Hadoop-based parallel algorithm for data mining in remote sensing images

Abstract

As a typical distributed parallel computing model, cloud computing can greatly reduce the execution time of computing tasks. Remote sensing image data mining, an important part of data mining, plays a significant role in meteorological analysis and earthquake prediction. By constructing a Hadoop cloud computing platform, this paper studies the Hadoop-based parallel algorithm for remote sensing image data mining. In accordance with the Hadoop distributed computing framework, the parallel algorithm for remote sensing image data mining is realized through data preprocessing, image feature extraction, and clustering analysis. The main work of this paper includes image preprocessing, Hadoop-based parallelization of remote sensing image feature extraction, and a Hadoop-based parallel algorithm for remote sensing image data mining.