Next Article in Journal
Fire Data as Proxy for Anthropogenic Landscape Change in the Yucatán
Previous Article in Journal
Informal Urban Green Space: Residents’ Perception, Use, and Management Preferences across Four Major Japanese Shrinking Cities
Article Menu
Issue 3 (September) cover image

Export Article

Open AccessArticle
Land 2017, 6(3), 60; doi:10.3390/land6030060

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

1
Department of Land Surveying and Geo-informatics, The Hong Kong Polytechnic University, HongKong, China
2
Swinburne Business School, Swinburne University of Technology, Hawthorn VIC 3122, Australia
3
Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, Enschede 7500AE, The Netherlands
4
Dutch Cadastre, Land Registry and Mapping Agency, Apeldoorn 7300GH, The Netherlands
*
Author to whom correspondence should be addressed.
Received: 25 July 2017 / Revised: 13 August 2017 / Accepted: 28 August 2017 / Published: 4 September 2017
View Full-Text   |   Download PDF [16413 KB, uploaded 11 September 2017]   |  

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 View Full-Text
Keywords: cadastral survey; boundary mapping; feature extraction; semi-automation; point cloud cadastral survey; boundary mapping; feature extraction; semi-automation; point cloud
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Luo, X.; Bennett, R.M.; Koeva, M.; Lemmen, C. Investigating Semi-Automated Cadastral Boundaries Extraction from Airborne Laser Scanned Data. Land 2017, 6, 60.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Land EISSN 2073-445X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top