A python script for longitudinally measuring the duration of vacant land uses

Galen Newman, Youjung Kim, Gunwoo Kim, Ryun Jung Lee, Donghwan Gu, Kaveh Forghanparast, Daniel Goldberg

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Populating and depopulating cities have some degree of underutilised land. The duration of vacancy, or length of time a property remains unused, more strongly influences urban decline than the amount of vacant land. Assessment of the duration of vacancy is seldom conducted, due to a lack of linking longitudinal data. This research creates and applies a Python script to track the duration of vacancy in Minneapolis, MN, U.S.A, to create a tool that can be utilised by cities with vacant land inventories. The tool can be used globally to prioritise treatment areas for urban regeneration plans.

Original languageEnglish
JournalJournal of Spatial Science
DOIs
StateAccepted/In press - 2020

Keywords

  • Vacant land
  • geographic information systems
  • python script
  • spatial analysis
  • urban decline

Fingerprint

Dive into the research topics of 'A python script for longitudinally measuring the duration of vacant land uses'. Together they form a unique fingerprint.

Cite this