Global Spatial Data Infrastructure Research Articles

International exchange of geospatial information and cooperation in the field of land castras

It was determined that the modern development of geographic information systems (GIS) and the growing need for international exchange of geospatial information (GI) emphasize the importance of this area for solving global challenges. The diversity of standards and methodologies in different countries creates specific barriers to practical cooperation. However, introducing the latest technologies, such as cloud computing and artificial intelligence, opens up new opportunities for exchanging and using AI at the international level. The research focuses on analyzing existing GI exchange practices, examining issues that hinder cooperation, examining cases of successful international exchange, and identifying factors that facilitate or hinder effective exchange. The importance of developing international cooperation in the cadastre of natural resources is emphasized by the unification of practices and standards and the development of a common regulatory framework, which promotes a global approach to solving cadastral issues. The development of such infrastructures as the US National Spatial Data Infrastructure (NSDI) is a vivid example of the successful implementation of integration and access to geospatial information that supports decision-making at the government level. Similar projects implemented in other countries and regions, including the Global Spatial Data Infrastructure (GSDI) and others, testify to the growing importance of joint efforts in this area. A vital aspect of the research is the analysis of challenges related to the international exchange of GIs and the search for ways to overcome them, in particular through the standardization of methods of collection, processing, and presentation of geospatial data, the use of open standards provided by the OGC consortium is defined as the basis for the development of web applications, that support sharing and collaboration in the field of GI. Ultimately, the study emphasizes the importance of continuous development and maintenance of spatial data infrastructures both for solving specific institutional tasks and for the general improvement of the availability and efficiency of geospatial information use, updating the technological base, regular data updates, and integration with modern information technologies, such as cloud computing and artificial intelligence are identified as critical elements of successful international exchange of geospatial information. Keywords: geospatial information, spatial data infrastructure, land cadastre, unified exchange format, GeoViewer, geoportal.

Infrastructural Organization of Geospatial Data in The Global Level: A Case Study of Albanian Global Mapping Dataset

Today, the development of economic and financial situation concerning the protection of environment and natural resources in a wider scope depends on the use of geospatial data. One of the main aims of the infrastructural organization of geospatial data is to provide users to be capable of acquiring complete, exact and updated dataset at the right time. This is necessary for providing an ideal environment, where all stakeholders can work collaboratively in an effective way, in order to solve environmental issues and to achieve their targets. Global Mapping (GM), a project established by United Nations, is one of the crucial contributions to the development of Global Spatial Data Infrastructure (GSDI). This case study on Albanian GM dataset was aimed at performing analyses of infrastructural organization of geospatial data in global-intercontinental level. Data standardization of GM as contributor of GSDI was analyzed through developed Albanian GM dataset. The main components taken into consideration for performing research analyses were data and metadata, technology, institutional framework, policies, interoperability, network services, search opportunities, and data sharing within GSDI. The main findings of this study are the necessity of infrastructural organization of geospatial data in the global level, known as GSDI, by including official geospatial datasets developed by the national mapping organizations of countries all over the world, in order to be used for environmental monitoring and protection, as well as for early warning management in international level. Finally, based on the research results, four conclusions for GSDI are offered, in order to be considered as guideline for further development of unified and globally homogeneous infrastructure of spatial data set.
 Keywords: GSDI; GM; spatial data infrastructure; Albania.
 Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember
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Semantic relatedness algorithm for keyword sets of geographic metadata

ABSTRACTAdvances in linked geospatial data, recommender systems, and geographic information retrieval have led to urgent necessity to assess the overall semantic relatedness between keyword sets of geographic metadata. In this study, a new model is proposed for computing the semantic relatedness between arbitrary two keyword sets of geographic metadata stored in current global spatial data infrastructures. In this model, the overall semantic relatedness is derived by pairing these keywords that are found to be most relevant to each other and averaging their relatedness. To find the most relevant keywords across two keyword sets precisely, the keywords in the keyword set of geographic metadata are divided into three kinds: the thesaurus elements, the WordNet elements, and the statistical elements. The thesaurus-lexical relatedness measure (TLRM), the extended thesaurus-lexical relatedness measure (ETLRM), and the Longest Common Substring method are proposed to compute the semantic relatedness between two thesaurus elements, two WordNet elements, a thesaurus element, and a WordNet element and two statistical elements, respectively. A human data set – the geographic-metadata’s keyword set relatedness dataset, which was used to evaluate the precision of the semantic relatedness measures of keyword sets of geographic metadata, was created. The proposed method was evaluated against the human-generated relatedness judgments and was compared with the Jaccard method and Vector Space Model. The results demonstrated that the proposed method achieved a high correlation with human judgments and outperformed the existing methods. Finally, the proposed method was applied to quantitatively linked geospatial data.

Similarity Measurement of Metadata of Geospatial Data: An Artificial Neural Network Approach

To help users discover the most relevant spatial datasets in the ever-growing global spatial data infrastructures (SDIs), a number of similarity measures of geospatial data based on metadata have been proposed. Researchers have assessed the similarity of geospatial data according to one or more characteristics of the geospatial data. They created different similarity algorithms for each of the selected characteristics and then combined these elementary similarities to the overall similarity of the geospatial data. The existing combination methods are mainly linear and may not be the most accurate. This paper reports our experiences in attempting to learn the optimal non-linear similarity integration functions, from the knowledge of experts, using an artificial neural network. First, a multiple-layer feed forward neural network (MLFFN) was created. Then, the intrinsic characteristics were used to represent the metadata of geospatial data and the similarity algorithms for each of the intrinsic characteristics were built. The training and evaluation data of MLFFN were derived from the knowledge of domain experts. Finally, the MLFFN was trained, evaluated, and compared with traditional linear combination methods, which was mainly a weighted sum. The results show that our method outperformed the existing methods in terms of precision. Moreover, we found that the combination of elementary similarities of experts to the overall similarity of geospatial data was not linear.

A methodological evaluation of the Polish cadastral system based on the global cadastral model

In an era when information is the main strategic resource, there is a growing need for comprehensive spatial information, including cadastral information, which necessitates the continuous modernization of cadastral systems. Standardization requirements are imposed by international agreements on the development of Global Spatial Data Infrastructure (GSDI). These efforts gave rise to new concepts and systems in the international arena, including Cadastre 2014, the Land Administration System (LAS), CCDM/LADM, Cadastre 2012, Cadastre 2034, Cadastre’Inspired, Cadastre 2.0, Cadastre 3D and Fit-for-Purpose Land Administration. These concepts have led to the development of new functional solutions for cadastral systems.The aim of this article was to analyse and to evaluate the Polish cadastral system based on the proposed universal method for evaluating cadastral systems. A global cadastral model has been proposed, and the Polish cadastral system has been evaluated in the context of the developed model. The results were used to identify the system’s strengths and weaknesses.

From Surveying to Geomatics

In the land surveying profession fast changes have been taking place in the last fifty years. Technological changes are generated by the Information and Communication Technologies; the analogue – digital trends; the automatic data acquisition methods replace manual ones; instead of two-dimensional base maps we use dynamic spatial databases more and more integrated into a global data infrastructure. However, these changes cause impacts also on scientific level. The traditional top-down approach substituted by bottom-up methodologies; in many cases the point-by-point measurement is changed by 3D laserscanning or Unmanned Aerial Systems, which produces huge amount of data, but it needs new algorithms for information extraction; instead of a simple data provision land surveyors support complex spatial decisions. The paper is dealing with some aspects of these changes. In the first chapter the authors would like to highlight the “data-information-knowledge” relations and the importance of changes in professional education. The second chapter gives an example of the benefits of a Global Spatial Data Infrastructure in spatial decision support. Finally we introduce a new concept (Building Information Modelling) in modelling the real world. However, until now BIM is used in building construction industry, it can can be a paradigm shift in geospatial information management in general.

INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH

Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). <br><br> Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. <br><br> In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. <br><br> Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. <br><br> This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

INTEGRATION OF REMOTELY SENSED DATA INTO GEOSPATIAL REFERENCE INFORMATION DATABASES. UN-GGIM NATIONAL APPROACH

Abstract. Remote sensing satellites, together with aerial and terrestrial platforms (mobile and fixed), produce nowadays huge amounts of data coming from a wide variety of sensors. These datasets serve as main data sources for the extraction of Geospatial Reference Information (GRI), constituting the “skeleton” of any Spatial Data Infrastructure (SDI). Since very different situations can be found around the world in terms of geographic information production and management, the generation of global GRI datasets seems extremely challenging. Remotely sensed data, due to its wide availability nowadays, is able to provide fundamental sources for any production or management system present in different countries. After several automatic and semiautomatic processes including ancillary data, the extracted geospatial information is ready to become part of the GRI databases. In order to optimize these data flows for the production of high quality geospatial information and to promote its use to address global challenges several initiatives at national, continental and global levels have been put in place, such as European INSPIRE initiative and Copernicus Programme, and global initiatives such as the Group on Earth Observation/Global Earth Observation System of Systems (GEO/GEOSS) and United Nations Global Geospatial Information Management (UN-GGIM). These workflows are established mainly by public organizations, with the adequate institutional arrangements at national, regional or global levels. Other initiatives, such as Volunteered Geographic Information (VGI), on the other hand may contribute to maintain the GRI databases updated. Remotely sensed data hence becomes one of the main pillars underpinning the establishment of a global SDI, as those datasets will be used by public agencies or institutions as well as by volunteers to extract the required spatial information that in turn will feed the GRI databases. This paper intends to provide an example of how institutional arrangements and cooperative production systems can be set up at any territorial level in order to exploit remotely sensed data in the most intensive manner, taking advantage of all its potential.

Forming a global monitoring mechanism and a spatiotemporal performance model for geospatial services

Geographic information service (GIService) has become popular in the last decade to develop applications for addressing global challenges. Performance is one of the most important criteria to help users select distributed online GIService for developing geospatial applications including natural hazards and emergency responses. However, performance accuracy is limited by the single-location-based evaluation mechanism while service performance is dynamic in space and time between end-users and services. We propose a spatiotemporal performance evaluation mechanism to improve the accuracy. Specially, a cloud and volunteer computing mechanism is proposed to collect performance information of globally distributed GIServices. A global spatiotemporal performance model is designed to integrate spatiotemporal dynamics for better performance evaluation for users from different regions at different times. This model is tested to support GIService selection in global spatial data infrastructures (SDIs). The experiment confirms that the proposed model provides more accurate evaluations for global users and better supports geospatial resource utilizations in SDIs than previous mechanisms. The methodology can be adopted to improve the services of other regional and global distributed operational systems.

Building bridges: experiences and lessons learned from the implementation of INSPIRE and e-reporting of air quality data in Europe

Abstract The collection, exchange and use of air quality data require diverse monitoring, processing and dissemination systems to work seamlessly together. These systems should supply data in a format usable for other applications such as planning, assessing population exposure and environmental impact assessment. As air quality does not change abruptly near national borders, international cooperation within this domain is highly desirable. This manuscript reports lessons learned during the implementation phase of one the world’s largest data harmonisation effort of environmental information infrastructures, INSPIRE, a backbone of a European wide spatial data reporting system which involves an unprecedented number of actors and volumes of data. It is important within the context of the Digital Earth concept and the establishment of a global spatial data infrastructure (SDI) through the Global Earth Observation System of Systems (GEOSS), as the quality of ambient air is among the most pressing contemporary environmental problems. We summarise our findings from the perspective of national public authorities, obliged by law to transmit standardised spatio-temporal data to streamline reporting and facilitate the use of information, while keeping public expenditure under control. To develop implementation strategies for these type of e-reporting data flows we established a cross-border case study, looking at the process of harmonisation and exchange of data in Belgium and the Netherlands based on interoperable standards. Our results cover the legal, semantic, technological and organisational aspects of reporting. They are relevant to a cross-thematic audience having to undergo similar processes of reporting, such as climate change, environmental noise, marine, biodiversity, water management, etc.

An optimized framework for seamlessly integrating OGC Web Services to support geospatial sciences

OGC Web Services (OWS) are essential building blocks for the national and global spatial data infrastructure (NSDI and GSDI) and the geospatial cyberinfrastructure (GCI). Web Map Service (WMS), Web Feature Service (WFS), Web Coverage Service (WCS), and Catalogue Service for Web (CSW) have been increasingly adopted to serve scientific data. Interoperable services can facilitate the integration of different scientific applications by searching, finding, and utilizing the large number of scientific data and Web services. However, these services are widely dispersed and hard to be found and utilized with acceptable performance. This is especially true when developing a science application to seamlessly integrate multiple geographically dispersed services. Focusing on the integration of distributed OWS resources, we propose a layer-based service-oriented integration framework and relevant optimization technologies to search and utilize relevant resources. Specifically, (1) an AJAX (Asynchronous JAvaScript and eXtensible Markup Language)-based synchronous multi-catalogue search is proposed and utilized to enhance the multi-catalogue searching performance; (2) a layer-based search engine with spatial, temporal, and performance criteria is proposed and used for identifying better services; (3) a service capabilities clearinghouse (SCCH) is proposed and developed to address the service issues identified by a statistical experiment. A science application of data correlation analysis is used as an example to demonstrate the performance enhancement of the proposed framework.

Global spatial data infrastructure

In this paper, the explanation of the term and concept of spatial data infrastructure is represented. It is emphasized the role of global spatial data infrastructure to support the joint efforts, worldwide, for the sustainable development of environment protection and efficient decision-making. Geo-information technology and spatial data infrastructure have an important role in the modern world by providing the possibility of governments, local communities, organizations, business sector, academic community and ordinary people progress in solving many problems. Most of these problems have regional or global character. International organization and institutions around the globe provide and share global spatial data about the state of globe and its changes, stressing the importance of public access to information and international cooperation. Approach in building the global infrastructure of spatial data requires the culture of joint working and sharing of spatial data as a common good. Significant support to the global spatial data infrastructure provides cartographic initiative Global Map and the development of geo-information products and services prominent the Earth Viewers. The development of global spatial data infrastructure is undoubtedly a step forward civilization but further increase the problems of privacy, public and national security.

The Role of Institutional Mechanisms in Spatial Data Infrastructure Development that Supports Decision-making

Improved economic, social and environmental decision-making are principal objectives for investing in the development of Spatial Data Infrastructure (SDI) at all political and administrative levels. Indeed, Resolution 7 of the recent 5th Global Spatial Data Infrastructure (GSDI) conference in Cartagena, Colombia (GSDI, 2001) argued that the purpose of the GSDI is to improve the availability, accessibility, and applicability of spatial information for decisionmaking. While accepting the development of institutional mechanisms to support decisionmaking by promoting the availability and accessibility of spatial information as part of SDI institutional frameworks, many institutional mechanisms fall short of addressing the application of spatial data to decison-making. From an institutional perspective, the motivation for SDI implementation is the impracticality of a single organisation producing and maintaining the wide variety of data and models needed to inform many decisions, resulting in a need for sharin...

Potential and benefits of electronic charts to Maritime Administrations

Electronic charts have come more and more into use for marine navigation. If complying with the relevant international standards they are an accepted substitute to the mandatory carriage of paper nautical charts. However, the potential of such official, high-quality electronic chart data goes far beyond the use for navigation. In order to show its potential, the basic concepts and features of official electronic charts as a marine geographic information data base are explained and the relation of Hydrographic Offices responsible for their production, to Maritime Administrations is described. The data standard to be followed for electronic charts opens the use of the data for a wide range of possible applications. If efficiently organised, Maritime Administrations can be provided with a powerful, versatile database establishing a single geographic reference data base for e.g. Vessel Traffic Services, for Search and Rescue as well as for various applications in Coastal Zone Management including coastal protection and marine environmental protection. Ultimately, digital marine geographic information will become part of the evolving global spatial data infrastructure.

Global Spatial data Infrastructure: Current Developments

A number of Spatial Data Infrastructure initiatives at local, national and European levels have been progressing since the early 1990s with a parallel global one emerging, beginning at the Bonn 1996 and continuing at the North Carolina 1997 meeting. This paper outlines some of the issues involved. Many of these are similar to those being experienced at the national and regional levels, but the solution to many of them will be different as will their implication. In particular it sets out the conclusions of the Chapel Hill, North Carolina meeting. The implementation of which is ongoing.

Global spatial data infrastructure: Current developments

Global spatial data infrastructure: Current developments

TOWARDS A GLOBAL SPATIAL DATA INFRASTRUCTURE: The Contribution of the Permanent Committee on GIS Infrastructure for Asia and the Pacific

The current interest in the concept of a Global Spatial Data Infrastructure (GSDI) is a direct response to the growing need to share spatial data and experience, between nations, in order to confront global issues such as sustainable development. The work being undertaken by the Permanent Committee on GIS Infrastructure for Asia and the Pacific is contributing to the achievement of a GSDI by developing, firstly, a spatial data infrastructure for the Asia and Pacific region. This regional infrastructure provides a fundamental building block in the global infrastructure solution. This paper proposes that the regional approach being taken by the Permanent Committee is a model that can be applied in other regions of the world. Furthermore, this regional approach has the potential to resolve many of the barriers to global cooperation.