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Investigating Semi-Automated Cadastral Boundaries Extraction from Airborne Laser Scanned Data

Author

Listed:
  • Xianghuan Luo

    (Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, HongKong, China)

  • Rohan Mark Bennett

    (Swinburne Business School, Swinburne University of Technology, Hawthorn VIC 3122, Australia
    Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500AE, The Netherlands)

  • Mila Koeva

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500AE, The Netherlands)

  • Christiaan Lemmen

    (Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500AE, The Netherlands
    Dutch Cadastre, Land Registry and Mapping Agency, Apeldoorn 7300GH, The Netherlands)

Abstract

Many developing countries have witnessed the urgent need of accelerating cadastral surveying processes. Previous studies found that large portions of cadastral boundaries coincide with visible physical objects, namely roads, fences, and building walls. This research explores the application of airborne laser scanning (ALS) techniques on cadastral surveys. A semi-automated workflow is developed to extract cadastral boundaries from an ALS point clouds. Firstly, a two-phased workflow was developed that focused on extracting digital representations of physical objects. In the automated extraction phase, after classifying points into semantic components, the outline of planar objects such as building roofs and road surfaces were generated by an α-shape algorithm, whilst the centerlines delineatiation approach was fitted into the lineate object—a fence. Afterwards, the extracted vector lines were edited and refined during the post-refinement phase. Secondly, we quantitatively evaluated the workflow performance by comparing results against an exiting cadastral map as reference. It was found that the workflow achieved promising results: around 80% completeness and 60% correctness on average, although the spatial accuracy is still modest. It is argued that the semi-automated extraction workflow could effectively speed up cadastral surveying, with both human resources and equipment costs being reduced

Suggested Citation

  • Xianghuan Luo & Rohan Mark Bennett & Mila Koeva & Christiaan Lemmen, 2017. "Investigating Semi-Automated Cadastral Boundaries Extraction from Airborne Laser Scanned Data," Land, MDPI, vol. 6(3), pages 1-23, September.
    • Handle: RePEc:gam:jlands:v:6:y:2017:i:3:p:60-:d:110796
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    References listed on IDEAS

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    1. Bruce, John W., 1998. "Review Of Tenure Terminology," Tenure Briefs 12814, University of Wisconsin-Madison, Land Tenure Center.
    2. -, 2000. "Administración ambiental," Sede de la CEPAL en Santiago (Estudios e Investigaciones) 35149, Naciones Unidas Comisión Económica para América Latina y el Caribe (CEPAL).
    3. Dale, Peter & McLaughlin, John, 2000. "Land Administration," OUP Catalogue, Oxford University Press, number 9780198233909.
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    Cited by:

    1. Julia Velastegui-Cáceres & Víctor M. Rodríguez-Espinosa & Oswaldo Padilla-Almeida, 2020. "Urban Cadastral Situation in Ecuador: Analysis to Determine the Degree of Proximity of the Cadastral Systems to the 3D Cadastral Model," Land, MDPI, vol. 9(10), pages 1-20, September.
    2. Dwi Budi Martono & Trias Aditya & Subaryono Subaryono & Prijono Nugroho, 2021. "The Legal Element of Fixing the Boundary for Indonesian Complete Cadastre," Land, MDPI, vol. 10(1), pages 1-24, January.

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