subjected to the Structure from Motion (SfM) approach processing. The results are used to quantify surface deformation, measure landslide volumetric change, and determine the landslide dynamics.
Estimating the area's evolution using UAV data enables a compelling valuation of residual risk on a medium to long-term scale.
UAV imagery and digital photogrammetry have been effective in helping to record slope conditions, improve our understanding of landslide processes, and accurately estimate slope instabilities. Using UAVs and machine learning algorithms for monitoring landslide risk areas and removing landslide susceptibility maps lead to the emergence of new and more creative methods for landslide investigation.
Light Detection and Ranging (LiDAR) Technology for Landslide Investigations
Light Detection and Ranging (LiDAR) technology is another frequently used instrument for numerous geotechnical research and landslide assessments. Airborne LiDARs are effective in the accurate representation of the surface, the monitoring of landslide dynamics, recognition of various types of mass movements, as well as the organization of slow-moving landslides in heavily vegetated areas.
Airborne LiDAR for landslide research is costly. Terrestrial LiDAR (TLS) surveys offer data with a higher temporal and spatial resolution at a lower cost. A general review of terrestrial laser scanning data processing and acquisition regarding the volume estimate, characterization, and monitoring of rock slopes has been developed.
Development of Multi-Dated Data for Accurate and Immediate Monitoring of Landslides
Integrating a range of remote sensing data is a unique viewpoint for a more thorough landslide investigation. Ground-based techniques, such as Ground-Based Interferometric SAR and terrestrial laser scanning can be combined with UAV imagery and spaceborne satellite data (high-resolution multispectral and radar images) to map, identify, and monitor landslides, which vary in their failure mechanisms, characteristics, spatial distribution, evolution processes, and risk of instability.
Examining the landslide's activity and estimating its kinematic evolution can be accomplished efficiently by combining UAV data with airborne LiDAR data or terrestrial laser scanning surveys.
Kyriou et al. congregated multi-dated data from terrestrial laser scanning and unmanned aerial vehicle (UAV) scans to accurately and quickly monitor a landslide to give local authorities operational information about the stability of the landslide.
UAV and terrestrial laser scanning field campaigns require only travel costs to the research region, making them reliable and reasonably priced tools for continuously monitoring tiny (ten meters) to moderate (hundreds of meters) active landslides.
The resultant data was correctly processed in this framework, and both UAV-based and terrestrial laser scanning point clouds were produced. Monitoring and evaluating the landslide’s evolution were conducted based on detecting instability events between the multi-dated UAV and terrestrial laser scanning point clouds utilizing the estimation of the deviation and direct cloud-to-cloud comparison.
The study's primary goal was to provide operational data on the stability of an environmentally sensitive area to local authorities for risk minimization. The intersection between surface sections and direct cloud-to-cloud comparison were used as change detection techniques.
The general evolution of the landslide can be divided into two sub-periods, one corresponding to human activity and the other resulting from ongoing natural processes.
The results of the terrestrial laser scanning and photogrammetric processing were similar. For the initial monitoring period, the most significant surface changes that could be distinguished in UAV/terrestrial laser scanning point clouds ranged from 1.5 to 1.7 meters. The second monitoring period revealed minor local surface changes (0.20 m–0.30 m) in the sliding area linked to natural processes. The use of terrestrial laser scanning-based point clouds appeared to be more effective for the quick and exact monitoring of the evolution of the landslide.
However, a hybrid strategy for enhancing the spatial coverage and point density of UAV-based point clouds could be suggested by integrating the usage of UAV and TLS data. This low-cost methodology will eventually be used as a guide for monitoring complex or sensitive sites or the quick detection of deformations brought on by natural disasters or human activity.
Kyriou, A., Nikolakopoulos, K. G., & Koukouvelas, I. K. (2022) Timely and Low-Cost Remote Sensing Practices for the Assessment of Landslide Activity in the Service of Hazard Management. Remote Sensing, 14(19), 4745. https://www.mdpi.com/2072-4292/14/19/4745