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

Xianghuan Luo,Christiaan Lemmen,Mila Koeva,Rohan Mark Bennett

doi:10.3390/land6030060

Xianghuan Luo, Christiaan Lemmen + Show 2 more

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https://doi.org/10.3390/land6030060

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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

Highlights

The above challenges and opportunities provide the overarching motivation for the research. Derived from this situation, the objective of this study is to develop a strategy for semi-automated extraction of parcel boundaries from airborne laser scanning (ALS) point cloud data and assess it in terms of accuracy, completion, and degree of automation, by comparing with existing cadastral maps
Since this study aimed to the reconstruct a 2D cadastral map, only planar coordinates of points were taken into consideration
This study, which explored the feasibility of point cloud data for cadastral survey, achieved the main objective: to develop a workflow for semi-automated extraction of cadastral boundaries from airborne laser scanning data

Summary

Introduction

Contemporary claims suggest 75% of global land rights are not registered in a statutory cadastral system and most are located in developing countries [1]. Proponents of land administration claim that without confirmation from a cadaster, people tend to find it more difficult to access and use land. In this situation, land disputes are likely to be aroused and may result in land grabbing, disorder, and failure of land markets [2]. For several decades, international development donors have argued for the accelerated establishment or completion of cadastral systems. Conventional cadastral survey methods are often argued as time-consuming and labor intensive

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