• DocumentCode
    71532
  • Title

    Google Fusion Tables for Managing Soil Moisture Sensor Observations

  • Author

    Peng Yue ; Liangcun Jiang ; Lei Hu

  • Author_Institution
    State Key Lab. of Inf. Eng. in Surveying, Wuhan Univ., Wuhan, China
  • Volume
    7
  • Issue
    11
  • fYear
    2014
  • fDate
    Nov. 2014
  • Firstpage
    4414
  • Lastpage
    4421
  • Abstract
    Soil moisture plays a significant role in both water and energy cycles. It is important to manage and analyze in situ sensor observations of soil moisture due to its impacts on agricultural and hydrological processes. Google Fusion Tables (GFT) is a cloud computing database that provides a service on the Web for data management and integration. Using GFT for managing soil moisture sensor observations, it is possible to take advantages of GFT for collaborative management, on-the-fly visualization, and flexible integration and analysis. The Open Geospatial Consortium (OGC) sensor observation service (SOS) can provide real-time or near-real-time observations in an interoperable way. Combing SOS and GFT together can take the best of both. The paper investigates how GFT could be employed for managing, visualizing, and analyzing soil moisture sensor observations. It describes the design and implementation of a cloud-based SOS for managing soil moisture data using cloud computing databases. By storing sensor observations in GFT, the SOS service is scalable, and observations can be visualized and analyzed on demand. Challenges and approaches on the integration of GFT and SOS are discussed. A prototype service on sharing and managing soil moisture sensor observations is developed to demonstrate the applicability of the approach.
  • Keywords
    cloud computing; data analysis; data integration; data visualisation; geophysics computing; hydrological techniques; moisture; soil; visual databases; Google Fusion Tables; Open Geospatial Consortium sensor observation service; Web; agricultural process; cloud computing database; cloud-based sensor observation service; collaborative management; data integration; data management; energy cycle; flexible integration; hydrological process; in-situ sensor observations; near-real-time observations; on-the-fly visualization; prototype service; soil moisture sensor observation data; water cycle; Cloud computing; Data visualization; Databases; Geospatial analysis; Google; Monitoring; Soil moisture; Cloud computing; Google Fusion Tables (GFT); geospatial service; sensor observation service (SOS); soil moisture sensor observations;
  • fLanguage
    English
  • Journal_Title
    Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of
  • Publisher
    ieee
  • ISSN
    1939-1404
  • Type

    jour

  • DOI
    10.1109/JSTARS.2014.2353621
  • Filename
    6899622