Assessment of Shoreline Transformation Rates and Landslide Monitoring on the Bank of Kuibyshev Reservoir (Russia) Using Multi-Source Data

This study focuses on the Kuibyshev reservoir (Volga River basin, Russia)-the largest in. The objective of this paper is to quantitatively assess the dynamics of reservoir bank landslides and shoreline abrasion at active zones based on the integrated use of modern instrumental methods (i.e., terrestrial laser scanning-TLS, unmanned aerial vehicle-UAV, and a global navigation satellite system-GNSS) and GIS analysis of historical imager

Review article: The use of remotely piloted aircraft systems (RPAS) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of Remotely Piloted Aircraft Systems (RPAS) for the management of natural hazards effects and the identification of occurred damages are strongly increased in last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPAS can acquire on-demand ultra-high resolution images that can be used for the identification of active processes like landslides or volcanic activities but also for the definition of effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologiesdeveloped for the study and monitoring of natural hazards

Review article: The use of remotely piloted aircraft systems (RPASs) for natural hazards monitoring and management

The number of scientific studies that consider possible applications of remotely piloted aircraft systems (RPASs) for the management of natural hazards effects and the identification of occurred damages strongly increased in the last decade. Nowadays, in the scientific community, the use of these systems is not a novelty, but a deeper analysis of the literature shows a lack of codified complex methodologies that can be used not only for scientific experiments but also for normal codified emergency operations. RPASs can acquire on-demand ultra-high-resolution images that can be used for the identification of active processes such as landslides or volcanic activities but can also define the effects of earthquakes, wildfires and floods. In this paper, we present a review of published literature that describes experimental methodologies developed for the study and monitoring of natural hazard

Progress in Landslide Research and Technology, Volume 1 Issue 2, 2022

This open access book provides an overview of the progress in landslide research and technology and is part of a book series of the International Consortium on Landslides (ICL). It gives an overview of recent progress in landslide research and technology for practical applications and the benefit for the society contributing to understanding and reducing landslide disaster risk

Micro air vehicles energy transportation for a wireless power transfer system

The aim of this work is to demonstrate the feasibility use of an Micro air vehicles (MAV) in order to power wirelessly an electric system, for example, a sensor network, using low-cost and open-source elements. To achieve this objective, an inductive system has been modelled and validated to power wirelessly a sensor node using a Crazyflie 2.0 as MAV. The design of the inductive system must be small and light enough to fulfil the requirements of the Crazyflie. An inductive model based on two resonant coils is presented. Several coils are defined to be tested using the most suitable resonant configuration. Measurements are performed to validate the model and to select the most suitable coil. While attempting to minimize the weight at transmitter’s side, on the receiver side it is intended to efficiently acquire and manage the power obtained from the transmitter. In order to prove its feasibility, a temperature sensor node is used as demonstrator. The experiment results show successfully energy transportation by MAV, and wireless power transfer for the resonant configuration, being able to completely charge the node battery and to power the temperature sensor.Peer ReviewedPostprint (published version

Landslide Detection Using a Saliency Feature Enhancement Technique from LiDAR-Derived DEM and Orthophotos

© 2013 IEEE. This study proposes a new landslide detection technique that is semi-automated and based on a saliency enhancement approach. Unlike most of the landslide detection techniques, the approach presented in this paper is simple yet effective and does not require landslide inventory data for training purposes. It comprises several steps. First, it enhances potential landslide pixels. Then, it removes the image background using slope information derived from a very high-resolution LiDAR-based (light detection and ranging) digital elevation model (DEM). After that, morphological analysis was applied to remove small objects, separate landslide objects from each other, and fill the gaps between large bare soil objects and urban objects. Finally, landslide scars were detected using the Fuzzy C-means (FCM) clustering algorithm. The proposed method was developed based on datasets acquired over the Kinta Valley area in Malaysia and tested on another area with a different environment and topography (i.e., Cameron Highlands). The results showed that the proposed landslide detection technique could detect landslides in the training area with a Prediction Accuracy, Kappa index, and Mean Intersection-Over-Union (mIOU) of 71.12%, 0.81, and 68.52%, respectively. The Prediction Accuracy, Kappa index, and mIOU of the method based on the test dataset were 65.78%, 0.68, and 56.14%, respectively. These results show that the proposed method can be used for landslide inventory mapping and risk assessments

Multi-temporal digital twin method and application of landslide deformation monitoring: A case study on Baige landslide in Jinsha River

High-locality and hidden landslides, due to its significant characteristics of being difficult to access, identify, and monitor, have strong suddenness and destructiveness when they occur. Continuous monitoring and risk assessment of these landslides are of great significance. Traditional artificial ground survey methods and ground monitoring equipment have the characteristics of high risk, low efficiency, easy damage to equipment, and frequent offline false alarms. Thus, based on unmanned aerial vehicle (UAV) tilt photogrammetry, this study attempts to provide a digital twin method to characterize high-locality and hidden landslides by monitoring and analyzing the deformation and spatiotemporal evolution of geological disasters. This study uses UAV tilt photogrammetry technology to obtain 10 periods of aerial survey data of the Baige landslide on the Jinsha River in Tibet as the research area from April 2019 to September 2021. A multi-temporal digital twin landslide body is constructed, and high-precision quantitative monitoring of multi-dimensional factors, such as the overall sliding characteristics, local micro deformation, and collapse volume of the Baige landslide, is achieved, which are applied to the monitoring and warning of Baige landslide. The results show that there are signs of continuous deformation in the Baige landslide during the monitoring period from 2019 to 2021, and strong deformation mainly occurs at both sides and rear edges of the landslide, gradually expanding, and posing a risk of collapse and river blockage. The multi-temporal digital twin method and application of landslide deformation monitoring on qualitative and quantitative characteristics description and risk assessment of geological disasters are further analyzed. The method in this study has the advantages of fast and flexible, comprehensive coverage, and not limited by complex and dangerous terrain conditions, which could provide information for the large gradient deformation monitoring and engineering practice of slope disasters, such as high-locality and hidden landslides

Remote Sensing of Natural Hazards

Each year, natural hazards such as earthquakes, cyclones, flooding, landslides, wildfires, avalanches, volcanic eruption, extreme temperatures, storm surges, drought, etc., result in widespread loss of life, livelihood, and critical infrastructure globally. With the unprecedented growth of the human population, largescale development activities, and changes to the natural environment, the frequency and intensity of extreme natural events and consequent impacts are expected to increase in the future.Technological interventions provide essential provisions for the prevention and mitigation of natural hazards. The data obtained through remote sensing systems with varied spatial, spectral, and temporal resolutions particularly provide prospects for furthering knowledge on spatiotemporal patterns and forecasting of natural hazards. The collection of data using earth observation systems has been valuable for alleviating the adverse effects of natural hazards, especially with their near real-time capabilities for tracking extreme natural events. Remote sensing systems from different platforms also serve as an important decision-support tool for devising response strategies, coordinating rescue operations, and making damage and loss estimations.With these in mind, this book seeks original contributions to the advanced applications of remote sensing and geographic information systems (GIS) techniques in understanding various dimensions of natural hazards through new theory, data products, and robust approaches

Characterization and Analysis of Landslide Evolution in Intramountain Areas in Loja (Ecuador) Using RPAS Photogrammetric Products

This case study focuses on the area of El Plateado near the city of Loja, Ecuador, where landslides with a high impact on infrastructures require monitoring and control. The main objectives of this work are the characterization of the landslide and the monitoring of its kinematics. Four flights were conducted using a remotely piloted aerial vehicle (RPAS) to capture aerial images that were processed with SfM techniques to generate digital elevation models (DEMs) and orthoimages of high resolution (0.05 m) and sufficient accuracy (below 0.05 m) for subsequent analyses. Thus, the DEM of differences (DoD) and profiles are obtained, but a morphometric analysis is conducted to quantitatively characterize the landslide's elements and study its evolution. Parameters such as slope, aspect, topographic position index (TPI), terrain roughness index (TRI), and topographic wetness index (TWI) are analyzed. The results show a higher slope and roughness for scarps compared to stable areas and other elements. From TPI, slope break lines have been extracted, which allow the identification of landslide features such as scarps and toe tip. The landslide shows important changes in the landslide body surface, the retraction of the main scarp, and advances of the foot. A general decrease in average slope and TRI and an increase in TWI are also observed due to the landslide evolution and stabilization. The presence of fissures and the infiltration of rainfall water in the unsaturated soil layers, which consist of high-plasticity clays and silts, contribute to the instability. Thus, the study provides insights into the measurement accuracy, identification and characterization of landslide elements, morphometric analysis, landslide evolution, and the relationship with geotechnical factors that contribute to a better understanding of landslides. A higher frequency of the RPAS surveys and quality of geotechnical and meteorological data are required to improve the instability analysis together with a major automation of the GIS procedures.Private Technical University of Loja PROY_GMIC_128