Geographic Information Visualization Research Articles

An MPI-based parallel genetic algorithm for multiple geographical feature label placement based on the hybrid of fixed-sliding models

ABSTRACT Multiple Geographical Feature Label Placement (MGFLP) has been a fundamental problem in geographic information visualization for decades. Moreover, the nature of label positioning has proven to be an Nondeterministic polynomial-time hard (NP-hard) problem. Although advances in computer technology and robust approaches have addressed the problem of label positioning, the lengthy running time of MGFLP has not been a major focus of recent studies. Based on a hybrid of the fixed-position and sliding models, a Message Passing Interface (MPI) parallel genetic algorithm is proposed in the present study for MGFLP to label mixed types of geographical features. To evaluate the quality of label placement, a quality function is defined based on four quality metrics: label-feature conflict; label-label conflict; label association with the corresponding feature; label position priority for all three types of features. The experimental results show that the proposed algorithm outperforms the DDEGA, DDEGA-NM, and Parallel-MS in both label placement quality and computation time efficiency. Across three datasets, compared to Parallel-MS, running times decreased from 118.45 to 8.34, 45.98 to 3.51, and 20.01 to 0.43 min, with further reductions in label-label and label-feature conflicts.

Geographic information system and information visualization capacity building: Successful polio eradication and current and future challenges in the COVID-19 era for the World Health Organization's African region.

Despite a half-century-long global eradication effort, polio continues to have a devastating impact on individuals and communities worldwide, especially in low-income countries affected by conflict or geographic barriers to immunization programs. In response, the World Health Organization (WHO) Global Polio Eradication Initiative (GPEI) employs disease surveillance and vaccination campaigns coordinated through the WHO Regional Office for Africa (AFRO) Geographic Information System (GIS) Centre. Established in 2017, the AFRO GIS Centre played a key role in the eradication of wild-type polioviruses (WPVs) in 2020, but the COVID-19 pandemic, emergence of circulating vaccine-derived polioviruses, and transmission of WPV1 from Central Asia have led to a resurgence of polio in Sub-Saharan Africa. The AFRO GIS comprises a set of mobile device or cloud-based tools for geospatial data collection, analysis, and visualization. Using tools such as Auto-Visual Acute Flaccid Paralysis Detection and Reporting, electronic surveillance, and Integrated Supportive Supervision, GIS personnel collect polio case numbers and locations, track field worker activities, follow the movements of nomadic populations vulnerable to polio and other diseases, and determine needs for further healthcare deployments. The system is location specific and operates in real time, enabling the AFRO GIS to promptly target its responses to polio, COVID-19, Ebola virus disease, and other public health crises and natural disasters. The present review describes the components of the AFRO GIS and how the AFRO GIS Centre coordinated on-the-ground polio eradication efforts to help secure Africa's certification as WPV free. It also examines current and prospective challenges regarding other disease outbreaks in the COVID-19 era and how the AFRO GIS Centre is addressing these ongoing public health needs.

Web-based agricultural infrastructure digital twin system integrated with GIS and BIM concepts

Geographic Information Systems (GIS) are currently used in agriculture to represent various farming-related geographical information. While prior research has highlighted the potential of GIS in visualizing agricultural data, it still faces limitations in terms of model quality, interaction capabilities, and representing detailed topographic information, particularly in hydrological structures like culverts, irrigation systems, and drainage facilities. A method integrating Building Information Modeling (BIM) concepts with GIS is proposed to overcome these limitations. To achieve this, information on agricultural infrastructure in beneficiary areas was collected through field surveys and photos captured by Unmanned Aerial Vehicle (UAV). Subsequently, a digital twin model was created with various characteristics and information about agricultural hydraulic structures such as land shape, sluices, and channels of the entire beneficiary area of the test bed (Heungeop reservoir in the City of Wonju, Gangwon Province, South Korea) based on this information. A web-based geographic information visualization platform (Cesium) was integrated with the concepts of BIM to check the information associated with the selected 3D agricultural infrastructure models in a pop-up window. The proposed method overcomes the limitations of existing GIS information representation by enabling a detailed depiction of the agricultural environment. It allows for an intuitive understanding of information such as structural features, details of the material, history of maintenance, year of completion, etc., on agricultural infrastructure through a pop-up window, providing a foundation for research on efficient management and planning.

Study on smart grid fault detection based on ZigBee and MapX technologies

As the complexity of the power system and the increasing demand for electricity continue to rise, ensuring the reliability and stability of the power system becomes critically important. This study utilizes ZigBee communication modules to establish a sensor network for real-time monitoring of the power system's status and employs MapX technology to achieve geographic information visualization of the power system. Through an improved RBF-PCA-WFCM algorithm, grid data can be dimensionally reduced, enabling simulation training tailored to grid loads, resulting in more accurate algorithm analysis and optimization. This paper introduces fault localization and diagnostic methods, as well as clustering optimization algorithms, to achieve fault monitoring, analysis, and identification in the smart power grid. Research findings demonstrate that the intelligent power grid data analysis and fault detection system based on ZigBee and MapX technologies can enhance the reliability of the power system and better support the increasing demands of the evolving field of electricity.

Geographical Information Visualization on a Panoramic Sphere in an Immersive Environment

Geographical Information Visualization on a Panoramic Sphere in an Immersive Environment

An AR Map Virtual–Real Fusion Method Based on Element Recognition

The application of AR to explore augmented map representation has become a research hotspot due to the growing application of AR in maps and geographic information in addition to the rising demand for automated map interpretation. Taking the AR map as the research object, this paper focuses on AR map tracking and registration and the virtual–real fusion method based on element recognition. It strives to establish a new geographic information visualization interface and application model. AR technology is applied to the augmented representation of 2D planar maps. A step-by-step identification and extraction method of unmarked map elements are designed and proposed based on the analysis of the characteristics of planar map elements. This method combines the spatial and attribute characteristics of point-like elements and line-like elements, extracts the color, geometric features, and spatial distribution of map elements through computer vision methods, and completes the identification and automatic extraction of map elements. The multi-target image recognition and extraction method based on template and contour matching, and the line element recognition and extraction method based on color space and area growth are introduced in detail. Then, 3D tracking and registration is used to realize the unmarked tracking and registration of planar map element images, and the AR map virtual–real fusion algorithm is proposed. The experimental results and results of an analysis of stepwise identification and extraction of unmarked map elements and map virtual–real fusion reveal that the stepwise identification of unmarked map elements and map model virtual–real fusion studied in this paper is effective. Through the analysis of map element step-by-step recognition efficiency and recognition rate, it is proved that the element step-by-step method in this paper is fast, its recognition efficiency meets the AR real-time requirements, and its recognition accuracy is high.

Geographic Information Visualization and Sustainable Development of Low-Carbon Rural Slow Tourism under Artificial Intelligence

This study conducts in-depth research on geographic information visualization and the sustainable development of low-carbon rural slow tourism under artificial intelligence (AI) to analyze and discuss the visualization of geographic information and the sustainable development of low-carbon slow tourism in rural areas. First, the development options related to low-carbon tourism in rural areas are discussed. Then, a low-carbon rural slow tourism recommendation method based on AI and a low-carbon rural tourism scene recognition method based on Cross-Media Retrieval (CMR) data are proposed. Finally, the proposed scheme is tested. The test results show that the carbon dioxide emissions of one-day tourism projects account for less than 10% of the total tourism industry. From the proportion, it is found that air transport accounts for the largest proportion, more than 40%. With the development of time, the number of rural slow tourists in Guizhou has increased the most, while the number of rural slow tourists in Yunnan has increased to a lesser extent. In the K-means clustering model, the accuracy of scenario classification based on the semantic features of scene attributes is 5.26% higher than that of attribute likelihood vectors. On the Support Vector Machine classifier, the scene classification accuracy based on the semantic features of scene attributes is 19.2% higher than that of the scene classification based on attribute likelihood vector features. CMR techniques have also played a satisfying role in identifying rural tourism scenarios. They enable passengers to quickly identify tourist attractions to save preparation time and provide more flexible time for the tour process. The research results have made certain contributions to the sustainable development of low-carbon rural slow tourism.

ГЕОІНФОРМАЦІЙНА СИСТЕМА – ДІЄВИЙ ІНСТРУМЕНТ ДОСЛІДЖЕННЯ ВПЛИВУ ГІБРИДНОЇ ВІЙНИ НА СОЦІАЛЬНУ БЕЗПЕКУ ЛЮДИНИ

Social security of the state is the ability to guarantee and provide its citizens with safe and decent living standards. Study of the impact of the war on the state of national security, in particular human social security, will help to identify weaknesses in the state policy implementation in the political, economic and social areas. The impact of Russia's full-scale war against our country on the social security of Ukrainians requires substantiation of new, more effective mechanisms and tools for strengthening human social security in times of war. Under these circumstances, there is a need to apply new technologies to manage the socio-economic processes of the state for analysis and decision-making, and to reflect the current situation. These technologies will make it possible to predict scenarios and offer managers at all levels the best ways to achieve a balanced result. We need technologies that can effectively combine space and time with large amounts of special data in the form of attribute information about objects in the operational environment, background information about regions, climatic conditions, socio-economic conditions and processes in the region, etc. The need for prompt decision-making based on real indicators of anthropogenic, social, and environmental nature, taking into account the factors of space and time in a particular region or area of study, necessitates the involvement of specialized software platforms – geographic information systems that combine analytical capabilities with geospatial analysis. Today, a large number of general-purpose geographic information systems have been developed, but despite the variety of such software products, there is still a need to create specialized geographic information documents and databases that allow obtaining up-to-date geographic information data, the use of which leads to a real reduction in the time required to solve specialized tasks of information management systems. The analysis and decision support system in the environment of existing geographic information platforms will allow to take into account the influence of external factors, analyze the possibility of development, expansion, and monitor the state of the general environment when assessing the current state of input data, using information on the spatial distribution of the necessary resources, information on the competitive environment, etc. With the help of spatial and surface analysis modules, a GIS user can analyze spatially compatible objects and their interrelationships, taking into account the dynamics of their development. Currently, the world leader among geographic information systems is the ArcGIS products. It is a complete system that allows you to collect, organize, manage, analyze, exchange and distribute geographic data. Additionally, ArcGIS, depending on the type and specification of the platform, has other specialized modules that provide a wide range of opportunities for working with geodata and their visual display, namely: creation, management, visualization, analysis and exchange of geographic information. In addition, there are many compatible applications and extensions that integrate into the GIS platform and are focused on solving highly specialized tasks, such as assessing the state of the environment (water, soil, vegetation) or forecasting the development of natural phenomena and man-made emergencies. The article analyzes and substantiates the approaches to the use of a geographic information system as an effective tool for studying the impact of a full-scale war on human social security, improving the efficiency, completeness and quality of information and spatial support for management processes. The modern and full-featured ArcGIS system is considered as a platform that allows not only to form a geographic information system of any scale and purpose, but also to form on its basis an effective system of socio-economic monitoring, which is combined with decision support systems. The article presents an algorithm for studying the impact of a full-scale war on human social security using the ArcGIS system as an effective decision support tool with the use of spatially specialized databases.

A novel method for adaptive terrain rendering using memory-efficient tessellation codes for virtual globes

Virtual globes render large-scale real-world earth’s surface in real-time for geographic information visualization. Modern GPUs have introduced hardware tessellation features for high-performance rendering. Patch-based terrain rendering using hardware tessellation introduces cracks and swimming artifacts during navigation. Hardware tessellation-based terrain rendering methods limit the tessellation factors to power-of-two and render patches with discrete-level-of-detail (DLOD). We present a novel method for adaptive terrain rendering using tessellation codes. In the proposed method, we present novel memory-efficient bit-field-based tessellation codes to encode patch Level-of-detail (LOD). The encoding scheme enabled patch rendering with Continuous-level-of-detail (CLOD) on tessellation hardware. The view-dependent simplification algorithm simplifies and encodes the patch’s Level-of-detail (LOD) in tessellation codes. The proposed method, based on tessellation codes, tessellates patches as uniformly spaced vertices grid. A novel relocation algorithm, based on tessellation codes, relocates uniformly spaced vertices to construct an encoded simplified vertices grid to avoid boundary cracks and swimming artifacts. The tessellation codes consumed 28 kilobytes of memory for a patch size of 65. The proposed method rendered 2.5 million triangles with a frame rate of 570 frames-per second for an ultra-HD display. The proposed method achieved a high simplification and rendering rate with low computational and memory usage as compared to state-of-the-art methods.

Social Media and Emergency Services: Information Sharing about Cases of Missing Persons in Rural Sweden

The aim of this article is to investigate the nature of information sharing in social media about missing persons by using social media data (mostly Twitter) and conventional media coverage (media archives), adopting a platial perspective to this geographical information. By focusing on the cases of three people gone missing, we report on ways in which civil society establishes relational networks through social media to collectively support local searches and share information in rural Sweden. Geographical information systems and visualization techniques underlie the methodology of this study. Findings show that the geography of information sharing in social media about a missing person is not random, revealing a globally dispersed pattern across the country. Information sharing contains more emotional than informational content, hitting a peak of spread after a person is found deceased. This finding indicates that the value of information shared by social media as a problem-solving resource might have so far been overestimated in the process of finding missing persons. In addition, tweets show indications that voluntary organizations constitute a valuable resource in rural contexts but not without impact on the existing networks of stakeholders delivering emergency services.

Design of Geographic Information Visualization System for Marine Tourism Based on Data Mining

Zhu, W.; Hou, Y.; Wang, E., and Wang, Y., 2020. Design of geographic information visualization system for marine tourism based on data mining. In: Yang, Y.; Mi, C.; Zhao, L., and Lam, S. (eds.), Global Topics and New Trends in Coastal Research: Port, Coastal and Ocean Engineering. Journal of Coastal Research, Special Issue No. 103, pp. 1034–1037. Coconut Creek (Florida), ISSN 0749-0208.This paper presents a design scheme of marine tourism geographic information visualization system based on big data fusion and B/S architecture. The software development design of marine tourism geographic information visualization system is carried out under embedded Linux kernel and B/S architecture. The algorithm design of sea tourism geographic information visualization is carried out by using big data mining and fuzzy information fusion clustering method. The software design consists of marine tourism geographic information collection module, marine tourism geographic information BIM reconstruction module, database module, marine tourism geographic information interaction module and integrated information processing module, etc. The basic database structure of marine tourism geographic information visualization system is constructed under the B/S structure system, and program loading and automatic compilation design are adopted to realize the software development of marine tourism geographic information visualization system under bus control and embedded environment. The test results show that the information integration and processing ability of marine tourism geographic information visualization is strong, the visualization information fusion and mining performance of marine tourism are good, and the result of visual analysis of marine tourism geographic information is stable and reliable.

The Effects of Length and Orientation on Numerical Representation in Flow Maps

Flow maps are a common type of geographic information visualization in which lines that symbolize flow are typically varied in width to represent differences in the magnitude of the flow. An accurate perception of thickness is critical to numerical representation in flow maps. Previous studies have identified some of the factors, such as horizontal–vertical visual illusions and color size effects, that affect the perceived size of objects. However, the question of whether multiple visual variables that encode flow lines, such as length, orientation, and shape, interfere with their perceived thicknesses, remains unanswered. In this study, we performed a user study to determine the effect of length and orientation on thickness perception. The result indicates that the horizontal orientation is perceived to be thicker than the vertical orientation, and a short length is perceived to be thicker than a long length. Furthermore, we report and discuss other results (e.g., on adjustment direction) that are consistent with previous work. Although this study constitutes basic research, accumulating evidence on thickness perception is essential to this field of science. This study may contribute to our understanding of the factors that influence the perception of the thickness of lines on a flow map. We provide some concrete guidelines for the design of flow maps that may be beneficial to map designers.

Visualization Analysis of Health Informatics Research from 2001 to 2018

To analyse the scientific outputs of health informatics research and explore its frontiers and hotspots, we retrieve publications on health informatics research from the Web of Science Core Collection between 2001 and 2018. Geographic information system mapping and visualization techniques were used for analysing the countries, journals, institutions, authors, references and keywords of publications. Timelines of co-citation clusters and keywords with citation bursts were created to study the emerging trends and hotspots. Six thousand seventy-seven publications were identified in health informatics research; the annual number of publications has increased rapidly over the last two decades. Keywords analysis indicated that ‘big data’ for health informatics and clinical informatics could become a research frontier. This study reveals the hot spots, structure and trend of health informatics research. Nevertheless, further research and cooperation are needed.

Automated map projection selection for GIS

ABSTRACTThe selection of an appropriate map projection has a fundamental impact on the visualization and analysis of geographic information. Distortion is inevitable and the decision requires simultaneous consideration of several different factors; a process which can be confusing for many cartographers and GIS users. The last few decades have seen numerous attempts to create automated map projection selection solutions based on traditional classification and selection guidelines, but there are no existing tools directly accessible to users of GIS software when making projection selection decisions. This paper outlines key elements of projection selection and distortion theory, critically reviews the previous solutions, and introduces a new tool developed for ESRI’s ArcGIS, employing an original selection method tailored to the specific purpose and geographical footprint characteristics of a GIS project. The tool incorporates novel quantitative projection distortion measures which are currently unavailable within existing GIS packages. Parameters are optimized for certain projections to further reduce distortions. A set of candidate projected coordinate systems are generated that can be applied to the GIS project; enabling a qualitative visual assessment to facilitate the final user selection. The proposed tool provides a straightforward application which improves understanding of the projection selection process and assists users in making more effective use of GIS.

Design of and Research on underground pipeline system in campus based on 3DGIS

The underground pipeline of campus is an extremely complex and huge system, and the traditional pipeline management mode can no longer meet the requirements of campus development and planning. The 3D geographic information visualization method can accurately describe the location and distribution information of various pipelines and spatial features, which can better serve the management of underground pipelines on campus. This paper designed overall framework and technology framework of underground pipeline information system, the system is satisfied with the PC, Web, mobile terminal and other multi-client access. In this paper, the key technology points of underground pipeline system construction on campus are comprehensively analyzed, and the feasibility of the technology is verified by combining with the practical application of underground pipeline system in lanzhou university.

MANAGEMENT PROCESSES RECONSTRUCTION OF HISTORICAL BUILDINGS SUPPORTED BY SMART TECHNOLOGY – A CASE STUDY OF FUZHOU CITY

Abstract. This research is based on the projects that Fuzhou has carried out and in developing, regarding to historical building survey, registration, documentation, publication, construction, and daily management business. It integrates smart technologies such as geographic information technology and visualization technology to develop a historical building conservation management database and Fuzhou historical building conservation planning management system. The construction of Fuzhou historical building conservation planning management system, promoted the reconstruction of historical building management processes, achieved efficient and advanced administrative management, achieved scientific and intelligent conservation of historical buildings, and improved the conservation and management of Fuzhou historical buildings in the field of technology level.

Establishment of Geographic Information System on risk assessment regarding infectious diseases imported to China

Objectives: To establish a geographic information application system for analyzing the spatial and temporal distribution of major infectious diseases in various regions of the world and to assess the risk of importation of those diseases, to China. Methods: We collected and integrated the following information on: 1) outbreaks and areas of epidemics of major infectious diseases in the world from 2000 to 2017, 2) cases of infectious diseases in arriving travelers through active surveillance at international entry-exit ports in mainland China from 2014 to 2016, 3) numbers of annual global international flights and travelers in the country. With the above information, a global space-time distribution database on major infectious diseases was then established, using the technology related to the system. Models regarding technologies on time-space analysis, probabilistic risk assessment and geographic information visualization, were applied to establish a geographic information system on risk assessment of infectious diseases that imported to China. Results: Through integration of information on outbreaks and epidemic areas of 60 major infectious diseases in 220 countries and regions around the world, as well as 42 kinds of infectious diseases identified among the international arrivals in mainland China, a system was then developed. Information on the distribution of major infectious diseases and their potential risks in the worldwide various regions, characteristics of spectrum and disease burden of infectious diseases imported to each province of mainland China were displayed. Thus, risks on importing infectious diseases in each province via air way were able to be evaluated and simulated by the probabilistic risk assessment model, under the information on specific kind of infectious disease, outside China. Conclusion: Geographic Information System on Risk Assessment Regarding Infectious Diseases Imported to China provides basic data for epidemiological reconnaissance and assessment on risks of importing infectious diseases outside China, thus would be helpful for the improvement of strategies on surveillance, prevention and control regarding the importing infectious diseases, in China.

From location tracking to personalized eco-feedback: A framework for geographic information collection, processing and visualization to promote sustainable mobility behaviors

Nowadays, most people carry around a powerful smartphone which is well suited to constantly monitor the location and sometimes even the activity of its user. This makes tracking prevalent and leads to a large number of projects concerned with trajectory data. One area of particular interest is transport and mobility, where data is important for urban planning and smart city-related activities, but can also be used to provide individual users with feedback and suggestions for personal behavior change. As part of a large-scale study based in Switzerland, we use activity tracking data to provide people with eco-feedback on their own mobility patterns and stimulate them to adopt more energy-efficient mobility choices. In this paper we explore the opportunities offered by smartphone based activity tracking, propose a general framework to exploit location data to foster more sustainable mobility behavior, describe the technical solutions chosen and discuss a range of outcomes in terms of user perception and sustainability potential. The presented approach extracts mobility patterns from users’ trajectories, computes credible alternative transport options, and presents the results in a concise and clear way. The resulting eco-feedback helps people to understand their mobility choices, discover the most non-ecological parts of their travel behavior, and explore feasible alternatives.

RectMap: A Boundary‐Reserved Map Deformation Approach for Visualizing Geographical Map

Spatial visualization has always been a primary part of information visualization and analysis, especially in the era of big data. The map, the most fundamental components of spatial visualization, is a kind of simple, intuitive and popular way to show the visualization of geographic information. The traditional map is not convenient to overlay complex elements due to its own complex filled color and the actual geographical boundaries. We aim to cut offi dusty foliage of the maps, and deliver the main structure of the map visualization result. We proposes RectMap, a boundary-reserved map deformation approach for visualizing geographical map, which can maintain the mind map of original map. The proposed approach integrate traditional Douglas-Peucker algorithm and our Gridding algorithm. The Douglas-Peucker algorithm generates a simplified map, and the Gridding algorithm optimizes the initial simplified map. Case study and user study are further conducted to demonstrate the effiectiveness and usefulness of the new-style map.

System resilience assessment method of urban lifeline system for GIS

System resilience is defined as the ability of a system to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents. It is a key property to measure the robustness of complex and high coupling degree systems such as urban water supply system, electricity transmission system and waste disposal system. This paper proposes an integrated decision-making process to evaluate system resilience for urban lifeline systems. The decision-making process has two steps: First, the establishment of a system resilience indicator framework that contains five dimensional attributes, namely Materials and Environmental Resources, Society and Well-being, Economy, Built Environment and Infrastructure, and Governance and Institutes. Second, the development of a hybrid K-means algorithm, which combines entropy theory, bootstrapping and analytic network process. Using the real data of is resilient indicators data, this methodology identifies and classifies the resilience level of different regions supported by the lifeline systems. Finally, by combining with geographic information system, the calculation, visualization and classification of resilience leave can be realized. The results can serve as guidelines for governments to allocate resources and prevent large economic loss, especially in those low resilience level areas.