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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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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DOI: https://doi.org/10.1007/978-3-030-01440-7_11
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