Статті в журналах: "090903 Geospatial Information Systems"

1

Meeks, W. Lee, and Subhasish Dasgupta. "Geospatial information utility: an estimation of the relevance of geospatial information to users." Decision Support Systems 38, no. 1 (October 2004): 47–63. http://dx.doi.org/10.1016/s0167-9236(03)00076-9.

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2

POKORSKI, Grzegorz, and płk w. st spocz prof dr hab inż PIOTR ZASKÓRSKI. "Geospatial information systems in business process management." Nowoczesne Systemy Zarządzania 13, no. 2 (June 28, 2018): 107–27. http://dx.doi.org/10.37055/nsz/129514.

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Systemy Informacji Geoprzestrzennej (GIS), zazwyczaj kojarzone z zastosowaniami kartograficznymi, rozszerzają swój zakres wykorzystania. Internet Rzeczy w połączeniu z formułą otwartych danych zwiększa powszechność i dostępność danych geograficznych. Możliwe więc staje się zwiększenie zakresu zasobów informacyjnych utrzymywanych dotychczas w postaci znakowej. Narzędzia GIS wzbogacają funkcjonalność rozwiązań informatycznych w obszarze zarządzania poprzez coraz szersze wykorzystanie zarówno analiz geoprzestrzennych, jak również własności samych systemów GIS. Artykuł jest próbą pokazania możliwości wykorzystania wymiaru geograficznego dla potrzeb analiz biznesowych.

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3

Sboui, Tarek, Mehrdad Salehi, and Yvan Bédard. "A Systematic Approach for Managing the Risk Related to Semantic Interoperability between Geospatial Datacubes." International Journal of Agricultural and Environmental Information Systems 1, no. 2 (July 2010): 20–41. http://dx.doi.org/10.4018/jaeis.2010070102.

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Geospatial datacubes are the database backend of novel types of spatiotemporal decision-support systems employed in large organizations. These datacubes extend the datacube concept underlying the field of Business Intelligence (BI) into the realm of geospatial decision-support and geographic knowledge discovery. The interoperability between geospatial datacubes facilitates the reuse of their content. Such interoperability, however, faces risks of data misinterpretation related to the heterogeneity of geospatial datacubes. Although the interoperability of transactional databases has been the subject of several research works, no research dealing with the interoperability of geospatial datacubes exists. In this paper, the authors support the semantic interoperability between geospatial datacubes and propose a categorization of semantic heterogeneity problems that may occur in geospatial datacubes. Additionally, the authors propose an approach to deal with the related risks of data misinterpretation, which consists of evaluating the fitness-for-use of datacubes models, and a general framework that facilitates making appropriate decisions about such risks. The framework is based on a hierarchical top-down structure going from the most general level to the most detailed level, showing the usefulness of the proposed approach in environmental applications.

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4

Jung, Hyung-Sup, Saro Lee, and Biswajeet Pradhan. "Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations." Sustainability 12, no. 6 (March 19, 2020): 2390. http://dx.doi.org/10.3390/su12062390.

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The Special Issue on “Sustainable Applications of Remote Sensing and Geospatial Information Systems to Earth Observations” is published. A total of 20 qualified papers are published in this Special Issue. The topics of the papers are the application of remote sensing and geospatial information systems to Earth observations in various fields such as (1) object change detection, (2) air pollution, (3) earthquakes, (4) landslides, (5) mining, (6) biomass, (7) groundwater, and (8) urban development using the techniques of remote sensing and geospatial information systems. More than 100 researchers have participated in this Special Issue. We hope that this Special Issue is helpful for sustainable applications.

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5

Mohan, M. "GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 979–85. http://dx.doi.org/10.5194/isprs-archives-xli-b8-979-2016.

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In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

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6

Mohan, M. "GEOSPATIAL INFORMATION FROM SATELLITE IMAGERY FOR GEOVISUALISATION OF SMART CITIES IN INDIA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B8 (June 24, 2016): 979–85. http://dx.doi.org/10.5194/isprsarchives-xli-b8-979-2016.

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Анотація:

In the recent past, there have been large emphasis on extraction of geospatial information from satellite imagery. The Geospatial information are being processed through geospatial technologies which are playing important roles in developing of smart cities, particularly in developing countries of the world like India. The study is based on the latest geospatial satellite imagery available for the multi-date, multi-stage, multi-sensor, and multi-resolution. In addition to this, the latest geospatial technologies have been used for digital image processing of remote sensing satellite imagery and the latest geographic information systems as 3-D GeoVisualisation, geospatial digital mapping and geospatial analysis for developing of smart cities in India. The Geospatial information obtained from RS and GPS systems have complex structure involving space, time and presentation. Such information helps in 3-Dimensional digital modelling for smart cities which involves of spatial and non-spatial information integration for geographic visualisation of smart cites in context to the real world. In other words, the geospatial database provides platform for the information visualisation which is also known as geovisualisation. So, as a result there have been an increasing research interest which are being directed to geospatial analysis, digital mapping, geovisualisation, monitoring and developing of smart cities using geospatial technologies. However, the present research has made an attempt for development of cities in real world scenario particulary to help local, regional and state level planners and policy makers to better understand and address issues attributed to cities using the geospatial information from satellite imagery for geovisualisation of Smart Cities in emerging and developing country, India.

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7

PAUL, MANOJ, and S. K. GHOSH. "A SERVICE-ORIENTED APPROACH FOR INTEGRATING HETEROGENEOUS SPATIAL DATA SOURCES REALIZATION OF A VIRTUAL GEO-DATA REPOSITORY." International Journal of Cooperative Information Systems 17, no. 01 (March 2008): 111–53. http://dx.doi.org/10.1142/s0218843008001774.

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Searching and accessing geospatial information in the open and distributed environments of geospatial information systems poses several challenges due to the heterogeneity in geospatial data. Geospatial data is highly heterogeneous — both at the syntactic and semantic level. The requirement for an integration architecture for seamless access of geospatial data has been raised over the past decades. The paper proposes a service-based model for geospatial integration where each geospatial data provider is interfaced on the web as services. The interface for these services has been described with Open Geospatial Consortium (OGC) specified service standards. Catalog service provides service descriptions for the services to be discovered. The semantic of each service description is captured in the form of ontology. The similarity assessment method of request service with candidate services proposed in this paper is aimed at resolving the heterogeneity in semantics of locational terms of service descriptions. In a way, we have proposed an architecture for enterprise geographic information system (E-GIS), which is an organization-wide approach to GIS integration, operation, and management. A query processing mechanism for accessing geospatial information in the service-based distributed environment has also been discussed with the help of a case study.

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8

Göbel, Stefan, and Uwe Jasnoch. "Visualization techniques in metadata information systems for geospatial data." Advances in Environmental Research 5, no. 4 (November 2001): 415–24. http://dx.doi.org/10.1016/s1093-0191(01)00093-4.

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9

Pierce, Marlon E. "Special Issue Editorial Introduction: Grids and Geospatial Information Systems." Concurrency and Computation: Practice and Experience 20, no. 14 (September 25, 2008): 1611–15. http://dx.doi.org/10.1002/cpe.1381.

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10

Sa’ad Alhefafi, Abdullah, and Adnan Yahya Almutawakle. "A Review on Geospatial Information Systems in Cloud Computing." International Journal of Computer Science and Mobile Computing 11, no. 11 (November 30, 2022): 205–8. http://dx.doi.org/10.47760/ijcsmc.2022.v11i11.017.

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Cloud computing technology is one of the most important technology in information systems (IS) today. It is an important alternative that ensures powerful data processing, storage and exchange. And as a result of the emergence of multiple sources of spatial data and their tremendous growth and the expansion of areas of use of Geospatial Information Systems (GIS), it became necessary to integrate these tow technologies to achieve the optimum benefit of these technologies to make Geospatial Information Systems capable of accommodating the large, rapid, and diverse amounts of spatial data available nowadays. Cloud computing is a new paradigm in Geographic Information Systems. Although there are many publications related to cloud computing in Geographic Information System, there is no systematic review of current research taxonomies .The purpose of this paper is to conduct a survey on GIS Cloud Computing. It addresses the different GIS Cloud frameworks or architectures. The search for articles carried out in general academic databases including the Scopus database, Web of Science Core Collection, and Google Scholar Citations. Retried articles are analysed according to inclusion and exclusion criteria, finally articles selected for review.

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11

Kussul, Nataliya N., Boris V. Sokolov, Yarema I. Zyelyk, Vyacheslav A. Zelentsov, Sergey V. Skakun, and Andrey Yu Shelestov. "Disaster Risk Assessment Based on Heterogeneous Geospatial Information." Journal of Automation and Information Sciences 42, no. 12 (2010): 32–45. http://dx.doi.org/10.1615/jautomatinfscien.v42.i12.40.

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12

Zhang, Ying, Chaopeng Li, Na Chen, Shaowen Liu, Liming Du, Zhuxiao Wang, and Miaomiao Ma. "Semantic Web and Geospatial Unique Features Based Geospatial Data Integration." International Journal on Semantic Web and Information Systems 12, no. 1 (January 2016): 1–22. http://dx.doi.org/10.4018/ijswis.2016010101.

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Since large amount of geospatial data are produced by various sources and stored in incompatible formats, geospatial data integration is difficult because of the shortage of semantics. Despite standardised data format and data access protocols, such as Web Feature Service (WFS), can enable end-users with access to heterogeneous data stored in different formats from various sources, it is still time-consuming and ineffective due to the lack of semantics. To solve this problem, a prototype to implement the geospatial data integration is proposed by addressing the following four problems, i.e., geospatial data retrieving, modeling, linking and integrating. First, we provide a uniform integration paradigm for users to retrieve geospatial data. Then, we align the retrieved geospatial data in the modeling process to eliminate heterogeneity with the help of Karma. Our main contribution focuses on addressing the third problem. Previous work has been done by defining a set of semantic rules for performing the linking process. However, the geospatial data has some specific geospatial relationships, which is significant for linking but cannot be solved by the Semantic Web techniques directly. We take advantage of such unique features about geospatial data to implement the linking process. In addition, the previous work will meet a complicated problem when the geospatial data sources are in different languages. In contrast, our proposed linking algorithms are endowed with translation function, which can save the translating cost among all the geospatial sources with different languages. Finally, the geospatial data is integrated by eliminating data redundancy and combining the complementary properties from the linked records. We mainly adopt four kinds of geospatial data sources, namely, OpenStreetMap(OSM), Wikmapia, USGS and EPA, to evaluate the performance of the proposed approach. The experimental results illustrate that the proposed linking method can get high performance in generating the matched candidate record pairs in terms of Reduction Ratio(RR), Pairs Completeness(PC), Pairs Quality(PQ) and F-score. The integrating results denote that each data source can get much Complementary Completeness(CC) and Increased Completeness(IC).

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13

Hammitzsch, Martin, and Matthias Lendholt. "Evolving an information logistics database for geospatial early warning systems." Geomatics, Natural Hazards and Risk 2, no. 2 (June 2011): 95–109. http://dx.doi.org/10.1080/19475705.2011.563448.

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14

Vinaja, Robert. "Geospatial infrastructure, applications and technologies: india case studies." Journal of Global Information Technology Management 22, no. 1 (January 2, 2019): 75–76. http://dx.doi.org/10.1080/1097198x.2019.1567659.

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15

Homburg, Timo. "Connecting Semantic Situation Descriptions with Data Quality Evaluations—Towards a Framework of Automatic Thematic Map Evaluation." Information 11, no. 11 (November 15, 2020): 532. http://dx.doi.org/10.3390/info11110532.

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A continuing question in the geospatial community is the evaluation of fitness for use of map data for a variety of use cases. While data quality metrics and dimensions have been discussed broadly in the geospatial community and have been modelled in semantic web vocabularies, an ontological connection between use cases and data quality expressions allowing reasoning approaches to determine the fitness for use of semantic web map data has not yet been approached. This publication introduces such an ontological model to represent and link situations with geospatial data quality metrics to evaluate thematic map contents. The ontology model constitutes the data storage element of a framework for use case based data quality assurance, which creates suggestions for data quality evaluations which are verified and improved upon by end-users. So-created requirement profiles are associated and shared to semantic web concepts and therefore contribute to a pool of linked data describing situation-based data quality assessments, which may be used by a variety of applications. The framework is tested using two test scenarios which are evaluated and discussed in a wider context.

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16

Müller, H. "BRIDGING THE GAP BETWEEN SURVEYORS AND THE GEO-SPATIAL SOCIETY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 683–86. http://dx.doi.org/10.5194/isprs-archives-xli-b4-683-2016.

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For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

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17

Müller, H. "BRIDGING THE GAP BETWEEN SURVEYORS AND THE GEO-SPATIAL SOCIETY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLI-B4 (June 14, 2016): 683–86. http://dx.doi.org/10.5194/isprsarchives-xli-b4-683-2016.

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For many years FIG, the International Association of Surveyors, has been trying to bridge the gap between surveyors and the geospatial society as a whole, with the geospatial industries in particular. Traditionally the surveying profession contributed to the good of society by creating and maintaining highly precise and accurate geospatial data bases, based on an in-depth knowledge of spatial reference frameworks. Furthermore in many countries surveyors may be entitled to make decisions about land divisions and boundaries. By managing information spatially surveyors today develop into the role of geo-data managers, the longer the more. Job assignments in this context include data entry management, data and process quality management, design of formal and informal systems, information management, consultancy, land management, all that in close cooperation with many different stakeholders. Future tasks will include the integration of geospatial information into e-government and e-commerce systems. The list of professional tasks underpins the capabilities of surveyors to contribute to a high quality geospatial data and information management. In that way modern surveyors support the needs of a geo-spatial society. The paper discusses several approaches to define the role of the surveyor within the modern geospatial society.

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18

Zhang, Ying, Puhai Yang, Chaopeng Li, Gengrui Zhang, Cheng Wang, Hui He, Xiang Hu, and Zhitao Guan. "A Multi-Feature Based Automatic Approach to Geospatial Record Linking." International Journal on Semantic Web and Information Systems 14, no. 4 (October 2018): 73–91. http://dx.doi.org/10.4018/ijswis.2018100104.

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This article describes how geographic information systems (GISs) can enable, enrich and enhance geospatial applications and services. Accurate calculation of the similarity among geospatial entities that belong to different data sources is of great importance for geospatial data linking. At present, most research works use the name or category of the entity to measure the similarity of geographic information. Although the geospatial relationship is significant for geographic similarity measure, it has been ignored by most of the previous works. This article introduces the geospatial relationship and topology, and proposes an approach to compute the geospatial record similarity based on multiple features including the geospatial relationships, category and name tags. In order to improve the flexibility and operability, supervised machine learning such as SVM is used for the task of classifying pairs of mapping records. The authors test their approach using three sources, namely, OpenStreetMap, Google and Wikimapia. The results showed that the proposed approach obtained high correlation with the human judgements.

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19

Elliott, Rory. "Geographic information systems (GIS) and libraries: concepts, services and resources." Library Hi Tech News 31, no. 8 (September 30, 2014): 8–11. http://dx.doi.org/10.1108/lhtn-07-2014-0054.

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Purpose – This paper aims to provide an introduction to core geographic information systems (GIS) concepts, prominent GIS software, the role of libraries in providing GIS services and support and resources for professional library staff to increase GIS knowledge and skills to fulfill the mission of serving the information needs of library patrons. Design/methodology/approach – This paper provides an overview of GISs core concepts and terminologies, Library GIS services and resources for library staff development. Findings – As GISs are being used by researchers in an ever-growing number of disciplines, librarians must increase their proficiency with geospatial technologies. Originality/value – While GISs have been used by certain researcher populations for some time, the increased use of such geospatial technologies creates a need for librarians who possess the skills and knowledge to assist patrons with their GIS needs. This paper introduces professional library staff to important GIS concepts, potential GIS services and resources to increase library staff’s competence with GISs.

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20

Sufi, Fahim, and Musleh Alsulami. "A Novel Method of Generating Geospatial Intelligence from Social Media Posts of Political Leaders." Information 13, no. 3 (February 28, 2022): 120. http://dx.doi.org/10.3390/info13030120.

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Social media platforms such as Twitter have been used by political leaders, heads of states, political parties, and their supporters to strategically influence public opinions. Leaders can post about a location, a state, a country, or even a region in their social media accounts, and the posts can immediately be viewed and reacted to by millions of their followers. The effect of social media posts by political leaders could be automatically measured by extracting, analyzing, and producing real-time geospatial intelligence for social scientists and researchers. This paper proposed a novel approach in automatically processing real-time social media messages of political leaders with artificial intelligence (AI)-based language detection, translation, sentiment analysis, and named entity recognition (NER). This method automatically generates geospatial and location intelligence on both ESRI ArcGIS Maps and Microsoft Bing Maps. The proposed system was deployed from 1 January 2020 to 6 February 2022 to analyze 1.5 million tweets. During this 25-month period, 95K locations were successfully identified and mapped using data of 271,885 Twitter handles. With an overall 90% precision, recall, and F1score, along with 97% accuracy, the proposed system reports the most accurate system to produce geospatial intelligence directly from live Twitter feeds of political leaders with AI.

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21

Murthy, M. S. R., B. Bajracharya, S. Pradhan, B. Shestra, R. Bajracharya, K. Shakya, S. Wesselmann, M. Ali, S. Bajracharya, and S. Pradhan. "Adoption of Geospatial Systems towards evolving Sustainable Himalayan Mountain Development." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-8 (November 28, 2014): 1319–24. http://dx.doi.org/10.5194/isprsarchives-xl-8-1319-2014.

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Natural resources dependence of mountain communities, rapid social and developmental changes, disaster proneness and climate change are conceived as the critical factors regulating sustainable Himalayan mountain development. The Himalayan region posed by typical geographic settings, diverse physical and cultural diversity present a formidable challenge to collect and manage data, information and understands varied socio-ecological settings. Recent advances in earth observation, near real-time data, in-situ measurements and in combination of information and communication technology have transformed the way we collect, process, and generate information and how we use such information for societal benefits. Glacier dynamics, land cover changes, disaster risk reduction systems, food security and ecosystem conservation are a few thematic areas where geospatial information and knowledge have significantly contributed to informed decision making systems over the region. The emergence and adoption of near-real time systems, unmanned aerial vehicles (UAV), board-scale citizen science (crowd-sourcing), mobile services and mapping, and cloud computing have paved the way towards developing automated environmental monitoring systems, enhanced scientific understanding of geophysical and biophysical processes, coupled management of socio-ecological systems and community based adaptation models tailored to mountain specific environment. There are differentiated capacities among the ICIMOD regional member countries with regard to utilization of earth observation and geospatial technologies. The region can greatly benefit from a coordinated and collaborative approach to capture the opportunities offered by earth observation and geospatial technologies. The regional level data sharing, knowledge exchange, and Himalayan GEO supporting geospatial platforms, spatial data infrastructure, unique region specific satellite systems to address trans-boundary challenges would go a long way in evolving sustainable Himalayan livelihoods.

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22

Brumana, Raffaella, Daniela Oreni, Branka Cuca, Anna Rampini, and Monica Pepe. "Open Access to Historical Information for Landscape Analysis in an SDI Framework." International Journal of Agricultural and Environmental Information Systems 4, no. 3 (July 2013): 18–40. http://dx.doi.org/10.4018/ijaeis.2013070102.

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The paper illustrates the potentials of geospatial data to access a historical digital atlas for landscape analysis and territorial government. The experience of a historical geo-portal, the “Atl@nte dei Catasti Storici,” in the management of geo-referenced and non-geo-referenced maps—ancient cadastral and topographic maps of the Lombardy Region—can be considered a case study with common aspects to many European regions with an extensive cartographic heritage. The development of downstream Web-based services enables integration with other data sources (current maps, satellite and Unmanned Aerial Vehicle [UAV] airborne photogrammetry, and multi-spectral images and derived products). This provides new scenarios for retrieving geospatial knowledge in support of more sustainable management and governance of the territory.

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Rigolon, Alessandro, and Jeremy Németh. "A QUality INdex of Parks for Youth (QUINPY): Evaluating urban parks through geographic information systems." Environment and Planning B: Urban Analytics and City Science 45, no. 2 (October 4, 2016): 275–94. http://dx.doi.org/10.1177/0265813516672212.

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Visiting urban parks regularly can provide significant physical and mental health benefits for children and teenagers, but these benefits are tempered by park quality, amenities, maintenance, and safety. Therefore, planning and public health scholars have developed instruments to measure park quality, but most of these tools require costly and time-consuming field surveys and only a handful focus specifically on youth. We rectify these issues by developing the QUality INdex of Parks for Youth (QUINPY) based on a robust literature review of studies on young people’s park visitation habits and an extensive validation process by academic and professional experts. Importantly, the QUINPY relies on publicly available geospatial data to measure park quality. We then successfully pilot test the QUINPY in Denver and New York City. We believe that park agencies, planning consultants, researchers, and nonprofits aiming to assess park quality will find this tool useful. The QUINPY is particularly promising given the increasing amount of publicly available geospatial data and other recent advancements in geospatial science.

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24

Sikder, Iftikhar U., and Santosh K. Misra. "Semantic Interoperability of Geospatial Services." International Journal of Intelligent Information Technologies 4, no. 1 (January 2008): 31–51. http://dx.doi.org/10.4018/jiit.2008010102.

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25

Davies, Benjamin, Iza Romanowska, Kathryn Harris, and Stefani A. Crabtree. "Combining Geographic Information Systems and Agent-Based Models in Archaeology: Part 2 of 3." Advances in Archaeological Practice 7, no. 2 (May 2019): 185–93. http://dx.doi.org/10.1017/aap.2019.5.

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ABSTRACTArchaeologists are using spatial data in increasingly sophisticated analyses and invoking more explicit considerations of space in their interpretations. Geographic information systems (GIS) have become standard technology for professional archaeologists in the collection and management of spatial data. Many calls have been made to develop and adapt digital geospatial technologies for interpretation and understanding past social dynamics, but this has been limited to some extent by the static nature of map-oriented GIS approaches. Here, we illustrate how coupling GIS with agent-based modeling (ABM) can assist with more dynamic explorations of past uses of space and geospatial phenomena.

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26

Robinson, Anthony. "Interacting with geospatial technologies." International Journal of Geographical Information Science 25, no. 2 (March 2011): 328–29. http://dx.doi.org/10.1080/13658816.2010.511623.

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Yudina, L., N. Levinskova, and R. Pysarenko. "Forecasting in geographic information systems to solve problems of geospatial support in the interests of the Armed Forces of Ukraine." Visnyk Taras Shevchenko National University of Kyiv. Military-Special Sciences, no. 2(50) (2022): 114–19. http://dx.doi.org/10.17721/1728-2217.2022.50.114-119.

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It should be noted that the role of the topographic and geoinformation component in the combat support of the operational group of troops, which is created in the context of hostilities, has recently increased significantly. The use of analytical and forecasting geoinformation models to solve problems of geospatial (topographic) support of troops, to replace analytical and forecasting activities based only on their own experience and limited information – improves the quality of tasks; allows you to simplify and increase the speed of tasks; automatically obtain reliable geospatial information while supporting decision-making with minimal time. Geographic information systems based on modern computer technologies allow to combine images of the territory (electronic display of maps, diagrams, space, aerial images of the earth's surface) with information of tabular type (various types of data) in the form of analytical and forecasting model of geoprocessing. Ability to develop additional geoinformation models (geoprocessing models) to solve various "custom" tasks – this allows them to be used in analytical and forecasting activities to perform geospatial support tasks in the preparation and conduct of hostilities. In the future, the trend of using analytical and forecasting geoinformation models to solve the problems of geospatial support of troops in hostilities will only grow. This is due to the development of information technology; increasing exponentially the amount of information that commanders (staffs) process when planning or making decisions; using the data of unmanned aerial vehicles, increasing the requirements for efficiency and quality of geospatial support of hostilities; increasing the geoinformation aspect in the topographic and navigational and navigation support of the Armed Forces of Ukraine.

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Hadi, Muhammad Sapoan, Sutanto Priyo Hastono, Kemal Nazarudin Siregar, and Dumilah Ayuningtyas. "Geospatial-Based Information Systems Model for Disaster Management of Reproductive Health." Media Kesehatan Masyarakat Indonesia 16, no. 1 (March 31, 2020): 62. http://dx.doi.org/10.30597/mkmi.v16i1.8780.

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Indonesia is a disaster-prone area, but it is often found that the response process is slow at the very beginning of a disaster. Furthermore, disasters are often unpredictable. Therefore, simulation of preparedness, mitigation, and disaster management should be conducted continuously and systematically, both in manual and electronic manner by utilizing advance technology in geospatial. The aim of this study to develop a model of geospatial-based information systems in disaster management of reproductive health sub-cluster (SIGAB KESPRO BISA) in Nusa Tenggara Barat. Data collection was conducted through in-depth interviews with several stakeholders. To complete the methodological approach and to obtain the system requirement, a content analysis was done toward in-depth interviews result. The research continued with the development of information system models. The analysis results by in-depth interview indicate the availability of infrastructure and the importance of the system offered. The SIGAB KESPRO BISA model needs to be composed of three main functions, namely preparedness and mitigation systems, logistics distribution, and reproductive health services. The design of the SIGAB KESPRO BISA model has been built to facilitate the process of developing the SIGAB KESPRO BISA application system so that disaster management can be carried out with high effectiveness and efficiency.

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Kolomiets, E. A., and V. N. Nikolaev. "AUTOMATED PROCESSING AND THE FORMATION OF GEOSPATIAL INFORMATION IN SOCIAL SYSTEMS." Proceedings of the Southwest State University 22, no. 5 (February 26, 2019): 82–95. http://dx.doi.org/10.21869/2223-1560-2018-22-5-82-95.

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30

Enescu, Ionuţ Iosifescu, Vassilios Vescoukis, Cristina M. Iosifescu Enescu, Fabian Müller, Nadia H. Panchaud, and Lorenz Hurni. "Hypercube-Based Visualization Architecture for Web-Based Environmental Geospatial Information Systems." Cartographic Journal 52, no. 2 (April 3, 2015): 137–48. http://dx.doi.org/10.1080/00087041.2015.1119469.

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31

Wimmerova, Sona, Tomas Trnovec, Beata Drobna, Henrieta Patayova, Eva Sovcikova, and Daniel Michniak. "Geospatial information systems analysis of regional environmental change in Eastern Slovakia." Toxicology Letters 180 (October 2008): S206. http://dx.doi.org/10.1016/j.toxlet.2008.06.247.

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Helmi, Abdelrahman M., Marwa S. Farhan, and Mona M. Nasr. "A framework for integrating geospatial information systems and hybrid cloud computing." Computers & Electrical Engineering 67 (April 2018): 145–58. http://dx.doi.org/10.1016/j.compeleceng.2018.03.027.

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Yambaev, Kharyes K. "DIGITAL DEFORMATION MONITORING TECHNOLOGIES - THE MOST IMPORTANT COMPONENT OF GEOSPATIAL ACTIVITIES (INDUSTRY)." Interexpo GEO-Siberia 1 (May 21, 2021): 20–24. http://dx.doi.org/10.33764/2618-981x-2021-1-20-24.

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Within the framework of the program for creation of a geospatial industry it is offered to form a competent state body - the Main Directorate of the Geospatial Industry under the Government of the Russian Federation. The key aspect of the program is digital production - a multi-level system that includes automated measuring systems in the process of deformation monitoring, means of transferring the received information and their visualization, powerful analytical tools for interpreting the received geospatial information and many other related components.

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34

Li, Linna, and Michael F. Goodchild. "The Role of Social Networks in Emergency Management." International Journal of Information Systems for Crisis Response and Management 2, no. 4 (October 2010): 48–58. http://dx.doi.org/10.4018/jiscrm.2010100104.

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Lack of relevant information, particularly geospatial information, is one of the major challenges in emergency management. In the past few years, geospatial information created by volunteers and facilitated by social networks has become a promising data source in time-critical situations. This paper discusses the roles that social networks can play in the crowdsourcing of geospatial information for emergency management, data generation and dissemination through social networks, and investigates the relationships and interactions in social networks. Research issues arise in the areas of data access, data quality, information synthesis, emerging patterns of human behaviors in emergencies, analysis and visualization of nested social networks, implementation of information systems for emergency management, privacy, and equity.

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35

Yue, Peng, Jianya Gong, Liping Di, Lianlian He, and Yaxing Wei. "Integrating semantic web technologies and geospatial catalog services for geospatial information discovery and processing in cyberinfrastructure." GeoInformatica 15, no. 2 (October 9, 2009): 273–303. http://dx.doi.org/10.1007/s10707-009-0096-1.

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Praharaj, S., and E. Wentz. "BUILDING COMMUNITY RESILIENCE THROUGH GEOSPATIAL INFORMATION DASHBOARDS." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W5-2022 (October 17, 2022): 151–57. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w5-2022-151-2022.

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Abstract. This article discusses a dashboard toolkit designed at the Knowledge Exchange for Resilience at the Arizona State University to integrate and analyze multi-agency data offering many ways of visualizing big data representable, contextualizable, and intelligible to a non-expert target audience. We outline a community-driven approach to identify pressing resiliency issues and deploy dashboard tools on targeted areas for significant community benefit. Our research builds on the offerings of data science to aid community-focused decision support systems to enable evidence-based and real-time decision-making. We hypothesize that building community resilience in response to emerging challenges requires a combination of timely data at the local scale and easy-to-use decision support tools. This research particularly focuses on augmenting the capacity of communities through dashboard technologies to comprehend rapidly evolving issues and address them in a timely and efficient manner. Our work contributes to a rapidly growing research domain around geospatial data visualization technologies that are increasingly playing a vital role in the shaping of government policies, including resiliency planning and disaster response. This study argues that dashboards that are action-oriented, easy-to-use, and locally embedded within the community have much more potential to be used as a decision-support system. The findings indicate that community-based knowledge networks catalyzed and influenced by modern technologies might provide a model to negotiate the gaps between ecosystem-based and social-science-focused conceptualization of community resilience.

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37

Watters, Carolyn, and Ghada Amoudi. "GeoSearcher: Geospatial ranking of search engine results." Proceedings of the American Society for Information Science and Technology 39, no. 1 (January 31, 2005): 409–16. http://dx.doi.org/10.1002/meet.1450390145.

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38

Mazroob Semnani, N., P. V. Kuper, M. Breunig, and M. Al-Doori. "TOWARDS AN INTELLIGENT PLATFORM FOR BIG 3D GEOSPATIAL DATA MANAGEMENT." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-4 (September 19, 2018): 133–40. http://dx.doi.org/10.5194/isprs-annals-iv-4-133-2018.

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Abstract. The use of intelligent technologies within 3D geospatial data analysis and management will decidedly open the door towards efficiency, cost transparency, and on-time schedules in planning processes. Furthermore, the mission of smart cities as a future option of urban development can lead to an environment that provides high-quality life along stable structures. However, neither geospatial information systems nor building information modelling systems seem to be well prepared for this new development. After a review of current approaches and a discussion of their limitations we present our approach on the way to an intelligent platform for the management and analysis of big 3D geospatial data focusing on infrastructure projects such as metro or railway tracks planning. three challenges are presented focusing on the management of big geospatial data with existing geo-database management systems, the integration of heterogeneous data, and the 3D visualization for database query formulation and query results. The approach for the development of a platform for big geospatial data analysis is discussed. Finally, we give an outlook on our future research supporting intelligent 3D city applications in the United Arab Emirates.

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39

Jetlund, Onstein, and Huang. "Adapted Rules for UML Modelling of Geospatial Information for Model-Driven Implementation as OWL Ontologies." ISPRS International Journal of Geo-Information 8, no. 9 (August 22, 2019): 365. http://dx.doi.org/10.3390/ijgi8090365.

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This study aims to improve the implementation of models of geospatial information in Web Ontology Language (OWL). Large amounts of geospatial information are maintained in Geographic Information Systems (GIS) based on models according to the Unified Modeling Language (UML) and standards from ISO/TC 211 and the Open Geospatial Consortium (OGC). Sharing models and geospatial information in the Semantic Web will increase the usability and value of models and information, as well as enable linking with spatial and non-spatial information from other domains. Methods for conversion from UML to OWL for basic concepts used in models of geospatial information have been studied and evaluated. Primary conversion challenges have been identified with specific attention to whether adapted rules for UML modelling could contribute to improved conversions. Results indicated that restrictions related to abstract classes, unions, compositions and code lists in UML are challenging in the Open World Assumption (OWA) on which OWL is based. Two conversion challenges are addressed by adding more semantics to UML models: global properties and reuse of external concepts. The proposed solution is formalized in a UML profile supported by rules and recommendations and demonstrated with a UML model based on the Intelligent Transport Systems (ITS) standard ISO 14825 Geographic Data Files (GDF). The scope of the resulting ontology will determine to what degree the restrictions shall be maintained in OWL, and different conversion methods are needed for different scopes.

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40

Zheng, Q. "GEOSPATIAL INFORMATION BASED EMERGENCY RESPONSE SYSTEM FOR GEOLOGICAL DISASTERS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 1293–98. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-1293-2020.

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Abstract. Emergency response is the critical phase in disaster management, which can save lives and reduce losses by useful, accurate, and timely information. The surveying and mapping authorities at all levels are making great efforts to meet the increasing demand for geospatial data in disaster and risk management. In this paper, it takes the Sichuan province of China as an example. It presents a geospatial information based emergency response system for geological disasters from the perspective of the provincial mapping authority. The scheme of the response system aims to solve many problems that arose in practical disaster management and to meet the requirements of public safety and government management by geospatial information and services. Built on historical experience and improved through practical application, the system has now effectively improved the workflow in all phases of emergency response. The paper discusses the critical contents of the system’s general framework in terms of emergency mechanism, GIS technology, geospatial data, emergency equipment, and professional teams. A case study is applied in this paper to explain how the system makes its function. The end of the article gives an analysis of its benefits and disadvantages and a comparison with other similar systems.

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41

Li, Haonan, Ehsan Hamzei, Ivan Majic, Hua Hua, Jochen Renz, Martin Tomko, Maria Vasardani, Stephan Winter, and Timothy Baldwin. "Neural factoid geospatial question answering." Journal of Spatial Information Science, no. 23 (December 24, 2021): 65–90. http://dx.doi.org/10.5311/josis.2021.23.159.

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Existing question answering systems struggle to answer factoid questions when geospatial information is involved. This is because most systems cannot accurately detect the geospatial semantic elements from the natural language questions, or capture the semantic relationships between those elements. In this paper, we propose a geospatial semantic encoding schema and a semantic graph representation which captures the semantic relations and dependencies in geospatial questions. We demonstrate that our proposed graph representation approach aids in the translation from natural language to a formal, executable expression in a query language. To decrease the need for people to provide explanatory information as part of their question and make the translation fully automatic, we treat the semantic encoding of the question as a sequential tagging task, and the graph generation of the query as a semantic dependency parsing task. We apply neural network approaches to automatically encode the geospatial questions into spatial semantic graph representations. Compared with current template-based approaches, our method generalises to a broader range of questions, including those with complex syntax and semantics. Our proposed approach achieves better results on GeoData201 than existing methods.

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42

Teixeira, Hugo, Alexandre Magalhães, André Ramalho, Maria de Fátima Pina, and Hernâni Gonçalves. "Indoor Environments and Geographical Information Systems: A Systematic Literature Review." SAGE Open 11, no. 4 (October 2021): 215824402110503. http://dx.doi.org/10.1177/21582440211050379.

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The increasing dissemination of geographic information systems (GIS) in recent years has broadened the availability and use of geospatial tools, mostly to analyze the spatial data of different territories. A territory can be viewed at different analysis scales, and some buildings are as complex as small cities, presenting the opportunity to use GIS to study the dynamics, patterns, and phenomena within a building. This study presents a systematic literature review of the relevant evidence focused on the utilization of GIS in indoor spaces. To this end, we searched in three scientific libraries following the PRISMA statement guidelines. All phases were analyzed independently by two of the authors and agreement between them calculated through the Kappa statistic. In total, 50 studies were included. A qualitative synthesis was performed, considering the assessment of data and heterogeneity of methodologies within the included articles. Subsequently, the studies were categorized into five groups: indoor management, indoor geospatial analysis, indoor positioning, indoor data acquisition, and indoor spatial data models. The results demonstrate that research on the use of GIS in indoor spaces is still emerging, despite its great potential to help and GIS users, data producers, researchers, or policymakers to improve their work, providing scientific evidence for decision support.

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43

Galić, Z., M. Baranović, K. Križanović, and E. Mešković. "Geospatial data streams: Formal framework and implementation." Data & Knowledge Engineering 91 (May 2014): 1–16. http://dx.doi.org/10.1016/j.datak.2014.02.002.

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44

Stepinski, Tomasz F., Wei Ding, and Christoph F. Eick. "Controlling patterns of geospatial phenomena." GeoInformatica 15, no. 3 (January 29, 2010): 399–416. http://dx.doi.org/10.1007/s10707-010-0107-2.

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45

Evangelidis, Konstantinos, Konstantinos Ntouros, Stathis Makridis, and Constantine Papatheodorou. "Geospatial services in the Cloud." Computers & Geosciences 63 (February 2014): 116–22. http://dx.doi.org/10.1016/j.cageo.2013.10.007.

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46

Jetlund, K. "A STRUCTURE OF UML PROFILES FOR MODELLING OF GEOSPATIAL INFORMATION IN GIS, ITS AND BIM." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences VI-4/W1-2020 (September 3, 2020): 101–8. http://dx.doi.org/10.5194/isprs-annals-vi-4-w1-2020-101-2020.

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Abstract. This study aims to improve the interoperability between models of geospatial information from the applications domains of Geographic Information Systems (GIS), Intelligent Transport Systems (ITS) and Building Information Models (BIM). A state-of-the-art analysis showed that the Unified Modelling Language (UML) and Model-Driven Architecture (MDA) are used for modelling information in a geospatial context in all three domains, but with different approaches and levels of formality. A structure of formal UML profiles for modelling of geospatial information in GIS, ITS and BIM is suggested and tested for implementation. The Core Geospatial Profile (GCP) and general encoding profiles for the Geography Markup Language (GML) and the Web Ontology Language (OWL) are based on adapted concepts from ISO/TC 211 standards. Community specific profiles for conceptual models and encodings are based on UML profiles and the use of UML for specific information models in the three application domains. The studies and related research showed that the structure of UML profiles could be implemented and used for information modelling in the UML software Enterprise Architect and that existing profiles and information models could be adapted into the framework. Integration of information models in a common approach based on MDA and UML establishes a fundament for improved interoperability through a shared understanding of the digital representation of the real world.

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47

Du, Gen Yuan, Fang Miao, and Xi Rong Guo. "A Novel Network Service Mode of Geospatial Information and its Prototype System." Advanced Materials Research 108-111 (May 2010): 319–23. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.319.

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This paper proposes a novel digital earth platform framework, which is a application, service and decision-making support systems of geospatial data acquisition, storage, transmission, conversion, processing, analysis, retrieval, expression and output as a unified body, the core of which is to deal with geospatial data for spatial geographic information network service Geo-Browser/Geospatial Information Server (G/S) mode and Hyper Geographic Markup Language (HGML). Depth understanding and analysis of platform architecture, this paper realizes of digital earth platform prototype – U-Star based on the geospatial information network service G/S mode, the platform has the merits of C/S mode that full use of client resources, efficient to deal with the client data, as well as the advantages of B/S mode that the unified client and convenient to access network. This platform is a new server which can cope with massive geospatial information and a solution which can provide efficient service. It has already been applied into many fields, such as the digital tourism service system, the time sequence analysis of Wenchuan Earthquake, the real-time video monitoring based on the digital earth platform and the intelligent processing and exhibition of remote sensing data. The result indicates that the perfection of space, time and complexion of the geospatial information network accessing will effectively improve the quality and efficiency of the shared data, which has very important theoretical significance and bright prospect of application.

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48

Duckham, M., and M. Worboys. "An algebraic approach to automated geospatial information fusion." International Journal of Geographical Information Science 19, no. 5 (May 2005): 537–57. http://dx.doi.org/10.1080/13658810500032339.

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49

Asiyanbola, Raimi Abidemi. "Geospatial literacy in Africa-Nigeria." Proceedings of the ICA 2 (July 10, 2019): 1–7. http://dx.doi.org/10.5194/ica-proc-2-5-2019.

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Abstract. Literature reveals that geography has always been a critical type of information that humans – in fact all animals – collect, organize, and use, and that place-based information is vital to survival on our planet. Geographic literacy is defined as the ability to apply geographic skills and understanding in personal and civic lives. The growing interest has been sparked by an understanding of the role that spatial literacy plays in implementation of geospatial technologies such as computer, cell phone, internet, geographic information systems (GIS), remote sensing, and global positioning systems (GPS). These technologies are fundamentally changing how we see the world and interact with it. This paper examines geospatial literacy, with reference to people’s awareness and use of geospatial literacy aid technologies in Ibadan metropolitan area, Nigeria. The research questions that the paper addresses include the following: How are people’s knowledge of computer, cell phone and internet? How are people’s awareness of geospatial literacy aid technologies? How are people using geospatial literacy aid technologies? Are people interested in learning more on how to use geospatial literacy aid technologies? What are the challenges confronting the people? The data used in the paper was from administration of 152 questionnaires to civil servants in five local governments in Ibadan metropolitan area and at the Oyo State Government Secretariat in Ibadan, Oyo State, Nigeria between February and August, 2017. Descriptive statistics are used to analyse the data. Policy implications of the findings towards improving human capacity building in geospatial literacy aid technologies were discussed in the paper.

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Breunig, Martin, Patrick Erik Bradley, Markus Jahn, Paul Kuper, Nima Mazroob, Norbert Rösch, Mulhim Al-Doori, Emmanuel Stefanakis, and Mojgan Jadidi. "Geospatial Data Management Research: Progress and Future Directions." ISPRS International Journal of Geo-Information 9, no. 2 (February 4, 2020): 95. http://dx.doi.org/10.3390/ijgi9020095.

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Without geospatial data management, today’s challenges in big data applications such as earth observation, geographic information system/building information modeling (GIS/BIM) integration, and 3D/4D city planning cannot be solved. Furthermore, geospatial data management plays a connecting role between data acquisition, data modelling, data visualization, and data analysis. It enables the continuous availability of geospatial data and the replicability of geospatial data analysis. In the first part of this article, five milestones of geospatial data management research are presented that were achieved during the last decade. The first one reflects advancements in BIM/GIS integration at data, process, and application levels. The second milestone presents theoretical progress by introducing topology as a key concept of geospatial data management. In the third milestone, 3D/4D geospatial data management is described as a key concept for city modelling, including subsurface models. Progress in modelling and visualization of massive geospatial features on web platforms is the fourth milestone which includes discrete global grid systems as an alternative geospatial reference framework. The intensive use of geosensor data sources is the fifth milestone which opens the way to parallel data storage platforms supporting data analysis on geosensors. In the second part of this article, five future directions of geospatial data management research are presented that have the potential to become key research fields of geospatial data management in the next decade. Geo-data science will have the task to extract knowledge from unstructured and structured geospatial data and to bridge the gap between modern information technology concepts and the geo-related sciences. Topology is presented as a powerful and general concept to analyze GIS and BIM data structures and spatial relations that will be of great importance in emerging applications such as smart cities and digital twins. Data-streaming libraries and “in-situ” geo-computing on objects executed directly on the sensors will revolutionize geo-information science and bridge geo-computing with geospatial data management. Advanced geospatial data visualization on web platforms will enable the representation of dynamically changing geospatial features or moving objects’ trajectories. Finally, geospatial data management will support big geospatial data analysis, and graph databases are expected to experience a revival on top of parallel and distributed data stores supporting big geospatial data analysis.

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