Infrastructural Organization of Geospatial Data in The Global Level: A Case Study of Albanian Global Mapping Dataset
Abstract
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
This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License
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Crompvoets, J. W. H. C. (2006). National spatial data clearinghouses: worldwide development and impact : Wageningen University.
Díaz, L., & Schade, S. (2011). GEOSS service factory: Assisted publication of geospatial content. In Advancing Geoinformation Science for a Changing World (pp. 423-442). Springer, Berlin, Heidelberg.
European Commission, (2004) European Interoperability Framework for Pan-European eGovernment services (vers. 1), European Communities.
Ferreira, K. R., de Queiroz, G. R., Vinhas, L., Câmara, G., Maurano, L. E., Souza, R. C. M., & Sanchez, A. (2015). Towards a Spatial Data Infrastructure for Big Spatiotemporal Data Sets. In 17th Brazilian Symposium on Remote Sensing (SBSR), 2015. Proceedings (pp. 7588-7594).
Forkel, M., Dorigo, W., Lasslop, G., Teubner, I., Chuvieco, E., & Thonicke, K. (2017). A data-driven approach to identify controls on global fire activity from satellite and climate observations (SOFIA V1). Geoscientific Model Development, 10(12), 4443-4476. doi:10.5194/gmd-10-4443-2017
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Groot, R., & McLaughlin, J. (2000). Geospatial Data Infrastructure: concepts, cases and good practice. Oxford University Press.
Hjelmager, J., Moellering, H., Cooper, A., Delgado, T., Rajabifard, A., Rapant, P., ... & Iwaniak, A. (2008). An initial formal model for spatial data infrastructures. International Journal of Geographical Information Science, 22(11-12), 1295-1309.
Hoffman-Hall, A., Loboda, T. V., Hall, J. V., Carroll, M. L., & Chen, D. (2019). Mapping remote rural settlements at 30 m spatial resolution using geospatial data-fusion. Remote Sensing of Environment, 233 doi:10.1016/j.rse.2019.111386
Holland, P., (2003). Global, regional and national SDI initiatives and the Global Disaster Information Network (GDIN). Australian Surveying and Land Information Group.
Hu, Y. & Li, W. (2017). "Spatial Data Infrastructures", The Geographic Information Science & Technology Body of Knowledge, John P. Wilson (ed.).
Idrizi B. (2017). Presentation: SDI from local up to global level, Struga : Macedonia.
Idrizi, B. (2006). Developing of globally homogeneous geographic data set through global mapping project. Kartografija i geoinformacije (Cartography and Geoinformation), 5(6), 90-101.
Idrizi, B. (2018). General Conditions of Spatial Data Infrastructure. International Journal on Natural and Engineering Sciences, 12 (1): 57-62
Idrizi, B., Meha, M., Nikolli, P., & Kabashi, I. (2011). Data quality of Global Map and some possibilities/limitations for its wide utilisation for global issues. Survey Review, 44(325), 134-140.
Lee, M. H., Park, J. M., Shin, D. B., & Ahn, J. W. (2015). A study on the selection of core services for geo-spatial big data. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 33(5), 385-396. doi:10.7848/ksgpc.2015.33.5.385
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Lu, Q., Ma, Y., & Xia, G. -. (2017). Active learning for training sample selection in remote sensing image classification using spatial information. Remote Sensing Letters, 8(12), 1210-1219. doi:10.1080/2150704X.2017.1375610
Lubishtani M., Idrizi B. (2016). Developing of the Albanian Global Map dataset. Micro Macro Mezzo Geo Information, 7.
Lubishtani M., Idrizi B., Bajrami Lubishtani F. (2018). The historical development of Global Mapping. Proceedings, 1st Western Balkan Conference on GIS, mine surveying, geodesy and geomatics. Tirana. Albania. ISBN: 978-9928-07-599-4.
Maruyama H., Sasaki H., and Takaki O., (2005). Global mapping project by national mapping organizations on the globe. In GSDI-9 Conference proceedings.
Nebert, D. (2009). “Introduction to Geospatial Web Services.” Workshop presentation at Global Geospatial Conference (GSDI11)
Park, J. M., Yu, S. C., Ahn, J. W., & Shin, D. B. (2016). A study on policy and system improvement plan of geo-spatial big data services in korea. Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, 34(6), 579-589. doi:10.7848/ksgpc.2016.34.6.579
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Rajabifard A., Williamson I. P., Holland P. & Johnstone G., (2000), From Local to Global SDI Initiatives: A Pyramid Building Blocks. Proceedings of the 4th GSDI Conference (13 – 15 March), Cape Town, South Africa.
Sinnott, R. O., & Voorsluys, W. (2016). A scalable cloud-based system for data-intensive spatial analysis. International Journal on Software Tools for Technology Transfer, 18(6), 587-605. doi:10.1007/s10009-015-0398-6
Specka, X., Gärtner, P., Hoffmann, C., Svoboda, N., Stecker, M., Einspanier, U., . . . Heinrich, U. (2019). The BonaRes metadata schema for geospatial soil-agricultural research data – merging INSPIRE and DataCite metadata schemes. Computers and Geosciences, 132, 33-41. doi:10.1016/j.cageo.2019.07.005
Thapa, R. B., Matin, M. A., & Bajracharya, B. (2019). Capacity building approach and application: Utilization of earth observation data and geospatial information technology in the hindu kush himalaya. Frontiers in Environmental Science, 7 doi:10.3389/fenvs.2019.00165
Thompson, E. S., & de Beurs, K. M. (2018). Tracking the removal of buildings in rust belt cities with open-source geospatial data. International Journal of Applied Earth Observation and Geoinformation, 73, 471-481. doi:10.1016/j.jag.2018.07.007
Vasin, Y. G., & Yasakov, Y. V. (2016). Distributed database management system for integrated processing of spatial data in a gis. Computer Optics, 40(6), 919-928. doi:10.18287/2412-6179-2016-40-6-919-928
Williamson, I.P., Grant, D. and Rajabifard, A. (2005). ‘Land Administration and Spatial Data Infrastructure’. Proceedings of FIG Working Week/ GSDI-8, Cairo.
Wu, X., Hong, D., Ghamisi, P., Li, W., & Tao, R. (2018). MsRi-CCF: Multi-scale and rotation-insensitive convolutional channel features for geospatial object detection. Remote Sensing, 10(12) doi:10.3390/rs10121990
Yang, L., Jin, S., Danielson, P., Homer, C., Gass, L., Bender, S. M., . . . Xian, G. (2018). A new generation of the united states national land cover database: Requirements, research priorities, design, and implementation strategies. ISPRS Journal of Photogrammetry and Remote Sensing, 146, 108-123. doi:10.1016/j.isprsjprs.2018.09.006
Yu, S. -., Shin, D. -., & Ahn, J. -. (2016). A study on concepts and utilization of geo-spatial big data in south korea. KSCE Journal of Civil Engineering, 20(7), 2893-2901. doi:10.1007/s12205-016-0504-7
Published
2020-04-24
How to Cite
LUBISHTANI, Milot et al.
Infrastructural Organization of Geospatial Data in The Global Level: A Case Study of Albanian Global Mapping Dataset.
Geosfera Indonesia, [S.l.], v. 5, n. 1, p. 106-126, apr. 2020.
ISSN 2614-8528.
Available at: <https://jurnal.unej.ac.id/index.php/GEOSI/article/view/16901>. Date accessed: 22 dec. 2024.
doi: https://doi.org/10.19184/geosi.v5i1.16901.
Section
Original Research Articles
