Volume XL-2/W3
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 1-6, 2014
https://doi.org/10.5194/isprsarchives-XL-2-W3-1-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XL-2/W3, 1-6, 2014
https://doi.org/10.5194/isprsarchives-XL-2-W3-1-2014
© Author(s) 2014. This work is distributed under
the Creative Commons Attribution 3.0 License.

  21 Oct 2014

21 Oct 2014

COEVRAGE ESTIMATION OF GEOSENSOR IN 3D VECTOR ENVIRONMENTS

A. Afghantoloee1, S. Doodman1, F. Karimipour1, and M. A. Mostafavi2 A. Afghantoloee et al.
  • 1Department of Surveying and Geomatic Engineering, College of Engineering, University of Tehran, Tehran, Iran
  • 2Center for Research in Geomatics, Department of Geomatics, University of Laval, Quebec, Canada

Keywords: Geosensor deployment, WSNs, geosensor coverage, vector data model, DSM

Abstract. Sensor deployment optimization to achieve the maximum spatial coverage is one of the main issues in Wireless geoSensor Networks (WSN). The model of the environment is an imperative parameter that influences the accuracy of geosensor coverage. In most of recent studies, the environment has been modeled by Digital Surface Model (DSM). However, the advances in technology to collect 3D vector data at different levels, especially in urban models can enhance the quality of geosensor deployment in order to achieve more accurate coverage estimations. This paper proposes an approach to calculate the geosensor coverage in 3D vector environments. The approach is applied on some case studies and compared with DSM based methods.