A python script for longitudinally measuring the duration of vacant land uses
- Authors
- Newman, Galen; Kim, Youjung; Kim, Gunwoo; Lee, Ryun Jung; Gu, Donghwan; Forghanparast, Kaveh; Goldberg, Daniel
- Issue Date
- Jan-2021
- Publisher
- TAYLOR & FRANCIS LTD
- Keywords
- Vacant land; urban decline; geographic information systems; spatial analysis; python script
- Citation
- JOURNAL OF SPATIAL SCIENCE, pp.1 - 13
- Indexed
- SCIE
SCOPUS
- Journal Title
- JOURNAL OF SPATIAL SCIENCE
- Start Page
- 1
- End Page
- 13
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/142506
- DOI
- 10.1080/14498596.2020.1721344
- ISSN
- 1449-8596
- 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.
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