2011Computer Engineering and Applications JournalRequires access

Representation methods of distance between spatial objects in GIS and their analysis

Kai Xü

Open publisher page 2 citations

Abstract

Spatial distance is an important metric indicator which is commonly used to constrain and represent the relative location relations between spatial objects.Therefore,the representation and computation of spatial distance between spatial objects may have a clear effect on the results of spatial query,spatial reasoning and spatial analysis.Classic Euclidean distance is only suitable for points.Meanwhile,simply extended distance metrics as minimum distance,maximum distance and centroid distance do not take into account the geometric characteristics of spatial objects,such as shape,positional distribution and so on.For this reason,the scholars develop some representative distances for various practical applications,e.g.Hausdorff distance,boundary Hausdorff distance,dual-Hausdorff distance,extended Hausdorff distance,Frechet distance,turning function distance and area of symmetric difference metric.This paper plays emphasis on the summary of the representation methods of all these distances,pointing out their limitations and adaptabilities,so as to develop more robust distance metrics for application problems in geo-information science.

About this research paper

What this paper is about

Spatial distance is an important metric indicator which is commonly used to constrain and represent the relative location relations between spatial objects.Therefore,the representation and computation of spatial distance between spatial objects may have a clear effect on the results of spatial query,spatial reasoning and spatial analysis.Classic Euclidean distance is only suitable for points.Meanwhile,simply extended distance metrics as minimum distance,maximum distance and centroid distance do not take into account the geometric characteristics of spatial objects,such as shape,positional distribution and so on.For this reason,the scholars develop some representative distances for various practical applications,e.g.Hausdorff distance,boundary Hausdorff distance,dual-Hausdorff distance,extended Hausdorff distance,Frechet distance,turning function distance and area of symmetric difference metric.This paper plays emphasis on the summary of the representation methods of all these distances,pointing out their limitations and adaptabilities,so as to develop more robust distance metrics for application problems in geo-information science.

Why it matters

OpenAlex reports 2 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Available abstract

Spatial distance is an important metric indicator which is commonly used to constrain and represent the relative location relations between spatial objects.Therefore,the representation and computation of spatial distance between spatial objects may have a clear effect on the results of spatial query,spatial reasoning and spatial analysis.Classic Euclidean distance is only suitable for points.Meanwhile,simply extended distance metrics as minimum distance,maximum distance and centroid distance do not take into account the geometric characteristics of spatial objects,such as shape,positional distribution and so on.For this reason,the scholars develop some representative distances for various practical applications,e.g.Hausdorff distance,boundary Hausdorff distance,dual-Hausdorff distance,extended Hausdorff distance,Frechet distance,turning function distance and area of symmetric difference metric.This paper plays emphasis on the summary of the representation methods of all these distances,pointing out their limitations and adaptabilities,so as to develop more robust distance metrics for application problems in geo-information science.

Key concepts: Hausdorff distance, Distance transform, Euclidean distance, Weighted Voronoi diagram, Earth mover's distance, Distance measures, Minkowski distance, Mathematics

Related papers

Back to paper searchBrowse research topicsOriginal source
Representation methods of distance between spatial objects in GIS and their analysis — Research Paper | ScholarLens