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2020, 45(9): 1319-1327.
doi: 10.13203/j.whugis20200010
Abstract:
The heterogeneous multidisciplinary spatial information data with multi-granularity and sophisticated semantics of features in the wide area of Sichuan-Tibet railway, which leads to the inconsistency of data content/format and spatio-temporal datum.Therefore, it is difficult to integrate/analyse relevant data efficiently. In order to establish the concept system of cognitive sharing for the unified expression of spatial information of Sichuan-Tibet railway, firstly, this article has studied and depicted the geometry, scale, topology, attribute, behavior characteristics and interactive relationship of different feature types such as "geography""geology""facilities""meteorology""ecology""disaster" and "personnel"; secondly, according to the framework of relevant national standard classification and coding system, the study has regulated the unified coding rules and expanding methods, conducted substantialization classification upon various feature types into the minimum management unit. Based on the rules, the classification in higher level (primary category, subcategory, large class and medium class) and the classification in lower level (level Ⅰ, Ⅱ and Ⅲ subclasses) was expanded and reduced according to the application requirements of Sichuan-Tibet railway respectively, leaving 2 primary categories, 6 subcategories, 27 large classes and 87 medium classes in total. On this basis, each feature entity in the classification system was coded and given a unique and unambiguous identity, so as to implement the precise mapping between three-dimensional spatial information and feature entities and provide support for the construction of Sichuan-Tibet railway.
The heterogeneous multidisciplinary spatial information data with multi-granularity and sophisticated semantics of features in the wide area of Sichuan-Tibet railway, which leads to the inconsistency of data content/format and spatio-temporal datum.Therefore, it is difficult to integrate/analyse relevant data efficiently. In order to establish the concept system of cognitive sharing for the unified expression of spatial information of Sichuan-Tibet railway, firstly, this article has studied and depicted the geometry, scale, topology, attribute, behavior characteristics and interactive relationship of different feature types such as "geography""geology""facilities""meteorology""ecology""disaster" and "personnel"; secondly, according to the framework of relevant national standard classification and coding system, the study has regulated the unified coding rules and expanding methods, conducted substantialization classification upon various feature types into the minimum management unit. Based on the rules, the classification in higher level (primary category, subcategory, large class and medium class) and the classification in lower level (level Ⅰ, Ⅱ and Ⅲ subclasses) was expanded and reduced according to the application requirements of Sichuan-Tibet railway respectively, leaving 2 primary categories, 6 subcategories, 27 large classes and 87 medium classes in total. On this basis, each feature entity in the classification system was coded and given a unique and unambiguous identity, so as to implement the precise mapping between three-dimensional spatial information and feature entities and provide support for the construction of Sichuan-Tibet railway.
2020, 45(9): 1328-1333.
doi: 10.13203/j.whugis20200080
Abstract:
Geographic information space is a high-dimensional space combining virtual and real. Geographic information system (GIS) based on European geometry plays an important role in the development of geographic information science. However, because the expression of GIS geographic objects and phenomena in European-style space depends on object coordinates and the adopted coordinate system, it is difficult for the expression, calculation and analysis of geographic objects to form a multi-dimensional unified operation rule and framework, which increases the algorithm's complexity and reduces the efficiency of algorithm analysis. Geometric algebra is a kind of combination algebra based on dimensional operation. Space can be defined as the operation between vector sets. The dimension of space is directly determined by the algorithm, which realizes the unification of high-dimensional geometric calculation and analysis. Based on the unified calculation and analysis framework of geometric algebra, GIS can better express and analyze high-dimensional objects, and then improve the ability of expressing complex geographical objects and dynamic geographical phenomena, analyzing spatiotemporal multi-scale objects and integration of different scale geographical models. This lays the theoretical foundation for the development of GIS towards holographic maps with real-time dynamics, virtual-real fusion, full perspective, full elements and full content expression.
Geographic information space is a high-dimensional space combining virtual and real. Geographic information system (GIS) based on European geometry plays an important role in the development of geographic information science. However, because the expression of GIS geographic objects and phenomena in European-style space depends on object coordinates and the adopted coordinate system, it is difficult for the expression, calculation and analysis of geographic objects to form a multi-dimensional unified operation rule and framework, which increases the algorithm's complexity and reduces the efficiency of algorithm analysis. Geometric algebra is a kind of combination algebra based on dimensional operation. Space can be defined as the operation between vector sets. The dimension of space is directly determined by the algorithm, which realizes the unification of high-dimensional geometric calculation and analysis. Based on the unified calculation and analysis framework of geometric algebra, GIS can better express and analyze high-dimensional objects, and then improve the ability of expressing complex geographical objects and dynamic geographical phenomena, analyzing spatiotemporal multi-scale objects and integration of different scale geographical models. This lays the theoretical foundation for the development of GIS towards holographic maps with real-time dynamics, virtual-real fusion, full perspective, full elements and full content expression.
2020, 45(9): 1334-1343.
doi: 10.13203/j.whugis20200211
Abstract:
The development of ICT (information and communications technology) provides new challenges and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about cartographic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to explore new fields. The development of "digits and culture" has pushed the game to the forefront of high-tech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, this paper explores the characteristics and essence of game map and its implications to the real physical world by the dimensionalities, interactivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
The development of ICT (information and communications technology) provides new challenges and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about cartographic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to explore new fields. The development of "digits and culture" has pushed the game to the forefront of high-tech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, this paper explores the characteristics and essence of game map and its implications to the real physical world by the dimensionalities, interactivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
2020, 45(9): 1344-1355.
doi: 10.13203/j.whugis20200047
Abstract:
Natural disasters occur frequently and pose a huge threat to China. Disaster prevention, mitigation, and disaster relief are eternal topics of human survival and development. However, in the field of disaster relief and emergency response, the relevant data increase sharply while the critical knowledge of emergency is obviously lacking. The "data-information-knowledge" transformation capacity is insufficient to meet the urgent needs of disaster prevention and reduction. Firstly taking natural disasters as the core, and around four elements of natural disaster events, disaster emergency tasks, disaster data, and methods, this paper proposes a knowledge graph construction method by combining a top-down approach and a bottom-up approach. Then, concept layer of knowledge graph is built from top to down, and the conceptual framework is formed through ontology modeling. Data layer of knowledge graph is built from bottom to top, and the relationship between entities is established through data acquisition, knowledge extraction, fusion, and storage. Finally, a flood disaster emergency knowledge graph is built to verify the validity of the proposed method. The concept layer in flood disaster emergency knowledge graph defines the conceptual levels, the attributes and the semantic relationships of flood disaster events, disaster emergency tasks, disaster data, and methods. The data layer in flood disaster emergency knowledge graph realizes the extraction of entities and relationships from multi-source data. After the knowledge fusion process, 3 054 nodes and 12 689 relationship edges are obtained and stored in the Neo4j graph database. The flood disaster emergency knowledge graph realizes the transformation from multi-source data to interrelated knowledge.
Natural disasters occur frequently and pose a huge threat to China. Disaster prevention, mitigation, and disaster relief are eternal topics of human survival and development. However, in the field of disaster relief and emergency response, the relevant data increase sharply while the critical knowledge of emergency is obviously lacking. The "data-information-knowledge" transformation capacity is insufficient to meet the urgent needs of disaster prevention and reduction. Firstly taking natural disasters as the core, and around four elements of natural disaster events, disaster emergency tasks, disaster data, and methods, this paper proposes a knowledge graph construction method by combining a top-down approach and a bottom-up approach. Then, concept layer of knowledge graph is built from top to down, and the conceptual framework is formed through ontology modeling. Data layer of knowledge graph is built from bottom to top, and the relationship between entities is established through data acquisition, knowledge extraction, fusion, and storage. Finally, a flood disaster emergency knowledge graph is built to verify the validity of the proposed method. The concept layer in flood disaster emergency knowledge graph defines the conceptual levels, the attributes and the semantic relationships of flood disaster events, disaster emergency tasks, disaster data, and methods. The data layer in flood disaster emergency knowledge graph realizes the extraction of entities and relationships from multi-source data. After the knowledge fusion process, 3 054 nodes and 12 689 relationship edges are obtained and stored in the Neo4j graph database. The flood disaster emergency knowledge graph realizes the transformation from multi-source data to interrelated knowledge.
2020, 45(9): 1356-1366.
doi: 10.13203/j.whugis20190346
Abstract:
Spatial heterogeneity or non-stationarity in data relationships is one of the hot topics in spatial statistics or relative application fields, while the development of local techniques forms an essential part for the relative studies. Geographically weighted regression (GWR) provides spatially varying coefficient estimates via location-specific weighted regression model calibrations, to explore spatial heterogeneities or non-stationarities, quantitatively. It has been widely used in a number of fields, and become one of the most important tools for exploring spatial heterogeneities in data relationships. We summarized the GWR basics in model calibration, result interpretation, model diagnostics, reviewed its research progress and problems in its applications, respectively. Meanwhile, we sorted out the important extensions of the basic GWR technique, particularly in applying flexible distance metric choices in GWR model calibration, multiscale parameter estimates and spatiotemporal data modeling. In addition, we also introduced the main GWR tools or software accordingly to provide the users or readers comprehensive reference and knowledge on the GWR technique.
Spatial heterogeneity or non-stationarity in data relationships is one of the hot topics in spatial statistics or relative application fields, while the development of local techniques forms an essential part for the relative studies. Geographically weighted regression (GWR) provides spatially varying coefficient estimates via location-specific weighted regression model calibrations, to explore spatial heterogeneities or non-stationarities, quantitatively. It has been widely used in a number of fields, and become one of the most important tools for exploring spatial heterogeneities in data relationships. We summarized the GWR basics in model calibration, result interpretation, model diagnostics, reviewed its research progress and problems in its applications, respectively. Meanwhile, we sorted out the important extensions of the basic GWR technique, particularly in applying flexible distance metric choices in GWR model calibration, multiscale parameter estimates and spatiotemporal data modeling. In addition, we also introduced the main GWR tools or software accordingly to provide the users or readers comprehensive reference and knowledge on the GWR technique.
2020, 45(9): 1367-1377, 1437.
doi: 10.13203/j.whugis20200175
Abstract:
It lacks of the semantic expression of the mutual effects and interactions between operational entities and geographical entities and geographical phenomena in the existing simulation model of battlefield environment, and consequently, it is hard to reflect the dynamic change rules of the geographic environmental entities under the conditions of time and space. A spatio-temporal process model of battlefield geography environment based on simulation events is proposed to realize the integrated description and structured storage in spatio-temporal process semantics, so as to express the mutual effects and interactions between spatio-temporal objects from semantic perspective. In this model, the ontology method is used to comprehensively describe the spatio-temporal semantics and attribute semantics of simulation events, environmental entities and their behavioral process. Firstly, the spatio-temporal process semantic concepts are abstractly described based on object-oriented method, and the structural conceptual model is established by integrating the semantic relations and semantic operation rules. Secondly, according to the "individual-part-whole" cognitive principle of geospatial, the semantic and logical relationship of spatio-temporal process with hierarchical structure is constructed by top-down method, and semantic constraints are established based on event triggering to standardize semantic operation. Thirdly, the organization and storage structure of spatio-temporal process data is established according to the semantic features of data model, and the dynamic change process of spatio-temporal data driven by simulation event is realized through semantic mapping mechanism. Through the simulation events defined by the simulation system, and the spatiotemporal database and the geographical environment ontology database called by the model association relationship, the semantic attribute record of spatiotemporal process is realized from the data layer, which providing services for spatiotemporal data reasoning and backtracking. The specific performance is as follows: (1) the semantic description of the simulation events is the cause of the change of the environmental entity object; (2) the spatial semantics of the environmental entity objects describe the change information of the spatial location, geometric type and topological relationship of the object; (3) the temporal semantics of the environmental entity objects describe the temporal information of the object during the simulation process; (4) the attribute semantics of the environmental entity objects describe the change information of the object type, structure and function; (5) the process of entity behavior is represented by a series of operations of the attri-bute semantics of entity objects according to time series. The semantic model of spatio-temporal process is established by ontology as the core, integrating spatio-temporal object semantic information as the core to establish the overall framework of the model, describing and expressing the spatio-temporal semantics simultaneously, to form an object-oriented structure system that conforms to the cognitive law. Compared with the traditional simulation model structure, the dynamic changes of the battlefield geographical environment and the interaction and influence with the simulation events are reflected from the semantic point of view, making the change of spatio-temporal data conform to the development law of battlefield simulation, so the semantic correlation between spatio-temporal data and event information is strengthened by the function, improving the theory and method of dynamic modeling of battlefield environment. In the further work, the dynamic evolution mechanism of spatio-temporal data under the condition of continuous events, the extensibility and reusability of data semantic model, and the application and implementation of the model in complex systems will be further studied and explored to meet the needs of future systems.
It lacks of the semantic expression of the mutual effects and interactions between operational entities and geographical entities and geographical phenomena in the existing simulation model of battlefield environment, and consequently, it is hard to reflect the dynamic change rules of the geographic environmental entities under the conditions of time and space. A spatio-temporal process model of battlefield geography environment based on simulation events is proposed to realize the integrated description and structured storage in spatio-temporal process semantics, so as to express the mutual effects and interactions between spatio-temporal objects from semantic perspective. In this model, the ontology method is used to comprehensively describe the spatio-temporal semantics and attribute semantics of simulation events, environmental entities and their behavioral process. Firstly, the spatio-temporal process semantic concepts are abstractly described based on object-oriented method, and the structural conceptual model is established by integrating the semantic relations and semantic operation rules. Secondly, according to the "individual-part-whole" cognitive principle of geospatial, the semantic and logical relationship of spatio-temporal process with hierarchical structure is constructed by top-down method, and semantic constraints are established based on event triggering to standardize semantic operation. Thirdly, the organization and storage structure of spatio-temporal process data is established according to the semantic features of data model, and the dynamic change process of spatio-temporal data driven by simulation event is realized through semantic mapping mechanism. Through the simulation events defined by the simulation system, and the spatiotemporal database and the geographical environment ontology database called by the model association relationship, the semantic attribute record of spatiotemporal process is realized from the data layer, which providing services for spatiotemporal data reasoning and backtracking. The specific performance is as follows: (1) the semantic description of the simulation events is the cause of the change of the environmental entity object; (2) the spatial semantics of the environmental entity objects describe the change information of the spatial location, geometric type and topological relationship of the object; (3) the temporal semantics of the environmental entity objects describe the temporal information of the object during the simulation process; (4) the attribute semantics of the environmental entity objects describe the change information of the object type, structure and function; (5) the process of entity behavior is represented by a series of operations of the attri-bute semantics of entity objects according to time series. The semantic model of spatio-temporal process is established by ontology as the core, integrating spatio-temporal object semantic information as the core to establish the overall framework of the model, describing and expressing the spatio-temporal semantics simultaneously, to form an object-oriented structure system that conforms to the cognitive law. Compared with the traditional simulation model structure, the dynamic changes of the battlefield geographical environment and the interaction and influence with the simulation events are reflected from the semantic point of view, making the change of spatio-temporal data conform to the development law of battlefield simulation, so the semantic correlation between spatio-temporal data and event information is strengthened by the function, improving the theory and method of dynamic modeling of battlefield environment. In the further work, the dynamic evolution mechanism of spatio-temporal data under the condition of continuous events, the extensibility and reusability of data semantic model, and the application and implementation of the model in complex systems will be further studied and explored to meet the needs of future systems.
2020, 45(9): 1378-1385.
doi: 10.13203/j.whugis20200091
Abstract:
This study aims to explore building education capacity to improve disaster management in public awareness. We can improve public awareness of disaster risks through public education on landslide disasters. The current education in disaster courses is mainly aimed at students and ambulance personnel. Those education methods focus on textbook teaching and professional training, and the contents are too professional. There is no effective communication channel between educators and the public. Thus, this paper proposes a visual representation method of landslide disasters for public education. We prepared a concept map to organize and represent bits of knowledge of landslide, instantiating nodes of concept map as animation, then used animation to publicize. The landslide on June 24, 2017 in Diexi, Maoxian was selected to conduct a case test analysis. One short animation created by the method and one brief disaster report summarized by that animation is produced for a questionnaire. We collected and analyzed the results of the questionnaire. The results show that people tend to learn about landslides by watching animation, and they answer more questions correctly in the questionnaire after watching animation than reading the report. So the proposed method in this paper can effectively construct the visual content of landslide disaster knowledge and quickly help the public understand the landslide disaster knowledge.
This study aims to explore building education capacity to improve disaster management in public awareness. We can improve public awareness of disaster risks through public education on landslide disasters. The current education in disaster courses is mainly aimed at students and ambulance personnel. Those education methods focus on textbook teaching and professional training, and the contents are too professional. There is no effective communication channel between educators and the public. Thus, this paper proposes a visual representation method of landslide disasters for public education. We prepared a concept map to organize and represent bits of knowledge of landslide, instantiating nodes of concept map as animation, then used animation to publicize. The landslide on June 24, 2017 in Diexi, Maoxian was selected to conduct a case test analysis. One short animation created by the method and one brief disaster report summarized by that animation is produced for a questionnaire. We collected and analyzed the results of the questionnaire. The results show that people tend to learn about landslides by watching animation, and they answer more questions correctly in the questionnaire after watching animation than reading the report. So the proposed method in this paper can effectively construct the visual content of landslide disaster knowledge and quickly help the public understand the landslide disaster knowledge.
2020, 45(9): 1386-1394.
doi: 10.13203/j.whugis20190409
Abstract:
The emergency evacuation sign is one of the key factors that determine whether the personnel can escape safely. The rationality of its layout needs further quantitative optimization research. This paper takes the office building as the experimental area, with the help of the virtual reality eye-tracking experiment, analyzes the unreasonable layout of the directional emergency evacuation signs in the experimental area, and designs an effective modification and optimization scheme to improve the directional function of the emergency evacuation signs.Two groups of virtual eye movement evacuation experiments are designed. Each experiment consists of two experiments, in which the experimental group 1 uses the real evacuation sign layout, and the experimental group 2 uses the modified evacuation sign layout as the verification experiment. Compared with the experimental data, the evacuation time of the two experiments in experimental groups 1 and 2 was reduced by 30.28% and 30.99%, and the expected evacuation distance was reduced by 42.67% and 40.06%, so the evacuation time and the expected evacuation distance were significantly improved. The experimental results and data analysis prove the effectiveness of the modification method and scheme of directional emergency evacuation signs in the experimental area. At the same time, a new optimization method and process of directional emergency evacuation signs layout is established.
The emergency evacuation sign is one of the key factors that determine whether the personnel can escape safely. The rationality of its layout needs further quantitative optimization research. This paper takes the office building as the experimental area, with the help of the virtual reality eye-tracking experiment, analyzes the unreasonable layout of the directional emergency evacuation signs in the experimental area, and designs an effective modification and optimization scheme to improve the directional function of the emergency evacuation signs.Two groups of virtual eye movement evacuation experiments are designed. Each experiment consists of two experiments, in which the experimental group 1 uses the real evacuation sign layout, and the experimental group 2 uses the modified evacuation sign layout as the verification experiment. Compared with the experimental data, the evacuation time of the two experiments in experimental groups 1 and 2 was reduced by 30.28% and 30.99%, and the expected evacuation distance was reduced by 42.67% and 40.06%, so the evacuation time and the expected evacuation distance were significantly improved. The experimental results and data analysis prove the effectiveness of the modification method and scheme of directional emergency evacuation signs in the experimental area. At the same time, a new optimization method and process of directional emergency evacuation signs layout is established.
2020, 45(9): 1395-1402.
doi: 10.13203/j.whugis20200203
Abstract:
Geographic modeling and simulation is an important method for solving environmental issues and providing decision-making. Recently, research related to geographic modeling and simulation in an open web environment is mainly focused on model service sharing, while the calculation speed of model has been less studied. The terrestrial carbon cycle model plays a key role in the simulation of carbon cycle, service-oriented sharing has promoted it's development, but the time-consuming calculation speed limits their widespread applications. The large amount of calculation of terrestrial carbon cycle model results in a large amount of time to obtain the output. Currently, the model sharing strategies have not employed effective ways to improve the calculation performance of terrestrial carbon cycle models. A service-oriented decentralized computing method is proposed to speed up the calculation of these models. The main idea of this method is adding computing nodes to alleviate the pressure of the calculation of the terrestrial carbon cycle model based on the existing model sharing strategies. First, the terrestrial carbon cycle models are published as model services in the open web environment. Then, a task segmentation and dispatch strategy is designed to break the complex computing tasks into small steps and dispatch them to different computing nodes for distributed calculation. The study case of three typical terrestrial carbon cycle models show the feasibility and practicability of the proposed method and it can be used to improve the calculation speed of the terrestrial carbon cycle model.
Geographic modeling and simulation is an important method for solving environmental issues and providing decision-making. Recently, research related to geographic modeling and simulation in an open web environment is mainly focused on model service sharing, while the calculation speed of model has been less studied. The terrestrial carbon cycle model plays a key role in the simulation of carbon cycle, service-oriented sharing has promoted it's development, but the time-consuming calculation speed limits their widespread applications. The large amount of calculation of terrestrial carbon cycle model results in a large amount of time to obtain the output. Currently, the model sharing strategies have not employed effective ways to improve the calculation performance of terrestrial carbon cycle models. A service-oriented decentralized computing method is proposed to speed up the calculation of these models. The main idea of this method is adding computing nodes to alleviate the pressure of the calculation of the terrestrial carbon cycle model based on the existing model sharing strategies. First, the terrestrial carbon cycle models are published as model services in the open web environment. Then, a task segmentation and dispatch strategy is designed to break the complex computing tasks into small steps and dispatch them to different computing nodes for distributed calculation. The study case of three typical terrestrial carbon cycle models show the feasibility and practicability of the proposed method and it can be used to improve the calculation speed of the terrestrial carbon cycle model.
2020, 45(9): 1403-1411.
doi: 10.13203/j.whugis20190394
Abstract:
In a virtual battlefield environment, efficient organization of spatiotemporal data is a prerequisite for dynamically describing key elements of the battlefield and analyzing military action plans in real time. First, the latitude, longitude, and time are synchronized and hierarchically subdivided to construct a regular multi-resolution spatiotemporal grid. Then, based on the Hilbert curve, a spatiotemporal coding is designed. A spatiotemporal data indexing method based on Hilbert code is proposed. Based on this, experiments are designed to compare the spatiotemporal proximity of coding, index construction efficiency, and query efficiency. The results show that the Hilbert code method is superior to Morton code in terms of proximity. The index construction speed meets the needs of large-scale spatiotemporal data processing, and the query efficiency is better than the methods based on longitude-latitude-time query and Morton code query directly, which means that the Hilbert code method can be used as the basis for spatiotemporal operations such as deduction of battle plans in the virtual battlefield, visualization and analysis of battlefield environment elements.
In a virtual battlefield environment, efficient organization of spatiotemporal data is a prerequisite for dynamically describing key elements of the battlefield and analyzing military action plans in real time. First, the latitude, longitude, and time are synchronized and hierarchically subdivided to construct a regular multi-resolution spatiotemporal grid. Then, based on the Hilbert curve, a spatiotemporal coding is designed. A spatiotemporal data indexing method based on Hilbert code is proposed. Based on this, experiments are designed to compare the spatiotemporal proximity of coding, index construction efficiency, and query efficiency. The results show that the Hilbert code method is superior to Morton code in terms of proximity. The index construction speed meets the needs of large-scale spatiotemporal data processing, and the query efficiency is better than the methods based on longitude-latitude-time query and Morton code query directly, which means that the Hilbert code method can be used as the basis for spatiotemporal operations such as deduction of battle plans in the virtual battlefield, visualization and analysis of battlefield environment elements.
2020, 45(9): 1412-1421.
doi: 10.13203/j.whugis20190456
Abstract:
Dynamic deformation of virtual terrain is an important research content to enhance the dynamic adaptability of virtual geographic environment, which can support disaster simulation, combat simulation and so on, and also an important support to study human-environment interaction. Taking the dynamic generation of crater as an example, starting from explosion physical force and geometric fitting of crater shape, the construction method of virtual terrain deformation model is explored, and the calculation method of crater shape model is proposed, which coupled with geological characteristics. Compared with the existing results, the method is coupled with a variety of projectile parameters at the same time, which is convenient for the introduction of geological characteristics parameters, and can effectively calculate the explosion effect of different projectiles in different geological environments under different incident angles. At the same time, the existing method of crater region texture generation is improved. The new method considers the problem of texture map mixing in the case of multi-media composition of crater region. The verification results of unity show that the crater model can reflect the impact of different projectile incidence angle, explosive equivalent and geological characteristics. The deformation state of crater is similar to the actual situation, and the map of crater area can reflect the impact of different geological texture. The research results can provide support for the simulation of the dynamic change process of the crater, which caused by the projectile touchdown explosion in the virtual battlefield environment.
Dynamic deformation of virtual terrain is an important research content to enhance the dynamic adaptability of virtual geographic environment, which can support disaster simulation, combat simulation and so on, and also an important support to study human-environment interaction. Taking the dynamic generation of crater as an example, starting from explosion physical force and geometric fitting of crater shape, the construction method of virtual terrain deformation model is explored, and the calculation method of crater shape model is proposed, which coupled with geological characteristics. Compared with the existing results, the method is coupled with a variety of projectile parameters at the same time, which is convenient for the introduction of geological characteristics parameters, and can effectively calculate the explosion effect of different projectiles in different geological environments under different incident angles. At the same time, the existing method of crater region texture generation is improved. The new method considers the problem of texture map mixing in the case of multi-media composition of crater region. The verification results of unity show that the crater model can reflect the impact of different projectile incidence angle, explosive equivalent and geological characteristics. The deformation state of crater is similar to the actual situation, and the map of crater area can reflect the impact of different geological texture. The research results can provide support for the simulation of the dynamic change process of the crater, which caused by the projectile touchdown explosion in the virtual battlefield environment.
2020, 45(9): 1422-1428.
doi: 10.13203/j.whugis20190477
Abstract:
Geographic information system(GIS) visualization analysis is an important method for disaster research, and mobile augmented reality (MAR) brings new vitality into GIS visualization.MAR visualization of disaster scenes usually needs to process multi-source and massive data, which challenges the performance of MAR device. To achieve smooth and stable loading capability for MAR visualization of disaster scenes, we proposed a flow-based optimization method for disaster scene loading. First, a MAR scene was split and compressed by the level of detail(LOD) method, then the scene data were stored on a data server. When a MAR client browsed data in a determined area, our optimized method can help to request the data from the server, and control the data loading by using our designed transmission strategy and alleviate the bandwidth pressure through our designed caching mechanism. A prototype system was built to test the performance of the optimized method. Experimental results show that the optimized method can achieve fast loading performance for MAR visualization of disaster scenes, and breakthrough the data volume limit on HoloLens device, and succeed stably under different data volume.
Geographic information system(GIS) visualization analysis is an important method for disaster research, and mobile augmented reality (MAR) brings new vitality into GIS visualization.MAR visualization of disaster scenes usually needs to process multi-source and massive data, which challenges the performance of MAR device. To achieve smooth and stable loading capability for MAR visualization of disaster scenes, we proposed a flow-based optimization method for disaster scene loading. First, a MAR scene was split and compressed by the level of detail(LOD) method, then the scene data were stored on a data server. When a MAR client browsed data in a determined area, our optimized method can help to request the data from the server, and control the data loading by using our designed transmission strategy and alleviate the bandwidth pressure through our designed caching mechanism. A prototype system was built to test the performance of the optimized method. Experimental results show that the optimized method can achieve fast loading performance for MAR visualization of disaster scenes, and breakthrough the data volume limit on HoloLens device, and succeed stably under different data volume.
2020, 45(9): 1429-1437.
doi: 10.13203/j.whugis20190470
Abstract:
3D building models are widely used in geographic information systems, virtual reality, and building information models. Reasonable geometric simplification of the 3D building model can reduce its structural complexity and data size while maintaining the consistency of visual effects, thereby reducing the pressure of graphics rendering and improving the experience of scene interaction. The simplification of 3D building model is one of the hot issues in the field of virtual geographic environment. This paper introduces the problems in 3D building model simplification, analyzes the characteristics of existing simplification methods and classifies them from two perspectives. From the perspective of geometric features, the methods are divided into simplification based on projection features, symbolic expression, and structural features; from the perspective of multi-factor constraints, the methods are divided into simplification under texture constraint, semantic constraint and user's understanding and perception constraint. The advantages and disadvantages of different simplified methods are discussed and summarized. With the goal of building a continuous level of detail model, the development direction of 3D building model simplification research is discussed.
3D building models are widely used in geographic information systems, virtual reality, and building information models. Reasonable geometric simplification of the 3D building model can reduce its structural complexity and data size while maintaining the consistency of visual effects, thereby reducing the pressure of graphics rendering and improving the experience of scene interaction. The simplification of 3D building model is one of the hot issues in the field of virtual geographic environment. This paper introduces the problems in 3D building model simplification, analyzes the characteristics of existing simplification methods and classifies them from two perspectives. From the perspective of geometric features, the methods are divided into simplification based on projection features, symbolic expression, and structural features; from the perspective of multi-factor constraints, the methods are divided into simplification under texture constraint, semantic constraint and user's understanding and perception constraint. The advantages and disadvantages of different simplified methods are discussed and summarized. With the goal of building a continuous level of detail model, the development direction of 3D building model simplification research is discussed.
2020, 45(9): 1438-1447.
doi: 10.13203/j.whugis20180053
Abstract:
Road traffic flow is an important feature to measure the importance of the road. Based on the GPS trajectory data and road network data, this paper proposed a novel method for the selection of road network considering both the commonly used geometric features (i.e. length, topological connection, distribution density, closeness and betweenness) and the sematic information—long-term week average traffic flow of the roads. Firstly, in order to ensure the continuity of the road network at small scale, the strokes of the original road network are obtained by using the continuity and direction constraints of Gestalt laws. Then, the geometric features and the traffic flow information of each strokes are computed. Further, a global measure is defined based on the geometric features and traffic flow information, and the weights between the length, topological connection, distribution density, closeness, betweenness and traffic flow are determined using the modified entropy-weight method. Finally, the proposed method of this paper is verified by using Wuhan road network data and taxi GPS trajectory data. The experimental results show that the proposed method can maintain the connectivity of the original road network and tend to select the important roads that are consistent with the human perception. On the other hand, this method can be used to discover the roads that are designed as high-level roads but in contrary rarely used in reality for applications such as urban road network planning and reconstruction.
Road traffic flow is an important feature to measure the importance of the road. Based on the GPS trajectory data and road network data, this paper proposed a novel method for the selection of road network considering both the commonly used geometric features (i.e. length, topological connection, distribution density, closeness and betweenness) and the sematic information—long-term week average traffic flow of the roads. Firstly, in order to ensure the continuity of the road network at small scale, the strokes of the original road network are obtained by using the continuity and direction constraints of Gestalt laws. Then, the geometric features and the traffic flow information of each strokes are computed. Further, a global measure is defined based on the geometric features and traffic flow information, and the weights between the length, topological connection, distribution density, closeness, betweenness and traffic flow are determined using the modified entropy-weight method. Finally, the proposed method of this paper is verified by using Wuhan road network data and taxi GPS trajectory data. The experimental results show that the proposed method can maintain the connectivity of the original road network and tend to select the important roads that are consistent with the human perception. On the other hand, this method can be used to discover the roads that are designed as high-level roads but in contrary rarely used in reality for applications such as urban road network planning and reconstruction.
2020, 45(9): 1448-1454.
doi: 10.13203/j.whugis20180125
Abstract:
Landmark extraction is a hotspot of spatial cognition and spatial knowledge organization research. Saliency measurement model is a most important method of landmark extraction, of which the principle is the weighted evaluation of the appearance, structure and semantics of objects. Considering the spatial distribution and geometric characteristics of objects, and it is difficult to extract landmarks with more consistent features, making it a complex process. From the viewpoint of composite features in Voronoi domain, a landmark extraction method is proposed to explore the geometric feature reflection of landmark from individual to its neighborhoods, based on the height of Voronoi element, Voronoi k-order neighborhood crevice and Voronoi k-order neighborhood visibility. Comparative experiments show that: (1) Compared with the landmark extracted by the existing methods with the results of traditional saliency measurement model, which verifies the effectiveness of this method; (2) As for the characteristics of ground property, the geometric features contained in Voronoi diagram can effectively represent the landmarks, reducing the complexity for feature selection of landmarks.
Landmark extraction is a hotspot of spatial cognition and spatial knowledge organization research. Saliency measurement model is a most important method of landmark extraction, of which the principle is the weighted evaluation of the appearance, structure and semantics of objects. Considering the spatial distribution and geometric characteristics of objects, and it is difficult to extract landmarks with more consistent features, making it a complex process. From the viewpoint of composite features in Voronoi domain, a landmark extraction method is proposed to explore the geometric feature reflection of landmark from individual to its neighborhoods, based on the height of Voronoi element, Voronoi k-order neighborhood crevice and Voronoi k-order neighborhood visibility. Comparative experiments show that: (1) Compared with the landmark extracted by the existing methods with the results of traditional saliency measurement model, which verifies the effectiveness of this method; (2) As for the characteristics of ground property, the geometric features contained in Voronoi diagram can effectively represent the landmarks, reducing the complexity for feature selection of landmarks.
2020, 45(9): 1455-1460.
doi: 10.13203/j.whugis20180268
Abstract:
Ground subsidence monitoring is an effective method to forecast geological hazard, and time series model is the main model for ground subsidence prediction. To take into account both the observation errors existing in coefficient matrix and observation vector, in this contribution, the time series model of ground subsidence is developed to improve errors-in-variables (EIV) model, while the traditional model only takes into account the observation error existing in observation error. Besides, to improve efficiency and accuracy of computation model parameters, prior information is utilized to establish EIV model with inequality constraints, and the inequality constraints model for ground subsidence prediction is converted into quadratic programming of nonlinear model. And the iterative algorithm which is combined with median function is proposed. The efficiency and feasibility of the presented algorithm are verified through the instances, which are compared with the traditional least squares estimation algorithm and current algorithm for EIV model.
Ground subsidence monitoring is an effective method to forecast geological hazard, and time series model is the main model for ground subsidence prediction. To take into account both the observation errors existing in coefficient matrix and observation vector, in this contribution, the time series model of ground subsidence is developed to improve errors-in-variables (EIV) model, while the traditional model only takes into account the observation error existing in observation error. Besides, to improve efficiency and accuracy of computation model parameters, prior information is utilized to establish EIV model with inequality constraints, and the inequality constraints model for ground subsidence prediction is converted into quadratic programming of nonlinear model. And the iterative algorithm which is combined with median function is proposed. The efficiency and feasibility of the presented algorithm are verified through the instances, which are compared with the traditional least squares estimation algorithm and current algorithm for EIV model.
2020, 45(9): 1461-1468.
doi: 10.13203/j.whugis20180261
Abstract:
Out the error source in tradition of multi-beam sounding system adjustment of post-processing methods are greatly influenced by factors such as sound velocity error limitation of application of adjacent strips the central beam is put forward to build each ping the topography of the trend line as a prior information, using Kalman filtering under the influence of the integrated error of sound sounding data of systemic error correction method. Firstly, the central beam data of adjacent bands with relatively high accuracy of the sounding data were extracted, and the trend line of the regional seabed topography of the area under which the multi-beam was located was constructed roughly. Secondly, the deviation of the observed value and the deviation of the trend line of the seabed topography are obtained by using the data of the overlaps between the central beam of the detection line and the main measuring line. Finally, based on the deviation obtained, the construction trend line is used as the prior information to correct the data using Kalman filtering, and the accuracy of the corrected data is analyzed and evaluated. The experimental results show that the system error of the edge beam can be corrected effectively by Kalman filter.
Out the error source in tradition of multi-beam sounding system adjustment of post-processing methods are greatly influenced by factors such as sound velocity error limitation of application of adjacent strips the central beam is put forward to build each ping the topography of the trend line as a prior information, using Kalman filtering under the influence of the integrated error of sound sounding data of systemic error correction method. Firstly, the central beam data of adjacent bands with relatively high accuracy of the sounding data were extracted, and the trend line of the regional seabed topography of the area under which the multi-beam was located was constructed roughly. Secondly, the deviation of the observed value and the deviation of the trend line of the seabed topography are obtained by using the data of the overlaps between the central beam of the detection line and the main measuring line. Finally, based on the deviation obtained, the construction trend line is used as the prior information to correct the data using Kalman filtering, and the accuracy of the corrected data is analyzed and evaluated. The experimental results show that the system error of the edge beam can be corrected effectively by Kalman filter.
2020, 45(9): 1469-1477.
doi: 10.13203/j.whugis20180278
Abstract:
Real-time and high-quality 3D reconstruction of indoor scenes has been a research focus in the field of augmented reality and robotics. However, the 3D reconstruction methods using RGB-D sensors suffer from weaknesses such as poor local model quality and producing holes in points cloud models. The two key factors that affect the quality of 3D reconstruction are the accuracy of the pose parameters derived from points cloud registration and the accuracy of loop closure. Firstly, an improved ElasticFusion algorithm is proposed to achieve better reconstruction quality in real time, which is achieved by improving the strategy of searching matching points in the iterative closest point (ICP) algorithm. Furthermore, radial basis functions are used to construct implicit surfaces in order to fill holes in the point clouds models that are generated in the previous step. In the end, benchmarks such as ICL-NUIM are used to evaluate the proposed algorithm. The experimental results have shown that our algorithm can significantly improve the quality of model reconstruction and the accuracy of the camera trajectory estimation.
Real-time and high-quality 3D reconstruction of indoor scenes has been a research focus in the field of augmented reality and robotics. However, the 3D reconstruction methods using RGB-D sensors suffer from weaknesses such as poor local model quality and producing holes in points cloud models. The two key factors that affect the quality of 3D reconstruction are the accuracy of the pose parameters derived from points cloud registration and the accuracy of loop closure. Firstly, an improved ElasticFusion algorithm is proposed to achieve better reconstruction quality in real time, which is achieved by improving the strategy of searching matching points in the iterative closest point (ICP) algorithm. Furthermore, radial basis functions are used to construct implicit surfaces in order to fill holes in the point clouds models that are generated in the previous step. In the end, benchmarks such as ICL-NUIM are used to evaluate the proposed algorithm. The experimental results have shown that our algorithm can significantly improve the quality of model reconstruction and the accuracy of the camera trajectory estimation.
2020, 45(9): 1478-1484.
doi: 10.13203/j.whugis20180129
Abstract:
For unstablity and unreliability of the traditional nonlinear least squares solution of ill-conditioned problems, a Frozen-Barycentre iterative algorithm is proposed based on the least squares solution property of nonlinear ranging location. The method applies the Samaski technique to Barycentre iterative method, to realize the transformation of internal and external iterations. This algorithm improves the convergence efficiency of Barycentre iterative method by reducing the derivative calculation. And the numerical convergence experiments of the method are performed. The results show that the numerical precision of proposed method is better than that of the linearized adjustment estimation, and the convergence property is more efficient than the Barycentre iterative method.
For unstablity and unreliability of the traditional nonlinear least squares solution of ill-conditioned problems, a Frozen-Barycentre iterative algorithm is proposed based on the least squares solution property of nonlinear ranging location. The method applies the Samaski technique to Barycentre iterative method, to realize the transformation of internal and external iterations. This algorithm improves the convergence efficiency of Barycentre iterative method by reducing the derivative calculation. And the numerical convergence experiments of the method are performed. The results show that the numerical precision of proposed method is better than that of the linearized adjustment estimation, and the convergence property is more efficient than the Barycentre iterative method.
2020, 45(9): 1485-1492.
doi: 10.13203/j.whugis20180483
Abstract:
Monitoring the dynamic changes of coastline is of great significance to the protection and development of coastal zone. Combined with multi-source synthetic aperture radar (SAR) satellite images and optical satellite remote sensing images, using rule-based object-oriented information extraction, combined with artificial visual correction, the coastline length and water area change information of Jiaozhou Bay are extracted every five years from 2000 to 2018. The results show that the coastline length of Jiaozhou Bay has increased by 43.5 km and the area of Jiaozhou Bay has shrunk by 24.9 km2 in the past 20 years. The coastline changes are mainly influenced by artificial factors such as offshore aquaculture activities, port construction, and natural factors such as river sediment accumulation and tidal action. From the point of view of three key areas, human factors have led to the change of coastline and the shrinkage of sea area in Jiaozhou Bay. The shoreline changes in three key areas of Jiaozhou Bay, namely, Red Island on the north coast, Yellow Island on the west coast and Qingdao on the east coast, show that the shoreline changes in Jiaozhou Bay are mainly influenced by human factors.
Monitoring the dynamic changes of coastline is of great significance to the protection and development of coastal zone. Combined with multi-source synthetic aperture radar (SAR) satellite images and optical satellite remote sensing images, using rule-based object-oriented information extraction, combined with artificial visual correction, the coastline length and water area change information of Jiaozhou Bay are extracted every five years from 2000 to 2018. The results show that the coastline length of Jiaozhou Bay has increased by 43.5 km and the area of Jiaozhou Bay has shrunk by 24.9 km2 in the past 20 years. The coastline changes are mainly influenced by artificial factors such as offshore aquaculture activities, port construction, and natural factors such as river sediment accumulation and tidal action. From the point of view of three key areas, human factors have led to the change of coastline and the shrinkage of sea area in Jiaozhou Bay. The shoreline changes in three key areas of Jiaozhou Bay, namely, Red Island on the north coast, Yellow Island on the west coast and Qingdao on the east coast, show that the shoreline changes in Jiaozhou Bay are mainly influenced by human factors.
Articles online first have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
, Available online ,
doi: 10.13203/j.whugis20200221
Abstract:
The development of ICT (Information and Communications Technology) provides new challeng⁃ es and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about carto⁃ graphic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to ex⁃ plore new fields. The development of "digits and culture" has pushed the game to the forefront of hightech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, the paper explores the charac⁃ teristics and essence of game map and its implications to the real physical world by the dimensionalities, in⁃ teractivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
The development of ICT (Information and Communications Technology) provides new challeng⁃ es and opportunities for modern cartography. Totally different from the traditional cartography in the fields of the research methods and themes, modern cartography trends to digital cyberspace from paper map, and cartographic theories are urged to be improved. However, the understanding of the theories about carto⁃ graphic virtual space have great differences within the professional domain, and the internal contradictions and transboundary invasion make map gradually become an appurtenance of Internet products. To learning from certain domains to analyse and handle them, challenges have prompted cartographic scholars to ex⁃ plore new fields. The development of "digits and culture" has pushed the game to the forefront of hightech. Games are often geographically significant, and maps of game are a combination of ICT and maps. Based on the cyberspace in game map with instances as the research subject, the paper explores the charac⁃ teristics and essence of game map and its implications to the real physical world by the dimensionalities, in⁃ teractivity, narrativity, exploration and cultural dissemination of game maps to discover the extension of cartography, which would replenish and perfect modern cartographic theory and promote its development.
, Available online ,
doi: 10.13203/j.whugis20200172
Abstract:
Aiming at the mixed observation data of multiple distribution forms, a P-model distributed mixed model is established. Considering that the mixed number in the model belongs to incomplete data, the EM algorithm is introduced to estimate the parameters of the mixed model and the P-model mixed model parameters are derived in detail The estimated iteration formula and the corresponding iteration steps are given. Finally, the mixed Gaussian distribution data, Laplacian distribution and Gaussian distribution mixed data, and the residual data of measured GPS observations are used to verify the correctness and adaptability of the formula in this paper. The results of the calculation examples show that, compared with the single probability distribution, the P-parameter hybrid model can accurately reflect the actual situation of the data distribution, and the model parameters estimated by the EM algorithm have higher accuracy.
Aiming at the mixed observation data of multiple distribution forms, a P-model distributed mixed model is established. Considering that the mixed number in the model belongs to incomplete data, the EM algorithm is introduced to estimate the parameters of the mixed model and the P-model mixed model parameters are derived in detail The estimated iteration formula and the corresponding iteration steps are given. Finally, the mixed Gaussian distribution data, Laplacian distribution and Gaussian distribution mixed data, and the residual data of measured GPS observations are used to verify the correctness and adaptability of the formula in this paper. The results of the calculation examples show that, compared with the single probability distribution, the P-parameter hybrid model can accurately reflect the actual situation of the data distribution, and the model parameters estimated by the EM algorithm have higher accuracy.
Articles just accepted have been peer-reviewed and accepted, which are not yet assigned to volumes /issues, but are citable by Digital Object Identifier (DOI).
Display Method:
, Available online ,
doi: 10.13203/j.whugis20200098
Abstract:
Unmanned Aerial Vehicle; Antarctic Expedition; Climate Change; Photogrammetry; Glaciology; Ecology; Geomorphology
Unmanned Aerial Vehicle; Antarctic Expedition; Climate Change; Photogrammetry; Glaciology; Ecology; Geomorphology
Accepted Manuscript
, Available online ,
doi: 10.13203/j.whugis20200422
Abstract:
Public health and public security events present the importance of crow dynamics observation. The crow dynamics observation should be a key component of human-orient observation, and the necessary elements of global observation system framework consisting observations of space, sky, land, ocean and people. This paper firstly introduces a concept of crow dynamics observation, defines its scientific connotations and boundaries, and highlights the role and significance of this theory. Then, from the perspective of public health and safety emergency, this paper analyzes the characteristics of accuracy, scientificity and on-demand in crow dynamics observation requirements, and introduces the state of art of crow dynamics observation includingdata perception of crow dynamics, sampling and expansion of population scale, and quantitative modeling of crow dynamics, crow dynamics research field, etc.Next, this paper thinks about the observation tasks of crowd dynamics from four important aspects, such as, rigorous distinction between individuals and groups, abnormal observations centered on spatiotemporal processes, breakthroughs in observational thinking under missing data, and scientific predictions of crowd dynamics under specific scenarios, etc. Finally, this paper summarizes three important research challengescombined with public health and safety emergency tasks, namely, the challenge of improving observation capabilities, the challenge of fusion observation of human and earth observation, and the research ethical challenge of human observation. In short, the concepts, thinking dimensions and challenges proposed in this article provide basic theories and methods for major public health and safety emergencies, clarifying the laws of urban multi-type spatial development, mastering the differentiation mechanism of spatial evolution, and controlling urban spatial development paths. All of them shows asignificanceof the frontier exploration.
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