Editorial for the special issue: “Novel Solutions or Novel Approaches in Operational Research”
Drobne Samo (),
Dumičić Ksenija () and
Zadnik Lidija ()
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Drobne Samo: University of Ljubljana, Faculty of Civic and Geodetic Engineering,Ljubljana, Slovenia
Dumičić Ksenija: University of Zagreb, Faculty of Economics and Business,Zagreb, Croatia
Zadnik Lidija: Stirn University of Ljubljana, Biotechnical Faculty,Ljubljana, Slovenia
Business Systems Research, 2018, vol. 9, issue 2, 1-7
Background Determining the location, boundaries and areas of land properties accurately in the land cadastre is essential. The named data are provided using coordinates, acquired from field measurements. Since 2008, the Slovenian land cadastre claims positioning in the national realization of the ETRS89, so the GNSS use is practically indispensable. Objectives: Contrary to real-time, we can change parameters in GNSS post-processing. The aim of this paper is to simulate different measurement conditions for GNSS in order to determine how to acquire the best possible coordinates for further use in land area calculation. Methods/Approach: Simulations of obstacles near points followed the increasing of the cut-off angle. Furthermore, shortening the observation interval resulted in different occupation duration. The final condition evaluation for coordinate quality acquisition followed from fuzzy logic. Results: The results show that for short baselines, occupation duration is the most important factor in acquiring high quality coordinates and avoiding the multipath. Differences in coordinates from specific strategies can sometimes exceed the tolerance and evidently affect the area calculation. Conclusions: The findings confirm that only good measurement conditions lead to high quality coordinates and well-defined areas of land properties, which are the fundamental factor in relation to the issues of property valuation and assessing land taxes or rents.
Keywords: interdisciplinary research; operations research; risk and uncertainty; autoregressive models; machine learning; clustering comparison measure; multicriteria decision making; big data; location-allocation; fuzzy logic; hidden economy (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:bit:bsrysr:v:9:y:2018:i:2:p:1-7:n:1
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