Logistic regression model for sinkhole susceptibility due to damaged sewer pipes

The occurrence of anthropogenic sinkholes in urban areas can lead to severe socioeconomic losses. A damaged underground sewer pipe is regarded as one of the primary causes of such a phenomenon. This study adopted the best subsets regression method to produce a logistic regression model that evaluates the susceptibility for sinkholes induced by damaged sewer pipes. The model was developed by analyzing the sewer pipe network as well as cases of sinkholes in Seoul, South Korea. Among numerous sewer pipe characteristics tested as explanatory variables, the length, age, elevation, burial depth, size, slope, and materials of the sewer pipe were found to influence the occurrence of sinkhole. The proposed model reasonably estimated the sinkhole susceptibility in the area studied, with an area value under the receiver-operating characteristics curve of 0.753. The proposed methodology will serve as a useful tool that can help local governments to choose a cavity inspection regime, and to prevent sinkholes induced by damaged sewer pipes.     

Evaluating climate change adaptation efforts on the US 50 states’ hazard mitigation plans

Climate change brings uncertain risks of climate-related natural hazards. The US Federal Emergency Management Agency (FEMA in Climate change: long-term trends and their implications for emergency management, 2011. https://www.fema.gov/pdf/about/programs/oppa/climate_change_paper.pdf) has issued a policy directive to integrate climate change adaptation actions into hazard mitigation programs, policies, and plans. However, to date there has been no comprehensive empirical study to examine the extent to which climate change issues are integrated into state hazard mitigation plans (SHMPs). This study develops 18 indicators to examine the extent of climate change considerations in the 50 SHMPs. The results demonstrate that these SHMPs treat climate change issues in an uneven fashion, with large variations present among the 50 states. The overall plan quality for climate change considerations was sustained at an intermediate level with regard to climate change-related awareness, analysis, and actions. The findings confirm that climate change concepts and historic extreme events have been well recognized by the majority of SHMPs. Even though they are not specific to climate change, mitigation and adaptation strategies that can help reduce climate change risks have been adopted in these plans. However, the plans still lack a detailed assessment of climate change and more incentives for collaboration strategies beyond working with emergency management agencies.     

Model Test on Self-Weight Consolidation of the Red Mud Tailings Placed in the Karsts

The management of tailings depends on its consolidation behavior to great extent. The red mud tailings in Pingguo, Guangxi is of high water content and void ratio. The present paper takes the red mud aluminiferous tailings in Pingguo, Guangxi as prototype. Model tests were carried out to study the consolidation behavior of red mud aluminiferous tailings that were landfilled layer by layer. The layered settlement and the water discharge caused by self-weight consolidation were studied. The influence of the latter landfilled layer of red mud on the previous layer was analyzed. The results show that the settlement at the surface with time can be divided into two stages. During the first stage, a thin layer of water appeared and the thickness kept increasing at the top of the mud surface with the particle of red mud sinking. During the second stage, water drained from the mud and settlement developed slowly. Cracks developed at the surface due to evaporation and the red mud near the surface became unsaturated. When the previous landfilled layer consolidated to the degree that the water content was less than 40%, the later landfilled layer of red mud will have little influence on the settlement of previous landfilled layer.     

A model for the representation of emergency cases

The aim of this paper is to propose a location model of earthquake emergency service depot on the basis of hybrid multi-attribute decision-making method. The advantage of the proposed method is that practical mixed uncertainty of location decision information is considered, and the corresponding factors that affect the location of transfer stations are contained. To solve the location problem, a hybrid multi-attribute decision procedure without information transformation is developed. Besides, a novel weighting method and aggregation process is given. Finally, a numerical example is provided to show the feasibility and validity of the proposed method.     

Position-domain integrity risk-based ambiguity validation for the integer bootstrap estimator

Integrity monitoring for ambiguity resolution is of significance for utilizing the high-precision carrier phase differential positioning for safety–critical navigational applications. The integer bootstrap estimator can provide an analytical probability density function, which enables the precise evaluation of the integrity risk for ambiguity validation. In order to monitor the effect of unknown ambiguity bias on the integer bootstrap estimator, the position-domain integrity risk of the integer bootstrapped baseline is evaluated under the complete failure modes by using the worst-case protection principle. Furthermore, a partial ambiguity resolution method is developed in order to satisfy the predefined integrity risk requirement. Static and kinematic experiments are carried out to test the proposed method by comparing with the traditional ratio test method and the protection level-based method. The static experimental result has shown that the proposed method can achieve a significant global availability improvement by 51% at most. The kinematic result reveals that the proposed method obtains the best balance between the positioning accuracy and the continuity performance.     

A new multipath mitigation method based on adaptive thresholding wavelet denoising and double reference shift strategy

Multipath disturbance is one of the major error sources in high-accuracy positioning for global navigation satellite system (GNSS). Although various methods based on software and hardware strategies have been developed to mitigate this error, they are still limited by different kinds of factors and the effect is not ideal. After analyzing the existing methods, a new single-difference sidereal filtering method, based on adaptive thresholding wavelet denoising and double reference shift strategy (ATDR), is proposed to mitigate multipath effects for static short-baseline GNSS applications. The key idea of the proposed method is the use of both the adaptive thresholding wavelet denoising to extract an accurate multipath correction model from the reference Day and the double reference shift strategy to mitigate multipath for subsequent Day 2 more accurately and efficiently. By applying the introduced adaptive thresholding method, the average improvement rate of the RMS values of the single-difference residuals can reach about 15.82% compared with the constant thresholding method. Moreover, after applying the proposed ATDR method, the 3D positioning precision is improved by about 37.73% for the single epoch mode with 30 s data sampling rate and about 31.22% for the continuous mode with 1 s high sampling rate compared with the original results. Even compared with the constant thresholding single orbital reference (CTSR) method, the improvement percentage is about 33.94% in single epoch mode and about 25.40% in continuous mode for 3D positioning precision, respectively. In conclusion, the results of the two experiments indicate that the proposed ATDR method performs much better than the CTSR method in mitigating multipath for different sampling rates and different processing modes in the measurement domain for GNSS static short-baseline postprocessing applications.     

Image-aided platform orientation determination with a GNSS/low-cost IMU system using robust-adaptive Kalman filter

The availability of miniaturized sensors with enhanced capabilities, new methods for image processing, and easy access to small and low-weight airborne platforms for data acquisition, including unmanned vehicles, opens new possibilities for geodetic navigation applications and developing new developments in sensor fusion. In this context, the development of efficient methods, based on low-cost sensors, to extract precise georeferenced information from digital cameras is of utmost interest. We present a method to improve the performance of the integration of GNSS/low-cost IMU by exploiting the orientation changes retrieved from digital images. In this work, a robust-adaptive Kalman filter is also introduced to further improve the performance of the method deployed. The adaptive factor and the robust factor accomplished are determined by innovation information and the threshold value of orientation changes between consecutive images. Results from airborne tests used to assess the performance of the method are presented. The results show that using a non-metric camera, the Euler angle estimation accuracy of the GNSS/low-cost IMU integration can be improved to be close to 0.5 degree and an additional improvement, which can reach 59%, can be achieved after using the robust-adaptive Kalman filter.     

3D-Monitoring Big Geo Data on a seaport infrastructure based on FIWARE

Many organizations of all kinds are using new technologies to assist the acquisition and analysis of data. Seaports are a good example of this trend. Seaports generate data regarding the management of marine traffic and other elements, as well as environmental conditions given by meteorological sensors and buoys. However, this enormous amount of data, also known as Big Data, is useless without a proper system to organize, analyze and visualize it. SmartPort is an online platform for the visualization and management of a seaport data that has been built as a GIS application. This work offers a Rich Internet Application that allows the user to visualize and manage the different sources of information produced in a port environment. The Big Data management is based on the FIWARE platform, as well as “The Internet of Things” solutions for the data acquisition. At the same time, Glob3 Mobile (G3M) framework has been used for the development of map requirements. In this way, SmartPort supports 3D visualization of the ports scenery and its data sources.     

Multiple Unmanned Underwater Vehicles Consensus Control with Unmeasurable Velocity Information and Environmental Disturbances Under Switching Directed Topologies

China Ocean Engineering - A consensus algorithm proposed in the paper is applied to tackle remarkable problems of unmeasurable velocities, the environmental disturbances, and the limited...     

Trends and risk evolution of drought disasters in Tibet Region,China

Journal of Geographical Sciences - The risk posed by natural disasters can be largely reflected by hazard and vulnerability. The analysis of long-term hazard series can reveal the mechanisms by...