Landslides

Landslides - Investigation and Monitoring offers a comprehensive overview of recent developments in the field of mass movements and landslide hazards. Chapter authors use in situ measurements, modeling, and remotely sensed data and methods to study landslides. This book provides a thorough overview of the latest efforts by international researchers on landslides and opens new possible research directions for further novel developments

Soil-Water Conservation, Erosion, and Landslide

The predicted climate change is likely to cause extreme storm events and, subsequently, catastrophic disasters, including soil erosion, debris and landslide formation, loss of life, etc. In the decade from 1976, natural disasters affected less than a billion lives. These numbers have surged in the last decade alone. It is said that natural disasters have affected over 3 billion lives, killed on average 750,000 people, and cost more than 600 billion US dollars. Of these numbers, a greater proportion are due to sediment-related disasters, and these numbers are an indication of the amount of work still to be done in the field of soil erosion, conservation, and landslides. Scientists, engineers, and planners are all under immense pressure to develop and improve existing scientific tools to model erosion and landslides and, in the process, better conserve the soil. Therefore, the purpose of this Special Issue is to improve our knowledge on the processes and mechanics of soil erosion and landslides. In turn, these will be crucial in developing the right tools and models for soil and water conservation, disaster mitigation, and early warning systems

Novel Approaches in Landslide Monitoring and Data Analysis

Significant progress has been made in the last few years that has expanded the knowledge of landslide processes. It is, therefore, necessary to summarize, share and disseminate the latest knowledge and expertise. This Special Issue brings together novel research focused on landslide monitoring, modelling and data analysis

Application of different watershed units to debris flow susceptibility mapping: A case study of Northeast China

The main purpose of this study was to compare two types of watershed units divided by the hydrological analysis method (HWUs) and mean curvature method (CWUs) for debris flow susceptibility mapping (DFSM) in Northeast China. Firstly, a debris flow inventory map consisting of 129 debris flows and 129 non-debris flows was randomly divided into a ratio of 70% and 30% for training and testing. Secondly, 13 influencing factors were selected and the correlations between these factors and the debris flows were determined by frequency ration analysis. Then, two types of watershed units (HWUs and CWUs) were divided and logistic regression (LR), multilayer perceptron (MLP), classification and regression tree (CART) and Bayesian network (BN) were selected as the evaluation models. Finally, the predictive capabilities of the models were verified using the predictive accuracy (ACC), the Kappa coefficient and the area under the receiver operating characteristic curve (AUC). The mean AUC, ACC and Kappa of four models (LR, MLP, CART and BN) in the training stage were 0.977, 0.931, and 0.861, respectively, for the HWUs, while 0.961, 0.905, and 0.810, respectively, for the CWUs; in the testing stage, were 0.904, 0.818, and 0.635, respectively, for the HWUs, while 0.883, 0.800, and 0.601, respectively, for the CWUs, which showed that HWU model has a higher debris flow prediction performance compared with the CWU model. The CWU-based model can reflect the spatial distribution probability of debris flows in the study area overall and can be used as an alternative model

Remote Sensing of the Oceans

This book covers different topics in the framework of remote sensing of the oceans. Latest research advancements and brand-new studies are presented that address the exploitation of remote sensing instruments and simulation tools to improve the understanding of ocean processes and enable cutting-edge applications with the aim of preserving the ocean environment and supporting the blue economy. Hence, this book provides a reference framework for state-of-the-art remote sensing methods that deal with the generation of added-value products and the geophysical information retrieval in related fields, including: Oil spill detection and discrimination; Analysis of tropical cyclones and sea echoes; Shoreline and aquaculture area extraction; Monitoring coastal marine litter and moving vessels; Processing of SAR, HF radar and UAV measurements

Advances in Remote Sensing-based Disaster Monitoring and Assessment

Remote sensing data and techniques have been widely used for disaster monitoring and assessment. In particular, recent advances in sensor technologies and artificial intelligence-based modeling are very promising for disaster monitoring and readying responses aimed at reducing the damage caused by disasters. This book contains eleven scientific papers that have studied novel approaches applied to a range of natural disasters such as forest fire, urban land subsidence, flood, and tropical cyclones

Bridges Structural Health Monitoring and Deterioration Detection Synthesis of Knowledge and Technology

INE/AUTC 10.0

Multi-scale analyses of granular flows for disaster resilience enhancement

A study that overlaps the fundamentals of granular flows with human responses to disasters at the community or regional scale is considered to be a strategic approach that advances existing methods in natural and human-induced hazard research in light of global-scale changes in earth systems. This study aims to improve the understanding: 1) on the mechanical behaviors of fluidized loess flowslide using centrifuge modeling as well as in-house designed laboratory testing and elastic wave characterization techniques (i.e. natural systems), and 2) on the cascading impacts of geohazards on local communities, assessing disaster resilience associated with reconstruction strategies and the performance of debris flow mitigation systems (i.e. natural-human systems interactions). The current work reveals the state-dependent effects of structure on flow behavior of loess and proposes modified criteria to predict the flow behavior. Laboratory tests show the changes in the mechanical behavior due to decementation of loess and indicate the needs to study loess within the scope of geotechnical analysis. The failure mechanism of loess flowslide is better understood from the study on the deformation process that shows the compounding effects of increasing pore-water pressure and reducing confining stresses on static liquefaction. The earthquake and post-earthquake impacts are documented after the 2008 Wenchuan earthquake, which permits a pilot study on quantifying the recovery processes of two communities of different reconstruction modes in light of Bayesian-based learning method. The design and performance of post-earthquake debris flow mitigation systems are reviewed; it offers a simple and robust data-driven approach to evaluate the effectiveness of debris flow mitigation systems at the regional scale.Ph.D