Application of ICTs in Airspace Management and Collaborative Decision-Making—Analyzing the Risk Avoidance in the Condition of Risky Weather as an Example

The application of ICTs makes structural change of the development and effective utilization of airspace. Next generation air transportation system (NextGen) includes new automation concepts with automated information to support the traffic control decision-making. As a result, in the field of academia and industry, air traffic controllers integrate information automatically while making decisions to change the previous manually integrated and decided pattern. The safety ability of airspace is reduced and airspace system is endangered under risky weather conditions of airspace. So there is an urgent demand for new information and communication technologies. The paper is an overview of the information constitution and support of NextGen and provides the study of the development of technique of airspace collaborative decision-makings to confirm the new features based on ICTs. It contains basic application-the input of data and output of the routes of airspace management and collaborative decision-making, and general application-the choose of probability nets of avoiding risky weather, and special application-the affection in the management of the air routes, which are made up of position and direction. The research shows the accurate schedule characteristics of airspace management and collaborative decision-making based on ICTs, which made the space accurate by time accurate. Second, the visualization of airspace management and collaborative decision-making based on ICTs made the maps of flight path under mobile data quickly generated. This could make the fully development and utilization of national airspace, ensure safety, and reduce air traffic controllers’ workload and the costs in delaying and operating in risky weather.     

Task-oriented information value measurement based on space-time prisms

Recent years have witnessed a large increase in the amount of information available from the Web and many other sources. Such an information deluge presents a challenge for individuals who have to identify useful information items to complete particular tasks in hand. Information value theory (IVT) from economics and artificial intelligence has provided some guidance on this issue. However, existing IVT studies often focus on monetary values, while ignoring the spatiotemporal properties which can play important roles in everyday tasks. In this paper, we propose a theoretical framework for task-oriented information value measurement. This framework integrates IVT with the space-time prism from time geography and measures the value of information based on its impact on an individual’s space-time prisms and its capability of improving task planning. We develop and formalize this framework by extending the utility function from space-time accessibility studies and elaborate it using a simplified example from time geography. We conduct a simulation on a real-world transportation network using the proposed framework. Our research could be applied to improving information display on small-screen mobile devices (e.g., smartwatches) by assigning priorities to different information items.     

Integration of GIS and video surveillance

This paper discusses the integration of three-dimensional (3D) geographic information systems (GIS) and video surveillance systems using augmented reality (AR) techniques. The motivation for this integration is to overcome problems faced by conventional video surveillance systems. Explicit information concerning which camera currently monitors what area in such systems is missing; therefore, insight into the situation depends heavily on the operator’s training and experience. To ensure the complete coordination and monitoring of a situation in a system with multiple cameras, it is necessary to introduce a single reference system. GIS arises as a natural solution because it not only provides a solid ground truth but also provides semantic information that can be highly important in certain video surveillance applications. To integrate information into a GIS application, that information must be georeferenced. Based on our previous research regarding the addition of georeferencing information to surveillance video, this paper introduces models that can be applied to help integrate video and GIS. With an analogy to Milgram’s continuum between the real world and virtual reality, and analogous to the augmented reality and augmented virtuality in Milgram’s continuum, two models of integration are defined here: GIS-augmented video and video-augmented GIS. Then, we define the architecture of GIS-based video surveillance based on these proposed integration models, and finally, a prototype is implemented. The implemented prototype serves as a basis for analysing possible applications of real-world systems based on the integration of GIS and video.     

Landfill site selection based on reliability concepts using the DRASTIC method and AHP integrated with GIS – a case study of Bengaluru city,India

The selection of landfill sites for municipal solid waste (MSW) disposal involves consideration of geological, hydrological and environmental parameters which exhibit large spatial variability. Therefore, it is necessary to define, to what extent the chosen sites are reliable such that the probability of environmental pollution and health risks to population is minimal. In the present study, groundwater vulnerability to contamination has been assessed using the standard DRASTIC method. The results showed that the study region has 9.45% of very less, 32.94% of less, 25.47% of moderate, 22.79% of high and 9.35% of very high vulnerable zones. The study also revealed that none of the landfills are located in safe zones. This suggests that it requires proper remedial measures to avoid environmental pollution. A landfill site selection process has been carried out using the Analytical Hierarchy Process integrated with Geographical Information System tools. The obtained results showed that only 3.59?km² (0.08%) of the total area is suitable for landfills. The reliability analysis of the site suitability revealed that landfills are located at unreliable locations where the probability of risk to environmental pollution is high. The presented approach assists decision-makers in selecting reliable locations for the safe disposal of MSW.     

基于高分二号卫星数据的煤矿区地质灾害信息提取研究

随着遥感数据获取技术和能力的全面提高,遥感数据呈现出明显的大数据特征。发展适应于遥感大数据的智能分析和信息挖掘技术,成为当前遥感技术研究的前沿。高分二号（GF-2）卫星数据是我国首颗自主研发的亚米级高分辨率卫星数据,具有观测幅宽、重访周期短、高辐射精度、高定位精度等优势,为未来我国地质灾害的长期、动态地监测和研究提供了高精度、稳定可靠的数据源。本文选取安徽谢桥煤矿2015年1月8日的GF-2卫星影像为研究数据,在对煤矿区主要地质灾害遥感地学分析的基础上,采用面向对象的影像分析方法对研究区由采煤活动所诱发的地质灾害信息进行自动提取。结果表明：利用GF-2卫星数据能够有效地识别地质灾害体的位置、范围、形态等空间分布特征;面向对象的自动提取方法对于煤矿区大面积的积水塌陷盆地、小规模的塌陷坑和线性的地裂缝都有很高的提取精度,识别精度达90% 以上;基于逐层剔除的思路构建的提取规则,为GF-2数据在地质灾害调查和大数据分析中的应用提供了很好的技术支持,也为其它地物目标的提取提供了参考,但在特征的选择和阈值的设定上需要具体分析。     

GIS professional development for teachers: lessons learned from high-needs schools

University faculty partners from the Departments of Geography and Instruction and Teacher Education at a large, public university collaborated with K-12 teachers and the leadership of a rural school district in order to investigate the crosscutting content of science, mathematics, and geography through the integration of web-based GIS technologies. The project explored the critical connections among technology, pedagogy, and content with a particular emphasis on developing technology-enhanced, inquiry-based lessons in which the teachers and their students used GIS technologies to analyze, visualize, and present data in real-world contexts. The findings highlight the importance of well-structured professional development that builds community, integrates diverse content and pedagogical expertise, provides feedback and coaching, and is of sufficient duration to effect change.     

Three-dimensional publication mode of Journal of Palaeogeography(Chinese Edition)

The network technology has provided impetus and channels for the development of sci-tech periodicals and promoted the transformation of the publication mode of Journal of Palaeogeography(Chinese Edition). Through the independent website construction,providing readers with diversified access to articles,diversified communication methods,personalized accurate article push,joining the OSID open science program,etc.,a three-dimensional publication mode adapted to the development of periodicals has been gradually formed.     

Spatial landslide susceptibility assessment using machine learning techniques assisted by additional data created with generative adversarial networks

In recent years,landslide susceptibility mapping has substantially improved with advances in machine learning.However,there are still challenges remain in landslide mapping due to the availability of limited inventory data.In this paper,a novel method that improves the performance of machine learning techniques is presented.The proposed method creates synthetic inventory data using Generative Adversarial Networks(GANs)for improving the prediction of landslides.In this research,landslide inventory data of 156 landslide locations were identified in Cameron Highlands,Malaysia,taken from previous projects the authors worked on.Elevation,slope,aspect,plan curvature,profile curvature,total curvature,lithology,land use and land cover(LULC),distance to the road,distance to the river,stream power index(SPI),sediment transport index(STI),terrain roughness index(TRI),topographic wetness index(TWI)and vegetation density are geo-environmental factors considered in this study based on suggestions from previous works on Cameron Highlands.To show the capability of GANs in improving landslide prediction models,this study tests the proposed GAN model with benchmark models namely Artificial Neural Network(ANN),Support Vector Machine(SVM),Decision Trees(DT),Random Forest(RF)and Bagging ensemble models with ANN and SVM models.These models were validated using the area under the receiver operating characteristic curve(AUROC).The DT,RF,SVM,ANN and Bagging ensemble could achieve the AUROC values of(0.90,0.94,0.86,0.69 and 0.82)for the training;and the AUROC of(0.76,0.81,0.85,0.72 and 0.75)for the test,subsequently.When using additional samples,the same models achieved the AUROC values of(0.92,0.94,0.88,0.75 and 0.84)for the training and(0.78,0.82,0.82,0.78 and 0.80)for the test,respectively.Using the additional samples improved the test accuracy of all the models except SVM.As a result,in data-scarce environments,this research showed that utilizing GANs to generate supplementary samples is promising because it can improve the predictive capability of common landslide prediction models.     

A novel index to evaluate discretization methods:A case study of flood susceptibility assessment based on random forest

The selection of a suitable discretization method(DM)to discretize spatially continuous variables(SCVs)is critical in ML-based natural hazard susceptibility assessment.However,few studies start to consider the influence due to the selected DMs and how to efficiently select a suitable DM for each SCV.These issues were well addressed in this study.The information loss rate(ILR),an index based on the informa-tion entropy,seems can be used to select optimal DM for each SCV.However,the ILR fails to show the actual influence of discretization because such index only considers the total amount of information of the discretized variables departing from the original SCV.Facing this issue,we propose an index,infor-mation change rate(ICR),that focuses on the changed amount of information due to the discretization based on each cell,enabling the identification of the optimal DM.We develop a case study with Random Forest(training/testing ratio of 7:3)to assess flood susceptibility in Wanan County,China.The area under the curve-based and susceptibility maps-based approaches were presented to compare the ILR and ICR.The results show the ICR-based optimal DMs are more rational than the ILR-based ones in both cases.Moreover,we observed the ILR values are unnaturally small(＜1％),whereas the ICR values are obviously more in line with general recognition(usually 10％-30％).The above results all demonstrate the superiority of the ICR.We consider this study fills up the existing research gaps,improving the ML-based natural hazard susceptibility assessments.     

区域数字地震台网实时速报系统研究

根据我国地震监测台网的发展趋势,提出了区域数字地震台网实时速报系统的发展目标,研究了实现这一目标应解决的实时数据流接收、震相自动识别、震相可靠性处理、实时地震定位、震相到时等值线实时绘制、地震震级的实时计算、地震动强度分布图的实时绘制等问题.我们编制了一套实时地震速报软件,实现了上述功能,并用福建数字地震台网记录的地震事件进行软件功能测试.测试结果表明:对于网内地震,软件处理结果基本达到中国地震局地震速报评比满分的要求,速报时间缩短至30～50 s.此外,通过实时仿真技术,系统可给出实际观测到的PGA、PGV、PGD等值线图,可以为应急救灾确定重灾区和有感范围提供帮助.