Positional accuracy of cadastral maps digitized from the stable cadastre system
DOI:
https://doi.org/10.14311/CEJ.2024.02.0011Keywords:
cadastral mapping, positional accuracy, digital maps, stable cadastre system, land parcel, boundary refinement, geographic information systemAbstract
The accuracy of positional data in cadastral mapping is crucial for various technical activities within the cadastre and related decision-making processes. With digital maps becoming ubiquitous in cadastral operations, assessing the positional accuracy of cadastral maps digitized from stable cadastre systems has become essential. These maps, categorized as DKM and KMD, present different challenges in determining their overall positional accuracy. While DKM maps offer high accuracy, KMD maps, derived from stable cadastre systems, pose challenges due to their varied origins, including potential positional errors inherited from historical data.
This study proposes a methodology for assessing the positional accuracy of KMD maps by comparing digitized boundaries with actual field measurements. The evaluation considers factors such as cadastral area characteristics, available survey data, and the timing of digitization efforts. The study aims to categorize objects based on their positional accuracy by analysing shifts in boundary points and building positions.
Results from testing in selected cadastral areas reveal varying degrees of accuracy in KMD maps. While some areas demonstrate high accuracy, others exhibit significant positional inaccuracies, particularly in peripheral regions or linear parcels. The study suggests that areas outside municipal boundaries may require immediate remapping to ensure accuracy.
Overall, the findings highlight the importance of assessing and improving the positional accuracy of cadastral maps to enhance their utility in land management and decision-making processes. Further research in this area could focus on developing automated methods for detecting and correcting positional errors in digital cadastral maps.
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