GeoProcessing Workflow Models for Distributed Processing Frameworks
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10.5120/19794-1574 |
Shruti Thakker, Jhummarwala Abdul and M B Potdar. Article: GeoProcessing Workflow Models for Distributed Processing Frameworks. International Journal of Computer Applications 113(1):33-38, March 2015. Full text available. BibTeX
@article{key:article,
author = {Shruti Thakker and Jhummarwala Abdul and M. B. Potdar},
title = {Article: GeoProcessing Workflow Models for Distributed Processing Frameworks},
journal = {International Journal of Computer Applications},
year = {2015},
volume = {113},
number = {1},
pages = {33-38},
month = {March},
note = {Full text available}
}
Abstract
Geographic Information Systems (GIS) platforms are used to implement and deal with the massive spatial data, especially image data. Therefore, these platforms require high storage capacity and high computational power to process them. This paper aims of processing of Geodata using Distributed processing Frameworks. Large volume of Geodata cannot be processed using desktop GIS tools such as QGIS, ArcGIS, GRASS, OpenJUMP etc. Therefore, to handle and process on these types of large data, use of Hadoop Distributed processing framework needs to be deployed. GeoProcessing is a GIS operation used to manipulate spatial data. It is one of the original proposal in GIS development. Almost every GIS application is represented by a GeoProcessing Workflow. This paper explains the GeoProcessing Workflow for processing of image data. Also explains Hadoop Distributed File System (HDFS), MapReduce Programming Model and Yet Another Resource Negotiator (YARN) architecture, useful in large spatial data handling and analysis at fast rate.
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