958
Views
8
CrossRef citations to date
0
Altmetric
Articles

DAPR-tree: a distributed spatial data indexing scheme with data access patterns to support Digital Earth initiatives

, , , , , & ORCID Icon show all
Pages 1656-1671 | Received 17 Jan 2020, Accepted 02 Jun 2020, Published online: 12 Jun 2020

References

  • Aji, A., F. Wang, H. Vo, R. Lee, Q. Liu, X. Zhang, and J. Saltz. 2013. “Hadoop Gis: A High Performance Spatial Data Warehousing System Over Mapreduce.” Proceedings of the VLDB Endowment 6 (11): 1009–1020. doi: 10.14778/2536222.2536227
  • Beckmann, N., H. P. Kriegel, R. Schneider, and B. Seeger. 1990. “The R*-tree: An Efficient and Robust Access Method for Points and Rectangles.” Proceedings of the 1990 ACM SIGMOD International Conference on Management of data, 322–331. Chicago.
  • Bereuter, P., and R. Weibel. 2013. “Real-time Generalization of Point Data in Mobile and Web Mapping Using Quadtrees.” Cartography and Geographic Information Science 40 (4): 271–281. doi: 10.1080/15230406.2013.779779
  • Boyd, D., and K. Crawford. 2011. “Six Provocations for Big Data.” In A Decade in Internet Time: Symposium on the Dynamics of the Internet and Society. Oxford: Oxford Internet Institute. doi:10.2139/ssrn.1926431.
  • Butterfield, M. L., J. S. Pearlman, and S. C. Vickroy. 2008. “A System-of-Systems Engineering Geoss: Architectural Approach.” IEEE Systems Journal 2 (3): 321–332. doi: 10.1109/JSYST.2008.925973
  • Cary, A., Y. Yesha, M. Adjouadi, and N. Rishe. 2010. “Leveraging Cloud Computing in Geodatabase Management.” Granular Computing (GrC), IEEE International Conference, 2010, 73–78. IEEE.
  • Christian, E. J. 2008. “GEOSS Architecture Principles and the GEOSS Clearinghouse.” IEEE Systems Journal 2 (3): 333–337. doi: 10.1109/JSYST.2008.925977
  • Feng, B., Q. Zhu, M. Liu, Y. Li, J. Zhang, X. Fu, Y. Zhou, M. Li, H. He, and W. Yang. 2018. “An Efficient Graph-Based Spatio-Temporal Indexing Method for Task-Oriented Multi-Modal Scene Data Organization.” ISPRS International Journal of Geo-Information 7 (9): 371. doi: 10.3390/ijgi7090371
  • Gaede, V., and O. Günther. 1998. “Multidimensional Access Methods.” ACM Computing Surveys (CSUR) 30 (2): 170–231. doi: 10.1145/280277.280279
  • Guo, H., L. Zhang, and L. Zhu. 2015. “Earth Observation Big Data for Climate Change Research.” Advances in Climate Change Research 6 (2): 108–117. doi: 10.1016/j.accre.2015.09.007
  • Guttman, A. 1984. “R-Trees: A Dynamic Index Structure for Spatial Searching.” Proceedings of the ACM SIGMOD international conference on management of data, 47–57. Boston.
  • Hadjieleftheriou, M., G. Kollios, P. Bakalov, and V. J. Tsotras. 2005. “Complex Spatio-temporal Pattern Queries.” Proceedings of the 31st international conference on Very large data bases, 877–888. VLDB Endowment.
  • Hoel, E. G., and H. Samet. 1994. Performance of Data-Parallel Spatial Operations. Very Large Data Bases, 156–167.
  • Hsu, Y. T., Y. C. Pan, L. Y. Wei, W. C. Peng, and W. C. Lee. 2012. “Key Formulation Schemes for Spatial Index in Cloud Data Managements.” Mobile Data Management (MDM), IEEE 13th International Conference, 2012, 21–26, IEEE.
  • Hu, F., C. Yang, Y. Jiang, Y. Li, W. Song, D. Q. Duffy, J. L. Schnase, and T. Lee. 2020. “A Hierarchical Indexing Strategy for Optimizing Apache Spark with HDFS to Efficiently Query Big Geospatial Raster Data.” International Journal of Digital Earth 13 (3): 410–428. doi: 10.1080/17538947.2018.1523957
  • Huang, C. S., M. F. Tsai, P. H. Huang, L. D. Su, and K. S. Lee. 2017. “Distributed Asteroid Discovery System for Large Astronomical Data.” Journal of Network and Computer Applications 93: 27–37. doi: 10.1016/j.jnca.2017.03.013
  • Huang, Q., C. Yang, K. Benedict, A. Rezgui, J. Xie, J. Xia, and S. Chen. 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.
  • Huang, Q., C. Yang, D. Nebert, K. Liu, and H. Wu. 2010. “Cloud Computing for Geosciences: Deployment of GEOSS Clearinghouse on Amazon’s EC2.” In ACM Sigspatial International Workshop on High PERFORMANCE and Distributed Geographic Information Systems. Vol. 281, 35–38. San Jose, CA: ACM.
  • Ji, C., Z. Li, W. Qu, Y. Xu, and Y. Li. 2014. “Scalable Nearest Neighbor Query Processing Based on Inverted Grid Index.” Journal of Network and Computer Applications 44: 172–182. doi: 10.1016/j.jnca.2014.05.010
  • Kamel, I., and C. Faloutsos. 1992. “Parallel R-Trees.” In: Proceedings of the ACM SIGMOD International Conference on Management of Data, 195–204. San Diego. doi:10.1145/141484.130315.
  • LaValle, S., E. Lesser, R. Shockley, M. S. Hopkins, and N. Kruschwitz. 2011. “Big Data, Analytics and the Path From Insights to Value.” MIT Sloan Management Review 52 (2): 21.
  • Li, Z., M. E. Hodgson, and W. Li. 2018. “A General-Purpose Framework for Parallel Processing of Large-Scale LiDAR Data.” International Journal of Digital Earth 11 (1): 26–47. doi: 10.1080/17538947.2016.1269842
  • Li, J., C. Li, F. Zhu, C. Song, and J. Wu. 2013. “Spatiotemporal Pattern of Urbanization in Shanghai, China Between 1989 and 2005.” Landscape Ecology 28 (8): 1545–1565. doi: 10.1007/s10980-013-9901-1
  • Mehrotra, H., B. Majhi, and P. Gupta. 2010. “Robust Iris Indexing Scheme Using Geometric Hashing of SIFT Keypoints.” Journal of Network and Computer Applications 33 (3): 300–313. doi: 10.1016/j.jnca.2009.12.005
  • Mondal, A., M. Kitsuregawa, B. C. Ooi, and K. Tan. 2001. “R-Tree-Based Data Migration and Self-Tuning Strategies in Shared-Nothing Spatial Databases.” Advances in Geographic Information Systems. 28–33.
  • Mountrakis, G., and K. Gunson. 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.
  • Nam, B., and A. Sussman. 2005. “Spatial Indexing of Distributed Multidimensional Datasets.” In CCGrid 2005. IEEE International Symposium on Cluster Computing and the Grid, 2005. Vol. 2, 743–750.
  • Nativi, S., P. Mazzetti, M. Santoro, F. Papeschi, M. Craglia, and O. Ochiai. 2015. “Big Data Challenges in Building the Global Earth Observation System of Systems.” Environmental Modelling & Software 68: 1–26. doi: 10.1016/j.envsoft.2015.01.017
  • Papadopoulos, A., and D. Katsaros. 2011. “A-Tree: Distributed Indexing of Multidimensional Data for Cloud Computing Environments.” In 2011 IEEE Third International Conference on Cloud Computing Technology and Science, 407–414. IEEE.
  • Schnitzer, B., and S. T. Leutenegger. 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.
  • Siddiqa, A., I. A. T. Hashem, I. Yaqoob, M. Marjani, S. Shamshirband, A. Gani, and F. Nasaruddin. 2016. “A Survey of Big Data Management: Taxonomy and State-of-the-Art.” Journal of Network and Computer Applications 71: 151–166. doi: 10.1016/j.jnca.2016.04.008
  • Tang, M., Y. Yu, Q. M. Malluhi, M. Ouzzani, and W. G. Aref. 2016. “Locationspark: A Distributed in-Memory Data Management System for Big Spatial Data.” Proceedings of the VLDB Endowment 9 (13): 1565–1568. doi: 10.14778/3007263.3007310
  • Tucker, D. M. 1993. “Spatial Sampling of Head Electrical Fields: The Geodesic Sensor Net.” Electroencephalography and Clinical Neurophysiology 87 (3): 154–163. doi: 10.1016/0013-4694(93)90121-B
  • Van Groenigen, J. W., and A. Stein. 1998. “Constrained Optimization of Spatial Sampling Using Continuous Simulated Annealing.” Journal of Environmental Quality 27 (5): 1078–1086. doi: 10.2134/jeq1998.00472425002700050013x
  • Wan, S., Y. Zhao, T. Wang, Z. Gu, Q. H. Abbasi, and K. K. R. Choo. 2019. “Multi-Dimensional Data Indexing and Range Query Processing Via Voronoi Diagram for Internet of Things.” Future Generation Computer Systems 91: 382–391. doi: 10.1016/j.future.2018.08.007
  • Wang, L., B. Chen, and Y. Liu. 2013. “Distributed Storage and Index of Vector Spatial Data Based on HBase.” International Conference on Geoinformatics, 1–5. IEEE.
  • Wang, B., H. Horinokuchi, K. Kaneko, and A. Makinouchi. 1999. “Parallel R-Tree Search Algorithm on DSVM.” In: Proceedings of 6th International Conference on Database Systems for Advanced Applications, 237–244. Kyoto. doi: 10.1109/DASFAA.1999.765757.
  • Wang, J. F., A. Stein, B. B. Gao, and Y. Ge. 2012. “A Review of Spatial Sampling.” Spatial Statistics 2: 1–14. doi: 10.1016/j.spasta.2012.08.001
  • Wang, F., X. Wang, W. Cui, X. Xiao, Y. Zhou, and J. Li. 2016. “Distributed Retrieval for Massive Remote Sensing Image Metadata on Spark.” In 2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), 5909–5912. IEEE.
  • Withee, G. W., D. B. Smith, and M. B. Hales. 2004. “Progress in Multilateral Earth Observation Cooperation: Ceos, Igos and the Ad Hoc Group on Earth Observations.” Space Policy 20 (1): 37–43. doi: 10.1016/j.spacepol.2003.12.001
  • Wu, X., X. Zhu, G. Q. Wu, and W. Ding. 2014. “Data Mining with Big Data.” IEEE Transactions on Knowledge and Data Engineering 26 (1): 97–107. doi: 10.1109/TKDE.2013.109
  • Xia, J., C. Yang, Z. Gui, K. Liu, and Z. Li. 2014. “, Optimizing an Index with Spatiotemporal Patterns to Support GEOSS Clearinghouse.” International Journal of Geographical Information Science 28 (7): 1459–1481. doi: 10.1080/13658816.2014.894195
  • Xia, J., C. Yang, and Q. Li. 2018. “Using Spatiotemporal Patterns to Optimize Earth Observation Big Data Access: Novel Approaches of Indexing, Service Modeling and Cloud Computing.” Computers, Environment and Urban Systems 72: 191–203. doi: 10.1016/j.compenvurbsys.2018.06.010
  • Yang, C., H. Wu, Q. Huang, Z. Li, and J. Li. 2011. “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.
  • Yu, J., J. Wu, and M. Sarwat. 2015. “Geospark: A Cluster Computing Framework for Processing Large-Scale Spatial Data.” In Proceedings of the 23rd SIGSPATIAL International Conference on Advances in Geographic Information Systems, 70. ACM.

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.