Data-Parallel Method for Georeferencing of MODIS Level 1B Data Using Grid Computing

  • Yincui Hu
  • Yong Xue
  • Jiakui Tang
  • Shaobo Zhong
  • Guoyin Cai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3516)


Georeference is a basic function of remote sensing data processing. Geo-corrected remote sensing data is an important source data for Geographic Information Systems (GIS) and other location services. Large quantity remote sensing data were produced daily by satellites and other sensors. Georeferenceing of these data is time consumable and computationally intensive. To improve efficiency of processing, Grid technologies are applied. This paper focuses on the parallelization of the remote sensing data on a grid platform. According to the features of the algorithm, backwards-decomposition technique is applied to partition MODIS level 1B data. Firstly, partition the output array into evenly sized blocks using regular domain decomposition. Secondly, compute the geographical range of every block. Thirdly, find the GCPs triangulations contained in or intersect with the geographic range. Then extract block from original data in accordance with these triangulations. The extracted block is the data distributed to producer on Grid pool.


Geographic Information System Remote Sensing Geographic Information System Grid Computing Output Array 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


  1. 1.
    Aloisio, G., Cafaro, M.: A Dynamic Earth Observation System. Parallel Computing 29, 1357–1362 (2003)CrossRefGoogle Scholar
  2. 2.
    Aloisio, G., Cafaro, M., Epicoco, I., Quarta, G.: A Problem Solving Environment for Remote Sensing Data Processing. In: Proceeding of ITCC 2004: International Conference on Information Technology: Coding and Computing, vol. 2, pp. 56–61. IEEE Computer Society, Los Alamitos (2004)CrossRefGoogle Scholar
  3. 3.
    Cai, G.Y., Xue, Y., Tang, J.K., Wang, J.Q., Wang, Y.G., Luo, Y., Hu, Y.C., Zhong, S.B., Sun, X.S.: Experience of Remote Sensing Information Modelling with Grid Computing. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3039, pp. 989–996. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  4. 4.
    Cannataro, M.: Clusters and Grids for Distributed and Parallel Knowledge Discovery. In: Williams, R., Afsarmanesh, H., Bubak, M., Hertzberger, B. (eds.) HPCN-Europe 2000. LNCS, vol. 1823, pp. 708–716. Springer, Heidelberg (2000)CrossRefGoogle Scholar
  5. 5.
    Hu, Y.C., Xue, Y., Wang, J.Q., Sun, X.S., Cai, G.Y., Tang, J.K., Luo, Y., Zhong, S.B., Wang, Y.G., Zhang, A.J.: Feasibility Study of Geo-spatial Analysis Using Grid Computing. In: Bubak, M., van Albada, G.D., Sloot, P.M.A., Dongarra, J. (eds.) ICCS 2004. LNCS, vol. 3039, pp. 956–963. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  6. 6.
    Lanthier, M., Nussbaurm, D.: Parallel Implementation of Geometric Shortest Path Algorithms. Parallel Computing 29, 1445–1479 (2003)CrossRefGoogle Scholar
  7. 7.
    Pouchard, L., Cinquini, L., Drach, B., Middleton, D., Bernholdt, D., Chanchio, K., Foster, I., Nefedova, V., Brown, D., Fox, P., Garcia, J., Strand, G., Williams, D., Chervenak, A., Kesselman, C., Shoshani, A., Sim, A.: An Ontology for Scientific Information in a Grid Environment: The Earth System grid. In: 3rd IEEE/ACM International Symposium on Cluster Computing and the GRID, pp. 626–632. IEEE Computer Society, Los Alamitos (2003)CrossRefGoogle Scholar
  8. 8.
    Roros, D.-K.D., Armstrong, M.P.: Using Linda to Compute Spatial Autocorrelation in Parallel. Computers & Geosciences 22, 425–432 (1996)CrossRefGoogle Scholar
  9. 9.
    Roros, D.-K.D., Armstrong, M.P.: Experiments in the Identification of Terrain Features Using a PC-Based Parallel Computer. Photogrammetric Engineering & Remote Sensing 64, 135–142 (1998)Google Scholar
  10. 10.
    Wang, S., Armstrong, M.P.: A Quadtree Approach to Domain Decomposition for Spatial Interpolation in Grid Computing Environments. Parallel Computing 29, 1481–1504 (2003)CrossRefGoogle Scholar
  11. 11.
    Wang, J., Xue, Y., Guo, H.: A Spatial Information Grid Supported Prototype Telegeoprocessing System. In: Proceedings of 2003 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2003) held in Toulouse, France, July 21-25, vol. 1, pp. 345–347 (2003)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yincui Hu
    • 1
  • Yong Xue
    • 1
    • 2
  • Jiakui Tang
    • 1
  • Shaobo Zhong
    • 1
  • Guoyin Cai
    • 1
  1. 1.State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Institute of Remote Sensing ApplicationsChinese Academy of SciencesBeijingChina
  2. 2.Department of ComputingLondon Metropolitan UniversityLondonUK

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