Formula for calculating spatial similarity degrees between point clouds on multi-scale maps taking map scale change as the only independent variable
Year: 2015
Type: article
Abstract: The degree of spatial similarity plays an important role in map generalization, yet there has been no quantitative research into it. To fill this gap, this study first defines map scale change and spatial similarity degree/relation in multi-scale map spaces and then proposes a model for calculating the degree of spatial similarity between a point cloud at one scale and its generalized counterpart at another scale. After validation, the new model features 16 points with map scale change as the x coordinate and the degree of spatial similarity as the y coordinate. Finally, using an application for curve fitting, the model achieves an empirical formula that can calculate the degree of spatial similarity using map scale change as the sole independent variable, and vice versa. This formula can be used to automate algorithms for point feature generalization and to determine when to terminate them during the generalization.
Source: Geodesy and Geodynamics
Authors: Weifang Yang, Haowen Yan, Jonathan Li
Institutions: University of Waterloo, Lanzhou Jiaotong University
Language: English
Subfield: Geography, Planning and Development
Field: Social Sciences
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W1975794881