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Seasonal Hydrological Loading from GPS Observed Data Across Contiguous United States Using Integrated Apache Hadoop Framework

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Advances in Remote Sensing and Geo Informatics Applications (CAJG 2018)

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Abstract

The study examined the relationship between seasonal vertical loading deformation and seasonal hydrological loading from precipitation specified as rain and snow. The vertical loading deformation is characterized by time-series estimated from continuous Global Positioning System (GPS) network across the contiguous United States for a timeframe of 48 months (January 1st, 2013 to December 31st, 2016). The data processing used custom-built R scripts and spatial libraries that were integrated with Hive framework which is a data warehouse extension of Apache Hadoop that is used as a database query interface. The relationships of vertical displacement were explored by visualization techniques such as spatial maps and wavelet coherence plots.

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References

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Author information

Authors and Affiliations

  1. School of Earth, Environment and Society, Bowling Green State University, Bowling Green, OH, 43403, USA

    Pece V. Gorsevski, Yuning Fu, Kurt S. Panter, Jeffrey Snyder & Asanga M. Ramanayake

Authors
  1. Pece V. Gorsevski
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  2. Yuning Fu
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  3. Kurt S. Panter
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  4. Jeffrey Snyder
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  5. Asanga M. Ramanayake
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Corresponding author

Correspondence to Pece V. Gorsevski .

Editor information

Editors and Affiliations

  1. Schmid College of Science and Technology, Chapman University, Orange, CA, USA

    Hesham M. El-Askary

  2. Korea Institute of Geoscience and Mineral Resources, Daejeon, Korea (Republic of)

    Saro Lee

  3. Jet Propulsion Laboratory, Caltech, Pasadena, CA, USA

    Essam Heggy

  4. University of Technology Sydney, Sydney, NSW, Australia

    Biswajeet Pradhan

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Gorsevski, P.V., Fu, Y., Panter, K.S., Snyder, J., Ramanayake, A.M. (2019). Seasonal Hydrological Loading from GPS Observed Data Across Contiguous United States Using Integrated Apache Hadoop Framework. In: El-Askary, H., Lee, S., Heggy, E., Pradhan, B. (eds) Advances in Remote Sensing and Geo Informatics Applications. CAJG 2018. Advances in Science, Technology & Innovation. Springer, Cham. https://doi.org/10.1007/978-3-030-01440-7_11

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