Strategic Indicators Scenario Planning of the Geospatial Technology Development in the Defense Field Using by System Dynamic technique

Document Type : Original Article

Authors

1 Ms.c in GIS of Tehran University

2 Assistant Prof. in Tehran University

3 Assistant Prof. in Amirkaber University

Abstract

A spatial data infrastructure (SDI) is the technology, policies, standards and related activities necessary to acquire, distribute, use and preserve spatial data. An SDI is a coordinated series of agreements on technology standards, institutional arrangements, and policies that enable the discovery and use of geospatial information by users and for purposes other than those it was created for. Modeling and simulation can facilitate the development of SDI system in different level. This study aims to model the development of local SDI in defensive organization using the system dynamics technique. In this regard, the spatial data management parameters were identified and then three indicators; data security, spatial data standardization and participation units were determined. The indicators were simulated by Vensim software and model validation tests were done using by three categories of model Validation: Structural, structural-oriented behavior and behavior pattern tests. These models can be analyzing the system behavior in different conditions. The results show that the priority of the indicators for planning and policy-making are data security, participation units and then defensive spatial data standardization. At the end the important scenarios for each index and strategies to improve them were presented in the defensive organization in the medium term future.

Keywords


  •  

    • Abdolmajidi, E. Harrie, L. & Mansourian, A. (2016). The stock-flow model of spatial data infrastructure development refined by fuzzy logic, Springerplus,V.5.
    • Crompvoets, J. (2006). National spatial data clearinghouses: worldwide development and impact, Thesis (PhD), Wageningen University.
    • Daglous, N. (2009). Spatial Data Infrastructures: The SDI Cookbook, GSDI.
    • Dudley, R. & Soderquist, C. (2000). A simple example of how system dynamics modeling can clarify and improve discussion and modification of model structure the 129th Annual Meeting of the American Fisheries Society, 29 August-2 September 1999, Charlotte, North Carolina.
    • Grus, L., Crompvoets, J. & Bregt, A. (2006). Defining National Spatial Data Infrastructures as Complex Adaptive Systems. GSDI-9 Conference Proceedings, 6-November 2006, Santiago, Chile.
    • Kalantari, A. Oskouei, M. Modiri, A. Alesheikh, R. & Nekooie, M.A. (2018). An analysis of the national spatial data infrastructure of Iran, Survey Review, Taylor & Francis (https://doi.org/10.1080/00396265.2017.1420586).
    • Mansourian, A. Lubida, A. Pilesjo, P. Abdolmajidi, E. & LASSI, M. (2015). SDI planning using the system dynamics technique within a community of practice: lessons earnt from Tanzania, GIS Center, Department of Physical Geography and Ecosystem Science, Lund University, Sölvegatan 12, 22362.
    • Parida1.P. K. & Tripathi. S. (2018). Odisha Spatial Data Infrastructure (OSDI) – Its Data Model, Meta Data and Sharing Policy, ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume IV-5.
    • Rajabifard, A. (2008). Spatial Data Infrastructure for a Spatially Enabled Government and Society, Space for Geo-Information (RGI), Wageningen University, Wageningen, pp.11-22.
    • Willem, M.S. (2011). Developing Spatial Data Infrastructures for use in the Military, a dissertation of master, Department of Environment & Geographic Science, The Manchester Metropolitan University.
    • Williamson, I., Grant, D., & Rajabifard, A. (2009). Land administration and Spatial Data Infrastructures. FIG Working Week 2009 and GSDI-8.