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GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata

Author

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  • Sheoran Savita Kumari
  • Parmar Vinti

    (Department of Computer Science and Engineering, Indira Gandhi University Meerpur, Rewari, India)

Abstract

Developments in big data technology, wireless networks, Geographic information system (GIS) technology, and internet growth has increased the volume of data at an exponential rate. Internet users are generating data with every single click. Geospatial metadata is widely used for urban planning, map making, spatial data analysis, and so on. Scientific databases use metadata for computations and query processing. Cleaning of data is required for improving the quality of geospatial metadata for scientific computations and spatial data analysis. In this paper, we have designed a data cleaning tool named as GeoWebCln to remove useless data from geospatial metadata in a user-friendly environment using the Python console of QGIS Software.

Suggested Citation

  • Sheoran Savita Kumari & Parmar Vinti, 2022. "GeoWebCln: An Intensive Cleaning Architecture for Geospatial Metadata," Quaestiones Geographicae, Sciendo, vol. 41(1), pages 51-62, March.
    • Handle: RePEc:vrs:quageo:v:41:y:2022:i:1:p:51-62:n:7
    DOI: 10.2478/quageo-2022-0004
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    References listed on IDEAS

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    1. Zylshal Zylshal, 2020. "Topographic Correction of LAPAN-A3/LAPAN-IPB Multispectral Image: A Comparison of Five Different Algorithms," Quaestiones Geographicae, Sciendo, vol. 39(3), pages 33-45, September.
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