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Data-Driven Multi-Scale Integration of Transportation Networks and Greenhouse Gas Emissions for Landscape Infrastructure Planning

Author

Listed:
  • Jiajia Wang

    (Department of Landscape Architecture, University of Illinois at Urbana, Champaign, IL 61820, USA)

  • Brian Deal

    (Department of Landscape Architecture, University of Illinois at Urbana, Champaign, IL 61820, USA)

  • Moazam Iqbal Hakim

    (School of Information Sciences, University of Illinois at Urbana, Champaign, IL 61820, USA)

Abstract

This study introduces a novel multi-scale framework for analyzing transportation-related greenhouse gas emissions across Illinois from a landscape infrastructure perspective. By integrating county-level, census tract, and high-resolution (30 × 30 m) data of road, rail, and aviation emissions, the research reveals distinct landscape corridor effects where major transportation routes create linear zones of elevated rural emissions connecting urban centers. While urban areas demonstrate higher total emissions, rural regions show higher tract-level and per capita emission intensities along transportation corridors. The extensive available land in rural areas, particularly along these high-emission corridors, presents significant opportunities for strategic green infrastructure deployment and mitigation. The study establishes a technical foundation for data-driven green infrastructure planning by identifying optimal locations for landscape interventions based on emission patterns. This research advances the integration of transportation and landscape planning by providing actionable insights for policymakers and designers working to mitigate climate impacts through strategic green infrastructure and nature-based solutions.

Suggested Citation

  • Jiajia Wang & Brian Deal & Moazam Iqbal Hakim, 2025. "Data-Driven Multi-Scale Integration of Transportation Networks and Greenhouse Gas Emissions for Landscape Infrastructure Planning," Land, MDPI, vol. 14(4), pages 1-24, April.
    • Handle: RePEc:gam:jlands:v:14:y:2025:i:4:p:807-:d:1630825
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