Distance in Spatial Analysis: Measurement, Bias, and Alternatives

Wangshu Mu, Daoqin Tong

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Distance is an important and basic concept in geography. Many theories, methods, and applications involve distance explicitly or implicitly. While measuring the distance between two locations is a straightforward task, many geographical processes involve areal units, where the distance measurement can be complicated. This research investigates distance measurement between a location (point) and an area (polygon). We find that traditional polygon-to-point distance measurements, which involve abstracting a polygon into a central or representative point, could be problematic and may lead to biased estimates in regression analysis. To solve this issue, we propose a new polygon-to-point distance metric along with two algorithms to compute the new distance metric. Simulation analysis shows the effectiveness of the new distance metric in providing unbiased estimates in linear regression.

Original languageEnglish (US)
Pages (from-to)511-536
Number of pages26
JournalGeographical Analysis
Volume52
Issue number4
DOIs
StatePublished - Oct 1 2020
Externally publishedYes

ASJC Scopus subject areas

  • Geography, Planning and Development
  • Earth-Surface Processes

Fingerprint Dive into the research topics of 'Distance in Spatial Analysis: Measurement, Bias, and Alternatives'. Together they form a unique fingerprint.

Cite this