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Decomposition method of raster geographic data based on parallel computing

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5 Author(s)
Zhibin Jin ; Sch. of Geographic & Oceanogr. Sci., Nanjing Univ., Nanjing, China ; Yingxia Pu ; Jiechen Wang ; Jingsong Ma
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The paper mainly studied decomposition method of raster geographic data based on parallel computing. Firstly, we structured computational transformation model of raster geographic data; Then, we designed a computational experiment to validate the computational transformation model and evaluate the performance of k-NN classification algorithm. Results of parallel computational experiment show that the model can be applied to decompose a heterogeneous spatial computational domain representation into a balanced set of computing tasks; the speedup performance of parallelizing k-NN classification algorithm based on the transformation model is superior to the results from traditional method.

Published in:

Geoinformatics (GEOINFORMATICS), 2012 20th International Conference on

Date of Conference:

15-17 June 2012

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