Decomposition method of raster geographic data based on parallel computing

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 p...

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Bibliographic Details
Published in2012 20th International Conference on Geoinformatics pp. 1 - 4
Main Authors Zhibin Jin, Yingxia Pu, Jiechen Wang, Jingsong Ma, Gang Chen
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2012
Subjects
Computational modeling
computational transformation model
Equations
Mathematical model
raster geographic data
spatial computational domain
speedup
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Summary: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.
ISBN:1467311030
9781467311038
ISSN:2161-024X
DOI:10.1109/Geoinformatics.2012.6270298