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Correction published on 22 April 2013, see Sensors 2013, 13(4), 5404-5405.

Open AccessArticle
Sensors 2012, 12(12), 17074-17093;

Geosensor Data Representation Using Layered Slope Grids

Database/Bioinformatics Lab, Chungbuk National University, Cheongju 361-763, Korea
Korea Institute of Science Technology and Information, 245 Daehangno, Yuseong, Daejeon 305-806, Korea
Department of Computer and Information Engineering, Kunsan National University, Kunsan 573-701, Korea
School of Computing and Information Science, University of Maine, Orono, 5711 Boardman Hall, Rm. 344, Orono, ME 04467, USA
Author to whom correspondence should be addressed.
Received: 17 October 2012 / Revised: 4 December 2012 / Accepted: 6 December 2012 / Published: 12 December 2012
(This article belongs to the Section Sensor Networks)
Full-Text   |   PDF [3257 KB, uploaded 21 June 2014]


Environmental monitoring applications are designed for supplying derived and often integrated information by tracking and analyzing phenomena. To determine the condition of a target place, they employ a geosensor network to get the heterogeneous sensor data. To effectively handle a large volume of sensor data, applications need a data abstraction model, which supports the summarized data representation by encapsulating raw data. For faster data processing to answer a user’s queries with representative attributes of an abstracted model, we propose such a data abstraction model, the Layered Slopes in Grid for Sensor Data Abstraction (LSGSA), which is based on the SGSA. In a single grid-based layer for each sensor type, collected data is represented by slope directional vectors in two layered slopes, such as height and surface. To answer a user query in a central monitoring server, LSGSA is used to reduce the time needed to extract event features from raw sensor data as a preprocessing step for interpreting the observed data. The extracted features are used to understand the current data trends and the progress of a detected phenomenon without accessing raw sensor data. View Full-Text
Keywords: sensor data abstraction; sensor data representation; geosensor network; slope grid; GIS; surface model sensor data abstraction; sensor data representation; geosensor network; slope grid; GIS; surface model
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Supplementary material

  • Correction

    A Correction was published on 22 April 2012 (PDF, 184 KB)

    There are four mistakes at the table derived from the (c) surface slope of Figure 4 in [1]. The direction numbers are derived according to (a) slope directions. The overall direction number should be changed from 6 to 4. The distinct direction number between the 1st and 2nd subcells should be changed from 0 to 8. The distinct direction number between the 2nd and 3rd subcells should be changed from 8 to 4. The distinct direction number between the 3rd and 4th subcells should be changed from 4 to 6. The authors would like to apologize for any inconvenience this may have caused to the readers of this journal.


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MDPI and ACS Style

Lee, Y.; Jung, Y.J.; Nam, K.W.; Nittel, S.; Beard, K.; Ryu, K.H. Geosensor Data Representation Using Layered Slope Grids. Sensors 2012, 12, 17074-17093.

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