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A classification scheme for vacant urban lands: integrating duration, land characteristics, and survival rates.

Ryun Jung LeeGalen Newman
Published in: Journal of land use science (2019)
This study develops a methodology to distinguish vacant land types and introduces a classification scheme using a citywide vacancy inventory. Using Minneapolis, MN as a study area, three land characteristics associated with vacant properties - parcel size, ownership, and land use - are examined. Kaplan-Meier survival rates are then estimated to evaluate and compare the durations of vacancy between 2005 and 2015. The results indicate that a vacant property, in general, has the lowest probability to remain vacant within its first two years after becoming vacant. Smaller-sized parcels tend to result in a longer-term vacancy; while publicly owned, industrial, institutional, and/or recreational vacancies show similar tendencies. From this analysis, this study then develops a six-category classification scheme that can be used as (1) a novel tool to inventory vacant urban lands, (2) a diagnostic tool to identify repurposing opportunities, and (3) reliable means of comparing vacant properties across localities.
Keyphrases
  • machine learning
  • deep learning
  • climate change
  • heavy metals
  • risk assessment
  • wastewater treatment