Comparison of Cloud-to-Cloud Distance Calculation Methods

Abstract

Cloud-to-cloud (C2C) distance calculations are frequently performed as an initial stage in change detection and spatiotemporal analysis with point clouds. There are various methods for calculating C2C distance, also called inter-point distance, which refers to the distance between two corresponding point clouds captured at different epochs. These methods can be classified from simple to complex, with more steps and calculations required for the latter. Generally, it is assumed that a more complex method will result in a more precise calculation of inter-point distance, but this assumption is rarely evaluated. This paper compares eight commonly used methods for calculating the inter-point distance. The results indicate that the accuracy of distance calculations depends on the chosen method and a characteristic related to the point density, the intra-point distance, which refers to the distance between points within the same point cloud. The results are helpful for applications that analyze spatiotemporal point clouds for change detection. The findings will be helpful in future applications, including analyzing spatiotemporal point clouds for change detection.