Characterizing slope instability kinematics by integrating multi-sensor satellite remote sensing observations

Over the past few decades, the occurrence and intensity of geological hazards, such as landslides, have substantially risen due to various factors, including global climate change, seismic events, rapid urbanization and other anthropogenic activities. Landslide disasters pose a significant risk in both urban and rural areas, resulting in fatalities, infrastructure damages, and economic losses. Nevertheless, conventional ground-based monitoring techniques are often costly, time-consuming, and require considerable resources. Moreover, some landslide incidents occur in remote or hazardous locations, making ground-based observation and field investigation challenging or even impossible. Fortunately, the advancements in spaceborne remote sensing technology have led to the availability of large-scale and high-quality imagery, which can be utilized for various landslide-related applications, including identification, monitoring, analysis, and prediction. This efficient and cost-effective technology allows for remote monitoring and assessment of landslide risks and can significantly contribute to disaster management and mitigation efforts. Consequently, spaceborne remote sensing techniques have become vital for geohazard management in many countries, benefiting society by providing reliable downstream services. However, substantial effort is required to ensure that such benefits are provided. For establishing long-term data archives and reliable analyses, it is essential to maintain consistent and continued use of multi-sensor spaceborne remote sensing techniques. This will enable a more thorough understanding of the physical mechanisms responsible for slope instabilities, leading to better decision-making and development of effective mitigation strategies. Ultimately, this can reduce the impact of landslide hazards on the general public. The present dissertation contributes to this effort from the following perspectives: 1. To obtain a comprehensive understanding of spaceborne remote sensing techniques for landslide monitoring, we integrated multi-sensor methods to monitor the entire life cycle of landslide dynamics. We aimed to comprehend the landslide evolution under complex cascading events by utilizing various spaceborne remote sensing techniques, e.g., the precursory deformation before catastrophic failure, co-failure procedures, and post-failure evolution of slope instability. 2. To address the discrepancies between spaceborne optical and radar imagery, we present a methodology that models four-dimensional (4D) post-failure landslide kinematics using a decaying mathematical model. This approach enables us to represent the stress relaxation for the landslide body dynamics after failure. By employing this methodology, we can overcome the weaknesses of the individual sensor in spaceborne optical and radar imaging. 3. We assessed the effectiveness of a newly designed small dihedral corner reflector for landslide monitoring. The reflector is compatible with both ascending and descending satellite orbits, while it is also suitable for applications with both high-resolution and medium-resolution satellite imagery. Furthermore, although its echoes are not as strong as those of conventional reflectors, the cost of the newly designed reflectors is reduced, with more manageable installation and maintenance. To overcome this limitation, we propose a specific selection strategy based on a probability model to identify the reflectors in satellite images

Assessment of altimetric river water level time series densification methods

Nowadays, collecting and analysing water level time series recorded by gauging stations or by satellite altimetry is crucial for the geodetic and environmental purposes, such as modelling ocean circulation and monitoring climate change. Since the 1970s, a large number of gauging stations has been removed. This has made altimetry increasing more important. However, data collected by individual altimetric satellites are limited, i.e., the temporal resolution is limited to the repeat cycle of satellites, and the spatial resolution is constrained to the distribution of virtual stations. In order to overcome these limitations, methods have been developed to combine all available altimetric satellite missions along a river to construct a new densified time series. This is referred to as densification. To our knowledge, there are only two proven densification methods applied to the river for now. The first is a hydraulic statistic densification method developed by Tourian et al. (2016). The other is the kriging densification method published by Boergens et al. (2017). However, each of them is realized under different circumstances, which makes them incomparable with each other. In this work, we implement the two densification methods and apply them under similar conditions. The various densified water level time series are compared and analysed both visually and statistically. Results reveal different characteristics of the two densification methods

Analysis of helicopter-borne gravity gradiometry

Nowadays the FALCON partial tensor gravity gradiometer is the only applied AGG instrument to be used in a helicopter to collect high-resolution data for commercial demand. In order to know its principles and make full use of its advantages, in this study thesis, a helicopterborne gravity gradiometry data set offered by USGS is processed and analysed. It is interesting to figure out that whether the gradient tensor invariants are truly "invariant". Also through Fourier transformation, all gradient tensor components can be determined mathematically. Besides, the effects of terrain corrections and different flight line spacings and drape heights are also concerned to obtain high-resolution data in the easiest way

The June 2020 Aniangzhai landslide in Sichuan Province, Southwest China: slope instability analysis from radar and optical satellite remote sensing data

A large, deep-seated ancient landslide was partially reactivated on 17 June 2020 close to the Aniangzhai village of Danba County in Sichuan Province of Southwest China. It was initiated by undercutting of the toe of this landslide resulting from increased discharge of the Xiaojinchuan River caused by the failure of a landslide dam, which had been created by the debris flow originating from the Meilong valley. As a result, 12 townships in the downstream area were endangered leading to the evacuation of more than 20000 people. This study investigated the Aniangzhai landslide area by optical and radar satellite remote sensing techniques. A horizontal displacement map produced using cross-correlation of high-resolution optical images from Planet shows a maximum horizontal motion of approximately 15 meters for the slope failure between the two acquisitions. The undercutting effects on the toe of the landslide are clearly revealed by exploiting optical data and field surveys, indicating the direct influence of the overflow from the landslide dam and water release from a nearby hydropower station on the toe erosion. Pre-disaster instability analysis using a stack of SAR data from Sentinel-1 between 2014 and 2020 suggests that the Aniangzhai landslide has long been active before the failure, with the largest annual LOS deformation rate more than 50 mm/yr. The 3-year wet period that followed a relative drought year in 2016 resulted in a 14% higher average velocity in 2018–2020, in comparison to the rate in 2014–2017. A detailed analysis of slope surface kinematics in different parts of the landslide indicates that temporal changes in precipitation are mainly correlated with kinematics of motion at the head part of the failure body, where an accelerated creep is observed since spring 2020 before the large failure. Overall, this study provides an example of how full exploitation of optical and radar satellite remote sensing data can be used for a comprehensive analysis of destabilization and reactivation of an ancient landslide in response to a complex cascading event chain in the transition zone between the Qinghai-Tibetan Plateau and the Sichuan Basin. © 2021, The Author(s)

An improvement in MATSim computing time for large-scale travel behaviour microsimulation

Abstract: Coupling activity-based models with dynamic traffic assignment appears to form a promising approach to investigating travel demand. However, such an integrated framework is generally time-consuming, especially for large-scale scenarios. This paper attempts to improve the performance of these kinds of integrated frameworks through some simple adjustments using MATSim as an example. We focus on two specific areas of the model—replanning and time stepping. In the first case we adjust the scoring system for agents to use in assessing their travel plans to include only agents with low plan scores, rather than selecting agents at random, as is the case in the current model. Secondly, we vary the model time step to account for network loading in the execution module of MATSim. The city of Baoding, China is used as a case study. The performance of the proposed methods was assessed through comparison between the improved and original MATSim, calibrated using Cadyts. The results suggest that the first solution can significantly decrease the computing time at the cost of slight increase of model error, but the second solution makes the improved MATSim outperform the original one, both in terms of computing time and model accuracy; Integrating all new proposed methods takes still less computing time and obtains relatively accurate outcomes, compared with those only incorporating one new method

Obeticholic acid and ferrostatin-1 differentially ameliorate non-alcoholic steatohepatitis in AMLN diet-fed ob/ob mice

Introduction: Non-alcoholic fatty liver disease (NAFLD) and non-alcoholic steatohepatitis (NASH) are common chronic liver diseases with limited treatment options.Methods: Ob/ob mice (6 weeks old) were fed with the Control diet or amylin liver NASH (AMLN) diet for 24 weeks to establish the NASH, the AMLN diet-fed mice were treated with obeticholic acid (OCA), ferrostatin-1 (Fer-1) or their combination for 7 weeks. Finally, various clinical profiles were assessed.Results: Our results indicate that Fer-1 exerts better effects on improving body weight, blood glucose levels, transaminase levels and insulin resistance than OCA. OCA has a profound effect on ameliorating lipid accumulation. OCA and Fer-1 differentially inhibit the activation of hepatic Kupffer cells and HSCs. The combination of OCA and Fer-1 significantly reduces inflammation and protects mice against liver oxidative stress. OCA and Fer-1 differentially reshape the intestinal microbiota and affect the hepatic lipidome.Discussion: Our study compares the effects of OCA, Fer-1 and their combination on various clinical profiles in NASH. These data demonstrate that different drug combinations results in different improvements, and these discoveries provide a reference for the use of the OCA, Fer-1 and their combination in the clinical treatment of NAFLD/NASH

Graphene and Related Materials for Resistive Random Access Memories

Graphene and related materials (GRMs) are promising candidates for the fabrication of resistive random access memories (RRAM). Here, we analyze, classify and evaluate this emerging field, and summarize the performance of the RRAM prototypes using GRMs. Graphene oxide, amorphous carbon films, transition metal dichalcogenides, hexagonal boron nitride and black phosphorous can be used as resistive switching media, in which the switching can be governed either by the migration of intrinsic species or penetration of metallic ions from adjacent layers. Graphene can be used as electrode to provide flexibility and transparency, as well as an interface layer between the electrode and dielectric to block atomic diffusion, reduce power consumption, suppress surface effects, limit the number of conductive filaments in the dielectric, and improve device integration. GRMs-based RRAMs fit some non-volatile memory technological requirements like low operating voltages 10 years, endurance >109 cycles and power consumption ~10 pJ/transition still remain a challenge. More technology-oriented studies including reliability and variability analyses may lead to the development of GRMs-based RRAMs with realistic possibilities of commercialization.We acknowledge support from the Young 1000 Global Talent Recruitment Program of the Ministry of Education of China, the National Natural Science Foundation of China (grants no. 61502326, 41550110223), the Jiangsu Government (grant no. BK20150343), the Ministry of Finance of China (grant no. SX21400213), the Young 973 National Program of the Chinese Ministry of Science and Technology (grant no. 2015CB932700), the Collaborative Innovation Center of Suzhou Nano Science & Technology, the Jiangsu Key Laboratory for Carbon-Based Functional Materials & Devices, the Priority Academic Program Development of Jiangsu Higher Education Institutions, the National Natural Science Foundation of China under Grant Nos. 61521064, 61322408, 61422407, the Beijing Training Project for the Leading Talents in S&T under Grant No. ljrc201508, the Opening Project of Key Laboratory of Microelectronic Devices & Integrated Technology, Institute of Microelectronics, Chinese Academy of Sciences, the EU Graphene Flagship, FP7 Grant CARERAMM, ERC Grants Hetero2D and Highgraink, EPSRC Grants EP/K01711X/1, EP/K017144/1, EP/N010345/1, EP/M507799/1, EP/L016087/1, EP/M013243/1