Table of Content

20 August 2018, Volume 47 Issue 8

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The Being and Non-being Generate Each Other,and the Virtual and the Real are Mutually Interactive-The Progress of Virtual Geographic Environments (VGE) Studies in Last 20 Years

LIN Hui, ZHU Qing, CHEN Min

2018, 47(8):  1027-1030.  doi:10.11947/j.AGCS.2018.20180202

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It has been 20 years since the conception of virtual geographic environments (VGE) was proposed.In this article,the development process of VGE is reviewed,the design concept and functional compositions of VGE are sketched,some of the currently achievements are introduced,and the further direction is pointed out.

Service-oriented Encapsulation Method of Geo-analysis Model on Linux for Virtual Geographic Environments

TAN Yufeng, CHEN Min, ZHANG Bowen, SHEN Chaoran, WEN Yongning

2018, 47(8):  1031-1042.  doi:10.11947/j.AGCS.2018.20180112

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Geo-analysis models are the abstraction and expression of real-world geographic phenomena and processes.Multidisciplinary and collaborative geographic modeling is currently becoming a main research trend in the field of geography.The service-oriented sharing and reuse of geo-analysis models have become a research direction.However,the heterogeneities in operating platforms lead to difficulties with the sharing and reuse of geo-analysis models.At present,the operating platforms for geo-analysis models mainly include Windows and Linux.A large number of geo-analysis models are developed depending on Linux,but there is less research related to the service-oriented sharing and reuse of these models.This article aims to analyze its differences and security and design a service-oriented security strategy for geo-analysis models on different Linux operating systems.Given the heterogeneities of geo-analysis models for Linux,the basic information description interface,behavior interface,and deployment interface were designed for the service-oriented sharing and reuse of geo-analysis models.The grid analysis model in the system for automated geoscientific analyses (SAGA GIS) was used as an example to demonstrate a service-oriented encapsulation method for geo-analysis models for Linux and validated.In summary,the proposed study can contribute to the theory and methods for the sharing and reuse of geo-analysis models on Linux.

Virtual Geographic Cognition Experiment in Big Data Era

ZHANG Fan, HU Mingyuan, LIN Hui

2018, 47(8):  1043-1050.  doi:10.11947/j.AGCS.2018.20180103

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Virtual geographic cognition experiment is an experimental framework to understand the perception,cognition,emotion and behavior of human to the environment.Since it has been proposed,experimental geography and other related field has been benefited from its theory and methodology.The coming big data era has brought with a huge massive of human cognitive,emotional and behavioral data,potentially bringing opportunities to establish new research paradigm in virtual geographic experiment,to help researchers look deeper into the man-land relationship.In this paper,we first proposed the framework of virtual geographic cognition experiment based on data-intensive scientific research paradigm,where we introduced how to treat human activity data and urban context data by integrating the theory in environmental psychology,and artificial intelligence.Second,we demonstrated the framework by introducing a case study,which has explored a series of visual factor in urban scene that would have an impact on depressing emotion of individual.

Geographic Knowledge Graph Building Extracted from Multi-sourced Heterogeneous Data

JIANG Bingchuan, WAN Gang, XU Jian, LI Feng, WEN Huiqi

2018, 47(8):  1051-1061.  doi:10.11947/j.AGCS.2018.20180113

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As a new generation of geographic language,virtual geographic environments(VGE) needs to construct the virtual geographic knowledge engineering through the analysis and excavation of multi-sourced heterogeneous spatio-temporal data.Through the transformation about "data-information-knowledge-wisdom",it can promote the rapid conversion and integration of geographic knowledge for intelligent VGE system,which may provide a theoretical and technical support for intelligent processing of geographic information and intelligent service of geographic knowledge.Knowledge graph plays the role of a bridge between artificial intelligence and knowledge engineering for VGE system.This paper firstly reviewed the research status in knowledge graph and geographic knowledge graph from the domestic and abroad perspectives.Then,the construction process of geographic knowledge graph is proposed.Furthermore,the key technologies of geographic knowledge graph are discussed in depth.Finally,the application direction of geographic knowledge graph is discussed and stated.The study of geographic knowledge graph in this paper may help to realize the knowledgization of geographic information and promote the intelligent service level for VGE system.

A Process-oriented Risk Monitoring and Assessment Modeling Approach in Urban Public Safety

HU Chuanbo, YOU Lan, LIN Hui

2018, 47(8):  1062-1071.  doi:10.11947/j.AGCS.2018.20180117

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Urban public safety is a typical application to realize the risk cognition and expression in the research of virtual geographical environment.However,for sharing management and instant demands of urban public emergencies risk assessment,there is a lack of process-oriented expression methods of risk monitoring and assessment to provide rapid and comprehensive decision support.Therefore,this paper aims at proposing a process-oriented risk assessment modeling method based on the MOF meta-model modeling framework under a unified space-time framework.The scheme can achieve sharing and reuse of risk monitoring and evaluation and provide instant,process-oriented personalized information services for risk assessment.It is also designed that a prototype system for risk assessment process management to realize the functions of risk assessment process modeling,registration,implementation and visualization.Experiment through the simulation of gas leakage in Taiyuan City as an application case verifies the feasibility of the method.

Spatio-temporal Modeling of Virtual Geographic Environments and Its Application in Battle Plan Deduction

LI Feng, WAN Gang, JIANG Bingchuan, AN Zipeng

2018, 47(8):  1072-1079.  doi:10.11947/j.AGCS.2018.20180115

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A scientific,reasonable and complete battle plan is the key to win the modern war,and the battle plan deduction can assist the commander in finding potential conflicts and optimizing the battle plan.The virtual geographical environment can provide the spatio-temporal description method,environment analysis model and situational visualization environment for battle plan deduction.Firstly,the method of virtual battlefield environment space subdivision and coding and spatio-temporal data organization model were designed for battle plan deduction.Then,an deduct event based battle plan expression method was proposed,the method of time and space conflict detection and dynamic play method based on deduct event were designed.At last,typical applications were made in the air defense battle plan deduction,it prove this method is feasible.

A Scenario Modeling-based Data Organization Method for Analyzing and Simulating Urban Residential Regions

TAO Hong, YUE Songshan, XIAO Dawei, SUN Lingzhi, LU Yuchen, WANG Lingshan, ZHENG Peibei, LÜ Guonian

2018, 47(8):  1080-1088.  doi:10.11947/j.AGCS.2018.20180109

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Urban residential regions are important parts of the urban living environment,and they are closely related to urban life.In order to meet the demands of comprehensive analysis and simulation of urban environments,this paper combines the concept of virtual scene and integrated modeling in the virtual geographic environment (VGE)to design a data organization method for constructing urban residential region for modeling.Through the abstraction of system,object and relation,the complex environment information of an urban residential region can be described and organized in a hierarchical structure.In addition,the universal data description and eXchange model (UDX)was also employed to describe and store the data content for urban residential regions in a uniform manner.The data content that meets the demands of a geo-analysis model can be extracted from the modeling scene,thus supporting the integration of different geo-analysis models and the modeling scene.The experimental results show that the proposed method can effectively organize the heterogeneous urban environment data and provide the demanded modeling data conveniently for the geo-analysis models from different research areas.

An Augmented Geographic Environment for Geo-process Visualization-A Case of Crowd Evacuation Simulation

GONG Jianhua, LI Wenhang, ZHANG Guoyong, SHEN Shen, HUANG Lin, SUN Jun

2018, 47(8):  1089-1097.  doi:10.11947/j.AGCS.2018.20180111

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Combining with the development of augmented reality (AR) technology,this paper proposed a conceptual framework about augmented geographic environment (AGE) based on the development of virtual geographic environments (VGE).Key computing and visualization technologies of the fusion of virtual geographic process and 3D printing realistic model,including the coordinate matching technology of virtual geospatial space and real geographical space and the technology of occlusion processing,are investigated.In the case of crowd evacuation,we implemented a prototype system for crowd evacuation simulation based on the AGE.Then we proved the novelty of the AGE by systematic testing and document investigation.We believe that the AGE is one of the future development of VGE.

The Multi-level Visualization Task Model for Multi-modal Spatio-temporal Data

LIU Mingwei, ZHU Qing, ZHU Jun, FENG Bin, LI Yun, ZHANG Junxiao, FU Xiao, ZHANG Pengcheng, YANG Weijun, NING Xinwen, XU Wanyan

2018, 47(8):  1098-1104.  doi:10.11947/j.AGCS.2018.20180104

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The existing spatio-temporal data visualization methods are mainly targeted at low-level view-only visualization tasks,which is difficult to meet the high concurrency and multi-level visualization tasks of multi-modal spatio-temporal data.To address this challenge,it is presented that the multi-level visualization task model for multi-modal spatiotemporal data,which categorized the visualization task as view-only visualization task,analytical visualization task and explorative visualization task.The main features of this model are:①it described the main driving forces and spatio-temporal information needed in different level of tasks;②it described the requirements of task and its relationship between storage,computing and rendering.Based on the model,task-aware and adaptive spatiotemporal data visualization engine is designed.Finally taking the refinement management and decision-making applications in smart city as an example,the model is proved to be effectively meet the needs of multi-level visualization and analysis applications and could lay a solid foundation for the complex applications in smart city.

Representing Multiple Urban Places' Footprints from Dianping.com Data

WANG Shengyin, LIU Yu, CHEN Zedong, SHI Li, ZHANG Jing

2018, 47(8):  1105-1113.  doi:10.11947/j.AGCS.2018.20180110

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A place is a geographical area with a particular semantic and humanistic experience.In virtual geographic environment studies,places play an important role in spatial knowledge representation,by providing the support for human-centroid understanding of geographic environment and VGE-based analysis and simulation.Identifying and modeling the existing vague places in cities are therefore fundamental to VGE studies.Crowd-sourced geo-data provide a new approach to extracting and representing vague places.The most of existing research,however,focused on modeling single or a few places but not considering the influence of threshold selection among multiple point sets of places in diverse scales.In order to model multiple places of the city at different spatial scales,we proposed the fuzzy set method based on adaptive kernel density estimation for generating the spatial footprints of places,which can provide a reasonable and efficient way to model multiple vague places.In the case study,POIs inside the 5^th Ring Road of Beijing,collected from Dianping.com,are used to visually represent footprints of places in the way of fuzzy sets and α-cuts,with the former one avoiding the over simplified representation of continuous surface while the latter focusing more on the crisp boundaries.By comparing the results and the corresponding places' scales showed by base maps,we found that the use of the dataset harvested from dianping.com could provide a better understanding of the places' footprints of commercial context.

A Visual Salience Model of Landmark Based on Virtual Geographical Experiments

JIA Fenli, TIAN Jiangpeng, ZHI Meixia, CHEN Lingyu, YANG Qingli

2018, 47(8):  1114-1122.  doi:10.11947/j.AGCS.2018.20180107

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In this paper,a visual salience model of landmark based on virtual geography experiments is proposed for landmark discrimination and salience calculation.Taking the calculation of salience model of city buildings as an example,visual factors of landmarks and their calculation are first analyzed,and then a virtual experiment environment is developed to incorporate eye tracking as well as controllable and computable visual factors.Furthermore,a quantitative model of the relationship between eye movement factors and visual salience of landmark is derived from empirical results.Based on the quantitative model,further experiment is designed to solve the equation of visual salience model of landmark by fitting experimental data,which describes the relationship between a visual salience of landmark and visual factors.The key to the proposed method is to use eye movement factors to represent a salience model in a virtual environment with controllable and computable visual factors,and then the salience model can be calculated through landmark cognition experiments and data analysis.This method can not only reduce the complexity of landmark research,but also overcome the difficulty of repeating the experiments,which makes it a unique advantage to solve problem that tackles interaction mechanism between human and environments such as landmark discrimination.

A Construction Optimization and Interaction Method for Flood Disaster Scenes Based on Mobile VR

HU Ya, ZHU Jun, LI Weilian, ZHANG Yunhao, HU Mingyuan, CAO Zhenyu

2018, 47(8):  1123-1132.  doi:10.11947/j.AGCS.2018.20180114

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The existing three-dimensional (3D) visualization of flood disaster scenes has problems such as weak immersion and lack of mobility.This paper combines mobile virtual reality (VR) with 3D visualization of flood disaster scenes,and proposes a construction optimization and interaction method for flood disaster scenes based on mobile VR.Firstly,a mobile VR scene construction scheme under a plugin-free B/S architecture is proposed.Second,certain key technologies for scene optimization are discussed,including diverse modes of scene data organization,optimization control of scene data volume and adaptive scheduling of mobile scenes.Finally,some interaction and analysis schemes based on gaze,such as scene roaming exploration and interactive flood information query,are designed.A test platform was developed and a case experiment analysis was carried out.The experiment results demonstrate that the flood disaster scene constructed by the methods addressed in this paper can be displayed smoothly and explored interactively on smart phones.

Method for Generating Forest Landscapes Based on the Characteristics of Plant Distribution

LI Jiaqi, GAO Yiyuan, SHE Jiangfeng

2018, 47(8):  1133-1140.  doi:10.11947/j.AGCS.2018.20180102

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The rapid generation of forest landscapes with specific spatial patterns in virtual geographic environment is a big challenge.Most of the previous studies specify the locations and attributes of trees using simulation and random synthesis methods.However,it is hard to reflect the distribution characteristics of each tree species for these methods.A graph-based neutral landscape model is proposed to generate forest landscapes with specific composition and spatial configuration based on landscape metrics set by users.The model converts a random map with many irregular regions into a region adjacency graph,and then generates patches with specific shape and size by merging neighbor nodes in the graph.Compared with other neutral landscape models,the proposed model has advantages of controllability and flexibility in expressing the landscape characteristics of different classes separately.Finally,based on the forest landscapes served as vegetation distribution maps,the positions and types of trees are determined.The proposed method can not only provide reasonable tree distributions for visualization of large-scale forests,but also reflect the spatial pattern of forest landscapes.The proposed method can also provide a reference for forestry planning and ecology research in virtual forest environment.

Parameter Estimate Algorithm in Adjustment Model with Interval Constraint

XIE Xuemei, SONG Yingchun, XIAO Zhaobing

2018, 47(8):  1141-1147.  doi:10.11947/j.AGCS.2018.20160407

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There are usually some uncertain additional information or prior information on parameters in surveying adjustment models,which can constraint on the parameters,and guarantee uniqueness and stability of parameters solution.This paper mainly focused on the studies of adjustment model with box constraints.Firstly,using the regular splitting method of matrix,adjustment model is converted to a simple quadratic programming problem.Then a new iterative algorithm of parameter estimation is established.The algorithm convergence is given.Finally,with example,it is confirmed that the proposed method can improve efficiency of parameter estimation,reduce ill-posed characteristic of model and keep statistical,geometric or physical significance of prior information.

A Coarse-to-fine Signal Detection Method for Airborne LiDAR Bathymetry

WANG Dandi, XU Qing, XING Shuai, LIN Yuzhun, LI Pengcheng

2018, 47(8):  1148-1159.  doi:10.11947/j.AGCS.2018.20170466

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To solve the problems that waveforms vary with different environments and detection accuracy is limited by the sampling interval of airborne LiDAR bathymetry (ALB) system,a coarse-to-fine signal detection method for ALB is proposed.The effective length of the received waveform is first calculated from the system transmit signal parameters as an approximation of water depth.For the coarse detection,the received waveform is preprocessed based on Richardson-Lucy deconvolution (RLD) and average square difference function (ASDF),determined by the approximation of water depth,and through a constrained detection method signals are detected from the preprocessed waveform as the initial values of the accurate detection.In the accurate detection,an improved exponential function with a second-order polynomial model is proposed to fit the received waveform and trust region algorithm is introduced to solve the model parameters.Thus,the exact positions of the signals are obtained.The experimental results show that the coarse detection can cope with the waveforms appropriately based on these characteristics and acquire reliable results.The detection results are accurate to subsampling interval and the accuracy of the coarse detection results is further improved by the accurate detection.Compared to the traditional methods including maximum detection,ASDF,RLD and quadrilateral fitting,the success rate and the accuracy of the proposed method averagely achieve nearly 10% and 30% improvement respectively.

Research on the Theory and Method of Inter-system Double Difference Ambiguity Forming and Fixing for Multi-GNSS

SUI Xin

2018, 47(8):  1160-1160.  doi:10.11947/j.AGCS.2018.20170518

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