SOLAP GIS in maritime research

• Autorzy: Drypczewski K. , Stepnowski A.
• Języki publikacji: EN

Abstrakty

EN

Multidimensional Geographical Information System is a system especially designed to acquire, distribute, analyze and visualize complicated spatio-temporal data. Modern Geographical Information System technology can provide easy-to-use, near real-time solutions to many problems from different areas of research. In the article, authors summarize recent works on Spatial Online Analytical Processing (SOLAP) and multidimensional Geographical Information System (GIS), discuss its capabilities and data structures used in spatio-temporal datasets, and propose its possible applications in maritime research.

Słowa kluczowe

EN

spatio-temporal GIS; multidimensional data; fish biomass estimation; AIS; tracking vessel movement

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2016
• Tom: Vol. 19
• Strony: 93--100
• Opis fizyczny: Bibliogr. 12 poz., rys.

Twórcy

autor

Drypczewski K.

• Gdansk University of Technology Faculty of Electronic and Informatics Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland

autor

Stepnowski A.

• Gdansk University of Technology Faculty of Electronic and Informatics Gabriela Narutowicza 11/12, 80-233 Gdańsk, Poland

Bibliografia

• [1] K. Drypczewski, Ł. Markiewicz, GIS solution for weather forecast data analysis, PhD Interdisciplinary Journal Vol. 3/2013, ISBN 978-83-60779-25-5.
• [2] K. Bruniecki, A. Stepnowski, M. Moszyński, Z. Łubniewski, K. Drypczewski, Ł. Markiewicz, M. Kulawiak, T. Bieliński, Using EO Satellite Data in Safe City and Coastal Zone Web-GIS, MIKON 2014 proceedings, Vol. 1, 67-70, 2014 Gdańsk, Poland, ISBN 978-83-931525-2-0.
• [3] O. Glorio, J. Mazón, I. Garrigós, J. Trujillo,A personalization process for spatial data warehouse development, Decision Support Systems, Vol. 52(4), 884-898, 2012.
• [4] N. Stefanovic, J. Han, K. Koperski, Object-Based Selective Materialization for Efficient Implementation of Spatial Data Cubes, IEEE Transactions on Knowledge and Data Engineering, Vol. 12(6), 2000.
• [5] S. Bimonte, V. Del Fatto, L. Paolino, M. Sebillo, G. Vitiello, A Visual Query Language for Spatial Data Warehouses, Geospatial Thinking, Lecture Notes in Geoinformation and Cartography, 43-60, 2010 Springer Berlin Heidelberg.
• [6] P. Baumann, Query Language Guide, 2013, https://ma.ellak.gr/documents/2014/12/rasdman-query-language-guide.pdf.
• [7] L. Leonardi et al., A general framework for trajectory data warehousing and visual OLAP, GeoInformatica, 18(2), 273-312, 2013.
• [8] D. Papadias, Y. Tao, P. Kalnis, J. Zhang, Indexing Spatio-Temporal Data Warehouses, Proceedings of 18th International Conference on Data Engineering, 166-175, 2002.
• [9] A. Harati-Mokhtaria, A. Wall, P. Brooks, J. Wang, Automatic Identification System (AIS): Data Reliability and Human Error Implications, Journal of Navigation, Vol. 60(3), 373-389, 2007.
• [10] A. Stepnowski, Zarys teorii i technika hydroakustycznych metod oceny siły celu i populacji ryb, Zeszyty Naukowe - Akademia Marynarki Wojennej im. Bohaterów Westerplatte, ISSN 0860-889X, 111 C, Gdynia 1991. In Polish.
• [11] Application of Remote Sensing to fisheries, Food and Agriculture Organization of the United Nations http://www.fao.org/docrep/003/t0355e/T0355E07.htm.
• [12] Shiotani S., Liu X.: Comparison of the Applied Car Navigation System and Developed Marine Navigational System. TransNav, the International Journal on Marine Navigation and Safety of Sea Transportation, Vol. 8, No. 1, pp. 27-32, 2014.

Uwagi

PL

Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)