Online image classification and analysis using OGC web processing service

Abstract

The online geoprocessing and analysis using state-of-the-art technology are offering automated analytical tools to a large group of users. This paper describes an online geoprocessing and analysis framework, which allows an inexperienced user to perform unsupervised classification of remote sensing data. The parallel computing based geoprocessing and analysis framework adopted in this work has been implemented using Free and Open Source Software for Geospatial (FOSS4G). Web Processing Service (WPS) based geoprocessing framework facilitates the deployment of unsupervised classification algorithm on the web in a standardized way. However, it is dynamic in nature to deploy other geoprocessing algorithms. The developed system describes how to process remote sensing data (Sentinel-2, Landsat-8, etc.) for classification and sharing the interoperable results in a distributed environment. To validate the classification results, a prototype architecture based on participatory GIS is developed for field data collection, accuracy assessment and online dissemination. The accuracy assessment (i.e., overall accuracy, Kappa coefficient) is performed to validate the derived classification results using collected field data.

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Acknowledgements

The first author would like to acknowledge MHRD, Govt. of India for providing the financial assistantship during the research and also want to extend his sincere thanks to IIRS/ISRO, Dehradun for their help in offering the resources in running the program. Thanks to Dr. S.K. Srivastav, dean (academics), IIRS/ISRO for their encouragement and technical support for this research study. Authors express their special thanks to Dr. A. Senthil Kumar, former Director IIRS/ISRO for sharing his overall suggestions to develop this web application.

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Correspondence to R. D. Garg.

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Communicated by: H. A. Babaie

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Singh, H., Garg, R.D. & Karnatak, H.C. Online image classification and analysis using OGC web processing service. Earth Sci Inform 12, 307–317 (2019). https://doi.org/10.1007/s12145-019-00378-z

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Keywords

  • Distributed GIS
  • Parallel computing
  • Unsupervised classification
  • Web processing service
  • Participatory GIS