Use Of Geographic Information Research Articles

Значення вивчення географії в умовах війни: перспектива шкільної географічної освіти

The article analyzes the current state of geography education in schools and universities in Ukraine, focusing on the practical aspects of the use of geographic information by society. Rapid changes in the world can lead to the obsolescence of educational materials. The political map of the world can change due to geopolitical events, and data on climate change is also becoming increasingly relevant. Traditional methods of teaching geography may not be interactive enough, which can reduce students' interest and make it difficult for them to learn the material. Particular attention is paid to the role and importance of school geography in wartime, and the possibilities of realizing its importance in crisis situations arising in all spheres of public life are considered. The importance of geography in the process of post-war reconstruction of Ukraine is also considered, emphasizing the need for an integrated approach to its study and use in various aspects of social development.

Geographic-information-based stochastic optimization model for multi-microgrid planning

This paper presents a model for the realistic planning of multi-microgrids in the context of Active Distribution Networks with the assistance of Geographic Information Systems. The model considers the distribution system grid as well as the geographic features of the Region of Interest. It also includes long-term purchase decisions and short-term operational constraints, and considers uncertainties associated with electricity demand and Renewable Energy Resources using an existing Two-Stage Stochastic Programming approach. Geographic Information Systems along with Deep Learning are used to estimate the areas of rooftops within the Region of Interest and model the Low Voltage grid. The planning model is used to study the feasibility of implementing a multi-microgrid system consisting of 4 individual microgrids at an Active Distribution Network in a municipality in the state of São Paulo, Brazil. The results of the model presented in this paper are compared with the results obtained using Monte Carlo Simulations and an existing, less detailed, Two Stage Stochastic model. It is demonstrated that the stochastic solutions are close to those obtained with Monte Carlo at a lower computational cost, and that the use of Geographic Information allows to determine both the capacity and location of the PV panels, batteries, and distribution transformers on the microgrids grid, thus providing more precise and useful planning results.

Volunteered geographic information use in crisis, emergency and disaster management: a scoping review and a web atlas

ABSTRACT Nowadays, an increasing number of crises worldwide, triggered by climate extremes, natural and human-made hazards, the coronavirus pandemic, and more, pose a high pressure on crisis, emergency, and disaster management. Spatial data and Volunteered Geographic Information (VGI) are key issues in the successful and immediate response to crises. This paper aims to explore the use of VGI in crisis management, including emergency and disaster management, based on a scoping review of existing literature in English for five years (2016–2020). Specifically, the research intends to answer Scoping Review Questions (SRQ) regarding the use of VGI in crisis, emergency, and disaster management, and the verified cases’ spatial distribution, the VGI sources utilized (e.g. OpenStreetMap – OSM, Crowdsourcing, Twitter), the types of hazards (e.g. natural and human-made hazards, pandemic), the specific tasks in crisis, emergency or disaster management and VGI use in the management of actual crisis events, e.g. COVID-19 pandemic, Hurricane Katrina, etc. Eligible papers on VGI use in crisis, emergency, and disaster management are geolocated based on first-author affiliation, and as a result, a spatial bibliography is provided. Thus, the term Spatial Scoping Review is introduced. Scoping Review Questions are answered, and the results are analyzed and discussed. Finally, implementing the “VGICED Atlas”, a web atlas, permits the publication of the research results to a broad audience and the visualization of the analysis with several interactive maps.

A Pre-Game Evaluation of the Tourism Legacy Of the Beijing 2022 Winter Olympic Games

The role of tourism in social and economic development and stabilizing the Olympic legacy has been widely discussed. Beijing is the first “Dual-Olympic City”. For the first time, the Beijing Winter Olympics has adopted a model of three competition areas, which has attracted much attention to the study of its tourism legacy. In the legacy plan, the construction of the “Beijing-Zhangjiakou Sports Culture and Tourism Belt” was proposed. The development of ice and snow tourism and the cultivation of the ice and snow tourism market is also reflected in many policy documents and government actions. The scientific planning before the competition laid a good foundation for the sustainable development of its ice and snow tourism heritage. This research combines Olympic legacy research with tourism destination theory, and focuses on ice and snow tourism directly related to the Winter Olympics and the significance of pre-event planning for legacy protection. At the same time, the improvement of the quality of ice and snow tourism destinations is embedded in the pre-Olympic legacy, and opinions and suggestions on how to ensure the stability of the legacy after the games are given. This study uses the literature review method and the second-hand materials survey research method, then through establishing a tourism legacy pre-game evaluation model and the use of geographic information, government reports, policies, publicly released statistics and news reports, etc.. It explores the legacy of the Beijing 2022 Winter Olympics and Paralympics, aiming to lay the foundation for preserving the continuous value of the ice and snow tourism legacy during and after the Olympics. The results indicate that the Beijing Winter Olympics has made relatively complete plans and reliable progress in both tangible and intangible legacy. Complete tourism infrastructure, an optimistic sport and cultural atmosphere, and the improvement of residents' health concept and sports awareness have become boosters for the development of ice and snow tourism in the Beijing-Zhangjiakou region.

A grammar for interpreting geo-analytical questions as concept transformations

Geographic Question Answering (GeoQA) systems can automatically answer questions phrased in natural language. Potentially this may enable data analysts to make use of geographic information without requiring any GIS skills. However, going beyond the retrieval of existing geographic facts on particular places remains a challenge. Current systems usually cannot handle geo-analytical questions that require GIS analysis procedures to arrive at answers. To enable geo-analytical QA, GeoQA systems need to interpret questions in terms of a transformation that can be implemented in a GIS workflow. To this end, we propose a novel approach to question parsing that interprets questions in terms of core concepts of spatial information and their functional roles in context-free grammar. The core concepts help model spatial information in questions independently from implementation formats, and their functional roles indicate how concepts are transformed and used in a workflow. Using our parser, geo-analytical questions can be converted into expressions of concept transformations corresponding to abstract GIS workflows. We developed our approach on a corpus of 309 GIS-related questions and tested it on an independent source of 134 test questions including workflows. The evaluation results show high precision and recall on a gold standard of concept transformations.

Relational POI recommendation model combined with geographic information.

Point of interest (POI) recommendation is a popular personalized location-based service. This paper proposes a Geographic Personal Matrix Factorization (GPMF) model that makes effective use of geographic information from the perspective of the relationship between POIs and users. This model considers the role of geographic information from multiple perspectives based on the locational relationship among users, the distributional relationship between users and POIs, and the proximity and clustering relationship among POIs. The GPMF mines the influence of geographic information on different objects and carries out unique modeling through cosine similarity, non-linear function, and k nearest neighbor (KNN). This study explored the influence of geographic information on POI recommendation through extensive experiments with data from Foursquare. The result shows that GPMF performs better than the commonly used POI recommendation algorithm in terms of both precision and recall. Geographic information through proximity relations effectively improves the recommendation algorithm.

The evolving field of Big Data: understanding geographic information systems analysis and its transformative potential in ophthalmic research.

The purpose of this review to is to highlight alternative uses of Big Data in the pursuit of ophthalmologic public health. In particular, we highlight geographic information systems (GIS) analysis as a type of Big Data, summarize various GIS methods, and enumerate sources of geographic data. The recent implementation of the IRIS Registry Data, has expanded our real-world knowledge of ophthalmology in the United States. Such innovations in Big Data allow us to better define ophthalmic diseases, treatments, and outcomes for underserved individuals and subpopulations. One underutilized source of Big Data entails use of geographic information to evaluate geographic heterogeneity and access across the United States. GIS and Big Data allow for refined epidemiologic estimates of eye disease for specific communities. In particular, how GIS can enable researchers to examine disparities in access to ophthalmic care is reviewed. GIS best practices and some data sources for GIS in ophthalmology are also summarized.

Humanistic GIS: Toward a Research Agenda

The accelerated proliferation of geographic information systems (GIS), especially in the last decade, has greatly expanded the connotation of GIS technology from primarily a diverse suite of digital objects, representations, and devices that create or make use of geographical information to a mediated means with which we humans experience, explore, or make sense of the world. The research perspective of humanistic GIS is proposed to better encompass the expanded category of GIS technology as well as the opportunities and challenges that go with it. Deeply rooted in humanistic geography, humanistic GIS offers a coherent and systematic framework that integrates existing fragmented humanism-related GIS studies and reorients the epistemological foundation by situating GIS in its mediation of human experience. This epistemological configuration not only categorizes GIS through its embodiment, hermeneutic, autonomous, and background relations with the involved human and place but it also provides an analytical structure for examining the intertwined implications of a particular instantiation of GIS. This newly proposed humanistic perspective demonstrates a sincere quest to develop and use GIS in ways that will be more empathetic and better for humanity. Through this article, both the GIS and geography communities are called on to envision a humanistic pathway for the next chapter of GIS.

Survey on economic considerations and decisions of key geodata providers and users in Czech public administration

This paper presents the results of an empirical economic data-based survey of the costs and revenues of geographical data and Web services across public administration in Czechia. The survey was composed of questionnaires and interviews. The data was collected from the 19 biggest public producers of geographical information and 25 organizations that use geographical information. The results focus on the economic consequences of data opening, splitting finances within public administration bodies, the prioritization of activities related to geographical information, licensing issues and life cycle planning etc. We also consider user opinions on the restrictions on the (re)use of geographical information of public administration, including open data.

Size and duration of COVID-19 clusters go along with a high SARS-CoV-2 viral load: A spatio-temporal investigation in Vaud state, Switzerland

To understand the geographical and temporal spread of SARS-CoV-2 during the first documented wave of infection in the state of Vaud, Switzerland, we analyzed clusters of positive cases using the precise residential location of 33,651 individuals tested (RT-PCR) between January 10 and June 30, 2020. We used a prospective Poisson space-time scan statistic (SaTScan) and a Modified Space–Time Density-Based Spatial Clustering of Application with Noise (MST-DBSCAN) to identify both space-time and transmission clusters, and estimated cluster duration, transmission behavior (emergence, growth, reduction, etc.) and relative risk. For each cluster, we computed the number of individuals, the median age of individuals and their viral load.Among the 1684 space-time clusters identified, 457 (27.1%) were significant (p ≤ 0.05), such that they harbored a higher relative risk of infection within the cluster than compared to regions outside the cluster. Clusters lasted a median of 11 days (IQR 7–13) and included a median of 12 individuals per cluster (IQR 5–20). The majority of significant clusters (n = 260; 56.9%) had at least one person with an extremely high viral load (>1 billion copies/ml). Those clusters were considerably larger (median of 17 infected individuals, p < 0.001) than clusters with individuals showing a viral load below 1 million copies/ml (median of three infected individuals). The highest viral loads were found in clusters with the lowest average age group considered in the investigation, while clusters with the highest average age had low to middle viral load. In 20 significant clusters, the viral load of the three first cases was below 100,000 copies/ml, suggesting that subjects with fewer than 100,000 copies/ml may still be contagious. Notably, the dynamics of transmission clusters made it possible to identify three diffusion zones, which predominantly differentiated between rural and urban areas, the latter being more prone to persistence and expansion, which may result in the emergence of new clusters nearby.The use of geographic information is key for public health decision makers in mitigating the spread of the SARS-CoV-2 virus. This study suggests that early localization of clusters may help implement targeted protective measures limiting the spread of the virus.

The Framework Design of the Construction of a Comprehensive Information Management Service Platform at the Township

This article makes full use of geographic information and other industry thematic data, builds a township-level database and informational integrated management service platform, develops mobile APP and multiple characteristic applications, and deeply promotes the guarantee service of geographic information at the township level (sub-district office) and below, helping rural revitalization, building beautiful villages, deepening the promotion and application, and forming a township information service system that integrates government decision-making, department management, and public application, in order to promote grassroots information management, improve grassroots human settlements, scientific planning and construction, strengthen ecological and environmental protection services to provide useful references.

Potentials and barriers of physical development of the Ruodbar city using Remote Sensing and GIS

Background and Objective: Physical development of cities around the world is influenced by its natural geography and human interactions. Geographic data analysis is difficult without the use of geographic information and satellite data, and impossible in a complex case. In this study, potentials and barriers of physical development of the Ruodbar city using Remote Sensing and GIS be evaluated. Method: Firstly, in the ArcGIS software environment, using the AHP-FUZZY combination method the use of slope, gradient, land use, power lines, river, road and rail, fault and rural points are used to locate the urban sprawl. The output was extracted in the form of a map of AHP and fuzzy overlay into five groups with very good, good, moderate, weak and very weak potential. In order to expand the city's physical development by using a visual interpretation on Google Earth images for 2016, 2009, 2004 for 12 years, a map was drawn out as the result. Finally, the results obtained from the Geographic Information and Visual Interpretation System were compared. Findings: The findings of the AHP-FUZZY compilation show that 95.6% of the study area has very weak potential, 1. 52% has a weak potential, 1.17% has a moderate potential, 1.21% has good potential and 0.69% has a very good potential. And the findings from the visual interpretation method over the course of 12 years show that the development of the city is just Mehr Housing (a project done government). Discussion and Conclusion: Based on the findings of the AHP-FUZZY Compilation and Metrology Measurement, we concluded that most of the constructions have been implemented in unpredictable places in the city of Roodbar, which is influenced by natural and inevitable factors, including steep slope, abundant faults, permanent existence of Sefidrood river, and land use, most of which are gardens and forests and agricultural land and has prevented its physical development.

Generative Pedestrian Trajectory Prediction with Graph Representation

Multi-agent trajectory prediction is one of the core modules of unmanned driving and intelligent robots. The traditional method is difficult to measure the relationship between multiple agents, and the modeling ability is rigid. Nowadays, most of the methods make less use of geographic information, and social relationship modeling is not sufficient. Our model uses Graph Neural Network (GNN) to measure social relationships to improve its usability. The model is built by the basic Conditional Auto-encoder (CVAE) framework, using Gaussian Mixture Model to mix multiple Gaussian distributions and the possibility of obtaining more potential space through dynamic integration to make the model achieve better results. Our model has achieved excellent results on the Stanford Drone Dataset. The evaluation by average displacement error (ADE) and final displacement error (FDE) metrics has exceeded the majority of existing models.

A geographical hierarchy greedy routing strategy for vehicular big data communications over millimeter wave

As the autonomous and intelligent driving technologies rapidly develop, vehicles are equipped with more sensors and produce more data. To cope with the challenge of big data, millimeter wave (mmWave) can achieve data rates of up to multiple gigabits per second. Though mmWave communications can provide wide bandwidths, mmWave is susceptible to blockage due to its poor diffraction capability and its high penetration loss. To overcome the limited communication range for vehicular applications in wide areas, a routing strategy is required to relay data in a multi-hop way. In this work, we propose a geographical hierarchy greedy routing algorithm for inter-vehicle mmWave communications. Also, we evaluate the channel characteristics and the throughput performance of mmWave working at 60 GHz. The proposed routing strategy makes use of geographical information for relay determination while maintaining the high throughput and ensuring the channel stability of mmWave. Based on the simulation results, it is found that mmWave is promising for the future big data vehicular applications.

Faster and Better Nested Dissection Orders for Customizable Contraction Hierarchies

Graph partitioning has many applications. We consider the acceleration of shortest path queries in road networks using Customizable Contraction Hierarchies (CCH). It is based on computing a nested dissection order by recursively dividing the road network into parts. Recently, with FlowCutter and Inertial Flow, two flow-based graph bipartitioning algorithms have been proposed for road networks. While FlowCutter achieves high-quality results and thus fast query times, it is rather slow. Inertial Flow is particularly fast due to the use of geographical information while still achieving decent query times. We combine the techniques of both algorithms to achieve more than six times faster preprocessing times than FlowCutter and even faster queries on the Europe road network. We show that, using 16 cores of a shared-memory machine, this preprocessing needs four minutes.

Geographic Information Metadata—An Outlook from the International Standardization Perspective

Geographic information metadata provides a detailed description of geographic information resources. Well before digital data emerged, metadata were shown in the margins of paper maps to inform the reader of the name of the map, the scale, the orientation of the magnetic North, the projection used, the coordinate systems, the legend, and so on. Metadata were used to communicate practical information for the proper use of maps. When geographic information entered the digital era with geographic information systems, metadata was also collected digitally to describe datasets and the dataset collections for various purposes. Initially, metadata were collected and saved in digital files by data producers for their own specific needs. The sharing of geographic datasets that required producers to provide metadata with the dataset to guide proper use of the dataset—map scale, data sources, extent, datum, coordinate reference system, etc. Because of issues with sharing and no common understanding of metadata requirements, the need for metadata standardization was recognized by the geographic information community worldwide. The ISO technical committee 211 was created in 1994 with the scope of standardization in the field of digital geographic information to support interoperability. In the early years of the committee, standardization of metadata was initiated for different purposes, which culminated in the ISO 19115:2003 standard. Now, there are many ISO Geographic information standards that covers the various aspect of geographic information metadata. This paper traces an illustration of the development and evolution of the requirements and international standardization activities of geographic information metadata standards, profiles and resources, and how these attest to facilitating the discovery, evaluation, and appropriate use of geographic information in various contexts.

Floyd-warshall algorithm to determine the shortest path based on android

The development of technology has made all areas of life easier now, one of which is the ease of obtaining geographic information. The use of geographic information may vary according to need, for example, the digital map learning, navigation systems, observations area, and much more. With the support of adequate infrastructure, almost no one will ever get lost to a destination even to foreign places or that have never been visited before. The reasons why many institutions and business entities use technology to improve services to consumers and to streamline the production process undertaken and so forth. Speaking of the efficient, there are many elements related to efficiency in navigation systems, and one of them is the efficiency in terms of distance. The shortest distance determination algorithm required in this research is used Floyd-Warshall Algorithm. Floyd-Warshall algorithm is the algorithm to find the fastest path and the shortest distance between 2 nodes, while the program is intended to find the path of more than 2 nodes.

The Impact of Geographic Location on the Subjective Assessment of System Usability

ABSTRACTMarketing researchers use geography to identify specific user groups for studies to more effectively describe their potential customer base. Since usability professionals often recruit users employing similar selection criteria as their marketing peers, the use of geographic information might also be relevant when selecting usability test participants. In total, 3,168 participants from across the United States rated the usability of different hardware, software, and web-based products using the System Usability Scale (SUS). SUS scores were compared across geographic divisions to determine if usability assessments differ by location. SUS scores were also compared across rural and urban areas to determine if usability assessment scores change with population density. There was a lack of evidence to support significant differences in usability scores across both US geographic areas and zones of population density. The findings suggest that people make similar system usability assessments regardless of the area of the United States in which they live.

Opportunities provided by geographic information systems and volunteered geographic information for a timely emergency response during flood events in Cologne, Germany

The occurrence of disasters such as extreme flooding in urban environments has severe consequences, not only on the human population but also on critical infrastructures such as the road networks, which are of vital importance for everyday living and particularly for emergency response. In this article, our main goal is to present-conceptually and in praxis-a model that could be used from the emergency responders for timely and efficient emergency management and response in an urban complex environment. For the city of Cologne in Germany, we aim to indicate possible ways to decrease the emergency response time during an extreme flood scenario through the development of an accessibility indicator, which consists of different components. Therefore, we will investigate the opportunities that occur, in a flood risk scenario, from the use of geographic information in different forms such as Volunteered Geographic Information (VGI) and open-source data in an ArcGIS environment, to increase urban resilience through the decreasing emergency response time. We will focus on network analysis for the fire brigades (first acting emergency responders) during a flood scenario to calculate their emergency response ranges and emergency response routes through flooded road networks, for the assistance of the possibly affected hospitals, refugee homes and fire brigades, which can be flooded. At the end of the paper, we suggest that the vulnerable community of the refugees could be taken into consideration as a new source of VGI, as an additional component that would lead to the decrease in the emergency response time. The geo-located information that could be provided by the refugee community can be very useful in emergency situations, such as those examined in this article where timely information can be forwarded to the proper authorities for a more focused and timely emergency response, increasing the resilience of the urban population and their community.

Employing Search Engine Optimization (SEO) Techniques for Improving the Discovery of Geospatial Resources on the Web

With the increasing use of geographical information and technology in a variety of knowledge domains and disciplines, the need to discover and access suitable geospatial data is imperative. Most spatial data infrastructures (SDI) provide geoportals as entry points to the SDI through which geospatial data are disseminated and shared. Geoportals are often known in geoinformation communities only, and they present technological challenges for indexing by web search engines. To overcome these challenges, we identified and categorized search terms typically employed by users when looking for geospatial resources on the Web. Guided by these terms, we published metadata about geospatial sources “directly” on the Web and performed empirical tests with search engine optimization (SEO) techniques. Two sets of HTML pages were prepared and registered with Google and Bing respectively. The metadata in one set was marked up with Dublin Core, the other with Schema.org. Analysis of the results shows that Google was more effective than Bing in retrieving the pages. Pages marked up with Schema.org were more effectively retrieved than those marked up with Dublin Core. The statistical results were significant in most of the tests performed. This research confirms that pages marked up with Schema.org and Dublin Core are a novel alternative for improving the visibility and facilitating the discovery of geospatial resources on the Web.