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
Link To Document :
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