Application of Lightning Monitoring and Positioning Data in Investigation and Identification of Lightning Disaster in Inner Mongolia

The lightning current magnitude and other characteristics are important basic data of the lightning disaster investigation and identification. The characteristics of lightning monitoring and positioning system in Inner Mongolia were introduced and studied in the lightning accident analysis based on the lightning monitoring and positioning data of the lightning stroke accidents. The positioning error of lightning monitoring and positioning system was analyzed. The results showed that lightning current intensity and the position precision were very important data in the lightning disaster investigation. Finally, a variety of meteorological data should be applied in the lightning disaster investigation and identification.

Evaluation of driving behavior based on massive vehicle trajectory data

Based on the driver surveillance video data and controller area network(CAN)data,the methods of studying commercial vehicles’driving behavior is relatively advanced.However,these methods have difficulty in covering private vehicles.Naturalistic driving studies have disadvantages of small sample size and high cost,one new driving behavior evaluation method using massive vehicle trajectory data is put forward.An automatic encoding machine is used to reduce the noise of raw data,and then driving dynamics and self-organizing mapping(SOM)classification are used to give thresholds or the judgement method of overspeed,rapid speed change,rapid turning and rapid lane changing.The proportion of different driving behaviors and typical dangerous driving behaviors is calculated,then the temporal and spatial distribution of drivers’driving behavior and the driving behavior characteristics on typical roads are analyzed.Driving behaviors on accident-prone road sections and normal road sections are compared.Results show that in Shenzhen,frequent lane changing and overspeed are the most common unsafe driving behaviors;16.1%drivers have relatively aggressive driving behavior;the proportion of dangerous driving behavior is higher outside the original economic special zone;dangerous driving behavior is highly correlated with traffic accident frequency.

Water storage changes in North America retrieved from GRACE gravity and GPS data

As global warming continues,the monitoring of changes in terrestrial water storage becomes increasingly important since it plays a critical role in understanding global change and water resource management.In North America as elsewhere in the world,changes in water resources strongly impact agriculture and animal husbandry.From a combination of Gravity Recovery and Climate Experiment（GRACE） gravity and Global Positioning System（GPS） data,it is recently found that water storage from August,2002 to March,2011 recovered after the extreme Canadian Prairies drought between 1999 and 2005.In this paper,we use GRACE monthly gravity data of Release 5 to track the water storage change from August,2002 to June,2014.In Canadian Prairies and the Great Lakes areas,the total water storage is found to have increased during the last decade by a rate of 73.8 ± 14.5 Gt/a,which is larger than that found in the previous study due to the longer time span of GRACE observations used and the reduction of the leakage error.We also find a long term decrease of water storage at a rate of-12.0 ± 4.2 Gt/a in Ungava Peninsula,possibly due to permafrost degradation and less snow accumulation during the winter in the region.In addition,the effect of total mass gain in the surveyed area,on present-day sea level,amounts to-0.18 mm/a,and thus should be taken into account in studies of global sea level change.

GRACE time-varying gravity field solutions based on PANDA software

The conventional dynamic approach for gravity filed modelling has been implemented in the PANDA(Position and Navigation Data Analyst) software. A variant of the so-called ’two-step’ method for gravity field modelling is adopted for this purpose, where the GRACE(Gravity Recovery and Climate Experiment)orbits are derived from the GPS(Global Positioning System) data in a first step followed by a simultaneous determination of dynamic orbit and gravity filed from the GPS-derived orbits and K-band rangerate measurements in a second step. In this way, the monthly gravity field solutions complete to degree and order 96 are produced for the period Jan. 2005 to Dec. 2010. Their performance is assessed by comparing them with the official solutions, i.e., CSR RL05, GFZ RL05 a and JPL RL05. A comparison in the spectral domain in terms of geoid heights reveals that the obtained solutions present the smallest degree amplitudes at degree 30-75. A further analysis of mass changes in the spatial domain demonstrates that the main signals observed from the obtained solutions are in great agreement with those from the official solutions. Remarkably, the correlation coefficients of mass changes in large river basins from the official solutions with respect to those from the obtained solutions are all above 0.97. These results demonstrate that the obtained solutions are comparable to the official solutions.

Impacts of Bus Lane on Bus Travel Time Reliability:a Case Study in Shenzhen

The aim of the paper is to evaluate the impacts of bus lane on bus travel time reliability.The data used are the Geographic Positioning System(GPS) data of two bus lines running parallel streets in Shenzhen,China,one of which is a bus lane and the other is a regular lane.Two linear regression models are developed to evaluate the influence of bus lane which has a separated right of way.Other factors including running direction,day of week,time of day,dwell time,and delay at the start point are also considered in the model.Without published time tables,coefficient of variance(CV) of travel time is employed to explore the impacts of bus lane.The results indicate that bus lane can save 22.0% of travel time,reduce 11.5% of the CV of travel time,and decrease the variance of headway by 17.4%.The analysis on bus travel time reliability could help operators and drivers improve the quality of transit service.It also sheds light on how to assess the effectiveness of bus lane for transit planners and service operators.

A GPS-Based Digital Dynamics Study of the Rugby World Cup 2019 Spectators

This study’s dynamic survey of spectators at the HRS(Hanazono Rugby Stadium)in HOC(Higashi Osaka City)during the 2019 RWC(Rugby World Cup)tournament used location information big data to analyze nine items,including spectator attributes-60 min or more stay in HOC(excluding residents),more than 15 min stay in the HRS on match days(besides,the days before and after the match).To compare spectators,visitors to HOC during the matches were added to the target group.The results show that the RWC attracted a high number of male visitors aged 20,40,and 50 years,mainly from the Kinki region,whose stopovers inside and outside the region were limited to Osaka City.Stopovers in tourist areas unrelated to the RWC were few,partly because it was possible to undertake a day trip solely to watch the game without any stopovers.

Hardware pre-processing for data of SBL underwater positioning system

The synchro double pulse signal mode is freuqently used in Short Base Line (SBL)underwater positioning system so as to obtain the information of both distance and depth of a target simultaneously. Howerer, this signal mode also brings about ranging indistinctness resulting in a shorter positioning distance much less than that limited by the period of the synchro signal. This paper presents a hardware distance-gate data acquiring scheme. It puts the original data sent to the computer in order of ' direct first pulse- depth information pulse (or first pulse reflected by water surface )…' to guarantee the effective positioning distance of the system. It has the advantage of reducing the processing time of the computer thus ensuring the realtime functioning of the system. A figure of the orbit of an underwater moving target measured in practice is attached to the end of the paper.

Sampled data based containment control of second-order multi-agent systems under intermittent communications

This paper studies the sampled data based containment control problem of second-order multi-agent systems with intermittent communications,where velocity measurements for each agent are unavailable.A novel controller for second-order containment is put forward via intermittent sampled position data measurement.Several necessary and sufficient conditions are derived to achieve intermittent sampled containment control by means of analyzing the relationship among control gains,eigenvalues of the Laplacian matrix,the sampling period,and the communication width.Finally,several simulation examples are used to testify the correctness and effectiveness of the theoretical results.

Population spatialization with pixel-level attribute grading by considering scale mismatch issue in regression modeling

Population spatialization is widely used for spatially downscaling census population data to finer-scale.The core idea of modern population spatialization is to establish the association between ancillary data and population at the administrative-unit-level(AUlevel)and transfer it to generate the gridded population.However,the statistical characteristic of attributes at the pixel-level differs from that at the AU-level,thus leading to prediction bias via the cross-scale modeling(i.e.scale mismatch problem).In addition,integrating multi-source data simply as covariates may underutilize spatial semantics,and lead to incorrect population disaggregation;while neglecting the spatial autocorrelation of population generates excessively heterogeneous population distribution that contradicts to real-world situation.To address the scale mismatch in downscaling,this paper proposes a Cross-Scale Feature Construction(CSFC)method.More specifically,by grading pixel-level attributes,we construct the feature vector of pixel grade proportions to narrow the scale differences in feature representation between AU-level and pixel-level.Meanwhile,fine-grained building patch and mobile positioning data are utilized to adjust the population weighting layer generated from POI-density-based regression modeling.Spatial filtering is furtherly adopted to model the spatial autocorrelation effect of population and reduce the heterogeneity in population caused by pixel-level attribute discretization.Through the comparison with traditional feature construction method and the ablation experiments,the results demonstrate significant accuracy improvements in population spatialization and verify the effectiveness of weight correction steps.Furthermore,accuracy comparisons with WorldPop and GPW datasets quantitatively illustrate the advantages of the proposed method in fine-scale population spatialization.