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

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  • 1Department of Landscape Architecture and Urban Planning, Texas A&M University, College Station, TX.

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The length of time urban properties remain vacant strongly impacts city decline. This study developed a Python tool to track vacancy duration, aiding urban regeneration efforts globally.

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Area of Science:

  • Urban planning and development
  • Geographic Information Systems (GIS)
  • Socio-economic geography

Background:

  • Urban areas experience land vacancy due to population shifts.
  • The duration of property vacancy is a critical, yet often overlooked, factor in urban decline.
  • Existing methods for assessing vacancy duration are limited by data integration challenges.

Purpose of the Study:

  • To develop and apply a Python script for tracking property vacancy duration.
  • To create a transferable tool for cities managing vacant land inventories.
  • To enable data-driven prioritization for urban regeneration strategies.

Main Methods:

  • Utilized a Python script to analyze longitudinal data for tracking property vacancy.
  • Applied the script to a case study in Minneapolis, MN, USA.
  • Focused on the temporal aspect of land use, specifically vacancy duration.

Main Results:

  • Successfully created a script to quantify the duration of urban land vacancy.
  • Demonstrated the script's applicability in a real-world urban setting.
  • Highlighted the potential for a standardized tool to assess vacancy metrics.

Conclusions:

  • Vacancy duration is a more significant driver of urban decline than the extent of vacant land.
  • The developed Python tool offers a scalable solution for cities worldwide.
  • This methodology can guide targeted urban regeneration and land management practices.