485
Views
13
CrossRef citations to date
0
Altmetric
Original Articles

Optimizing an index with spatiotemporal patterns to support GEOSS Clearinghouse

, , , &
Pages 1459-1481 | Received 25 Jul 2013, Accepted 10 Feb 2014, Published online: 18 Mar 2014

References

  • Achakeev, D., Seeger, B., and Widmayer, P., 2012. Sort-based query-adaptive loading of R-trees. In: Proceedings of the 21st ACM international conference on information and knowledge management, New York, NY, 2080–2084. doi:10.1145/2396761.2398577
  • Beckmann, N., et al., 1990. The R*-tree: an efficient and robust access method for points and rectangles. In: Proceedings of the 1990 ACM SIGMOD international conference on management of data, New York, NY, 322–331. doi:10.1145/93597.98741
  • Bercken, J.V.d., et al., 2001. XXL – a library approach to supporting efficient implementations of advanced database queries. In: Proceedings of the 27th international conference on very large data bases, San Francisco, CA, 39–48.
  • Bunt, R.B., et al., 1999. Achieving load balance and effective caching in clustered Web servers. In: Proceedings of the 4th international web caching work, San Diego, CA, 159–169.
  • Buyya, R., et al., 2009. Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Generation Computer Systems, 25 (6), 599–616. doi:10.1016/j.future.2008.12.001
  • Cary, A., et al., 2009. Experiences on processing spatial data with MapReduce. In: Proceedings of the 21st international conference on scientific and statistical database management, Berlin, 302–319. doi:10.1007/978-3-642-02279-1_24
  • Dean, J. and Ghemawat, S., 2008. MapReduce: simplified data processing on large clusters. Communications of the ACM – 50th Anniversary Issue, 51 (1), 107–113. doi:10.1145/1327452.1327492
  • García Martín, R., et al., 2013. An OLS regression model for context-aware tile prefetching in a web map cache. International Journal of Geographical Information Science, 27 (3), 614–632. doi: 10.1080/13658816.2012.721555
  • GEOSS, 2013. The GEOSS common infrastructure [online]. Available from: http://www.earthobservations.org/gci_gci.shtml [Accessed 14 June 2013].
  • Gui, Z., et al., 2013. A performance, semantic and service quality-enhanced distributed search engine for improving geospatial resource discovery. International Journal of Geographical Information Science, 27 (6), 1109–1132. doi:10.1080/13658816.2012.739692
  • Güting, R.H., 1994. An introduction to spatial database systems. The VLDB Journal, 3 (4), 357–399. doi:10.1007/BF01231602
  • Guttman, A., 1984. R-trees: a dynamic index structure for spatial searching. In: Proceedings of the ACM SIGMOD international conference on management of data, Boston, MA, 47–57.
  • Haverkort, H. and Walderveen, F.V., 2008. Four-dimensional Hilbert curves for R-trees. Journal of Experimental Algorithmics (JEA), 16 (3.4). doi:10.1145/1963190.2025380
  • Horvitz, E., et al., 1998. The Lumiere project: Bayesian user modeling for inferring the goals and needs of software users. In: Proceedings of the fourteenth conference on uncertainty in artificial intelligence, Madison, WI, 256–265.
  • Huang, C.-Y. and Liang, S.H.L., 2013. LOST-Tree: a spatio-temporal structure for efficient sensor data loading in a sensor web browser. International Journal of Geographical Information Science, 27 (6), 1190–1209. doi:10.1080/13658816.2012.743663
  • Huang, H., et al., 2011. An SVG-based method to support spatial analysis in XML/GML/SVG-based WebGIS. International Journal of Geographical Information Science, 25 (10), 1561–1574. doi:10.1080/13658816.2010.532133
  • Huang, Q., et al., 2013. Using adaptively coupled models and high-performance computing for enabling the computability of dust storm forecasting. International Journal of Geographical Information Science, 27 (4), 765–784. doi:10.1080/13658816.2012.715650
  • Informix, 2003. IBM informix R-tree index user’s guide [online]. IBM. Available from: www.informix.com.ua/doc/9.40/ct1tana.pdf [Accessed 14 June 2013].
  • Kamel, I. and Faloutsos, C., 1992. Parallel R-trees. In: Proceedings of the ACM SIGMOD international conference on management of data, San Diego, CA, 195–204. doi:10.1145/141484.130315
  • Kamel, I. and Faloutsos, C., 1993. Hilbert R-Tree: an improved R-Tree using fractals. In: Proceedings of the 20th international conference on very large databases, Santiago de, 500–509.
  • Kang, Y.-K., Kim, K.-C., and Kim, Y.-S., 2001. Probability-based tile pre-fetching and cache replacement algorithms for web geographical information systems. In: Proceedings of the 5th East European conference on advances in databases and information systems, London, 127–140.
  • Kothuri, R., Hanckel, R., and Yalamanchi, A., 2008. Using Oracle extensibility framework for supporting temporal and spatio-temporal applications. In: 15th international symposium on temporal representation and reasoning, Montréal.
  • Kothuri, R.K.V., Ravada, S., and Abugov, D., 2002. Quad-tree and R-tree indexes in oracle spatial: a comparison using GIS data. In: Proceedings of the 2002 ACM SIGMOD international conference on management of data, New York, NY, 546–557. doi:10.1145/564691.564755
  • Li, R., et al., 2012. A prefetching model based on access popularity for geospatial data in a cluster-based caching system. International Journal of Geographical Information Science, 26 (10), 1831–1844. doi:10.1080/13658816.2012.659184
  • Li, Z., et al., 2011. An optimized framework for seamlessly integrating OGC web services to support geospatial sciences. International Journal of Geographical Information Science, 25 (4), 595–613. doi:10.1080/13658816.2010.484811
  • Liu, K., et al., 2011. The GEOSS Clearinghouse high performance search engine. In: Proceedings of 2011 19th international conference on geoinformatics, Shanghai, 1–4.
  • Mountrakis, G. and Gunson, K., 2009. Multi‐scale spatiotemporal analyses of moose–vehicle collisions: a case study in northern Vermont. International Journal of Geographical Information Science, 23 (11), 1389–1412. doi:10.1080/13658810802406132
  • Nah, F.F.-H., 2004. A study on tolerable waiting time: how long are web users willing to wait? Behaviour & Information Technology, 23 (3), 153–163. doi:10.1080/01449290410001669914
  • Nativi, S.M.C. and Pearlman, J., 2013. Earth science infrastructures interoperability: the brokering approach. Journal of Selected Topics in Applied Earth Observation and Remote Sensing, 6 (3), 1118–1129.
  • Nebert, D., Whiteside, A., and Vretanos, P., 2007. OpenGIS catalog services specification, Version 2.0.2 [online]. OGC. Available from: https://portal.opengeospatial.org/modules/admin/license_agreement.php?SuppressHeaders=0&access_license_id=3&target=http://portal.opengeospatial.org/files/%3fartifact_id=20555 [Accessed 14 June 2013].
  • Pfoser, D., Jensen, C.S., and Theodoridis, Y., 2000. Novel approaches to the indexing of moving object trajectories. In: Proceedings of the 26th international conference on very large data bases, Cairo, 395–406.
  • PostGIS, 2013. PostGIS 2.0.0 manual [online]. PostGIS. Available from: http://postgis.refractions.net/documentation/manual-2.0 [Accessed 14 June 2013].
  • Sagan, H., 1994. Space-filling curves. Vol. 18. New York: Springer-Verlag.
  • Schnitzer, B. and Leutenegger, S.T., 1999. Master-client R-trees: a new parallel R-tree architecture. In: Eleventh international conference on scientific and statistical database management, 68–77. doi:10.1109/SSDM.1999.787622
  • Sedda, L., et al., 2011. Spatio-temporal analysis of tree height in a young cork oak plantation. International Journal of Geographical Information Science, 25 (7), 1083–1096. doi:10.1080/13658816.2010.517534
  • Sellis, T., Roussopoulos, N., and Faloutsos, C., 1987. The R+-tree: a dynamic index for multi-dimensional objects. In: Proceedings of the 13th international conference on very large data bases, Brighton, 507–518.
  • Tao, Y., Papadias, D., and Sun, J., 2003. The TPR*-tree: an optimized spatio-temporal access method for predictive queries. In: Proceedings of the 29th international conference on very large data bases, Berlin, 790–801.
  • Theodoridis, Y., et al., 1996. Spatio-temporal indexing for large multimedia applications. In: Proceedings of the IEEE conference on multimedia computing and systems, Hiroshima, 441–448.
  • Tobler, W.R., 1970. A computer movie simulating urban growth in the Detroit region. Economic Geography, 46, 234–240. doi:10.2307/143141
  • USGS, 2011. Earthquake Hazards program [online]. Available from: http://earthquake.usgs.gov/earthquakes/eqinthenews/2011/usb0006bqc [Accessed 14 June 2013].
  • Wang, B., et al., 1999. Parallel R-tree search algorithm on DSVM. In: Proceedings of 6th international conference on database systems for advanced applications, Kyoto, 237–244. doi: 10.1109/DASFAA.1999.765757
  • Whitehouse, 2012. Obama administration unveils ‘BIG DATA’ initiative: announces $200 million in new R&D investments. Whitehouse. Available from: http://www.whitehouse.gov/sites/default/files/microsites/ostp/big_data_press_release_final_2.pdf [Accessed 14 June 2013].
  • Xu, X., Han, J., and Lu, W., 1990. RT-Tree: an improved R-Tree indexing structure for temporal spatial databases. In: Proceedings of international symposium on spatial data handling, Zurich, 1040–1049.
  • XXL, 2013. eXtensible and fleXible library, version 2.0 [online]. eXtensible and fleXible Library. Available from: https://code.google.com/p/xxl/ [Accessed 14 June 2013].
  • Yang, C., et al., 2011a. Spatial cloud computing: how can the geospatial sciences use and help shape cloud computing? International Journal of Digital Earth, 4 (4), 305–329. doi:10.1080/17538947.2011.587547
  • Yang, C., et al., 2014. Spatial cloud computing: a practical approach. Boca Raton, FL: CRC Press/Taylor & Francis, 333p. ISBN: 978–1466593169
  • Yang, C., et al., 2010. Geospatial cyberinfrastructure: past, present and future. Computers, Environment and Urban Systems, 34 (4), 264–277. doi: 10.1016/j.compenvurbsys.2010.04.001
  • Yang, C., et al., 2011b. Using spatial principles to optimize distributed computing for enabling the physical science discoveries. Proceedings of the National Academy of Sciences, 108 (14), 5498–5503. doi: 10.1073/pnas.0909315108
  • Zhang, T. and Tsou, M.-H., 2009. Developing a grid-enabled spatial Web portal for Internet GIServices and geospatial cyberinfrastructure. International Journal of Geographical Information Science, 23 (5), 605–630. doi: 10.1080/13658810802698571
  • Zheng, Y., Xie, X., and Ma, W.Y., 2010. GeoLife: a collaborative social networking service among user, location and trajectory. Proceedings of IEEE Data Engineering Bulletin, 33 (2), 32–39.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.