Evaluating Point Cloud Measurement Accuracy for Residential Property Valuation: A Case Study Using LiDAR Scanning
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Abstract—The most important part of property valuation is accurate property measurement. The more accurate measurement of all types of property, including residential buildings, could lead to an equal and fair value for the property. By comparing linear wall-to-wall measurements taken from point clouds with those taken from certified floor plans, this study evaluates the potential of three-dimensional (3D) point cloud data for use in property measurement. Dimensional measurements were obtained by processing 3D data of a residence in Kajang, Malaysia, using LiDAR-based scanning via PolyCam Pro on an iPhone 14 Pro Max. To assess the workflow’s generalizability, a sample dataset provided by PolyCam representing a landed residential unit was also tested using the same measurement procedure. The results indicate that consumer-grade point cloud data can achieve accuracy sufficient for expert valuation support, with deviations of approximately ±10 mm in the primary dataset and ±3.5 mm in the validation dataset. This shows how point cloud technology can improve transparency, reduce measurement errors caused by individuals, and help in the digital transformation of valuation workflows
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