A python script for longitudinally measuring the duration of vacant land uses. Issue 1 (2nd January 2022)

• Record Type: Journal Article
• Authors: Newman, Galen; Kim, Youjung; Kim, Gunwoo; Lee, Ryun Jung; Gu, Donghwan; Forghanparast, Kaveh; Goldberg, Daniel
• Is Part Of: Journal of spatial science. Volume 67:Issue 1(2022)
• Page Start: 129
• Page End: 141
• Publication Date: 2022-01-02
• Subjects: Vacant land -- urban decline -- geographic information systems -- spatial analysis -- python script; Geographic information systems -- Periodicals; Cartography -- Periodicals; Surveying -- Periodicals; Geodesy -- Periodicals; Photogrammetry -- Periodicals; Cartography; Geodesy; Geographic information systems; Photogrammetry; Surveying; Periodicals; 526.05
• DOI: 10.1080/14498596.2020.1721344
• Languages: English
• ISSNs: 1449-8596

Abstract

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.