Large-scale ecological red line planning in urban agglomerations using a semi-automatic intelligent zoning method

  • Jinyao Lin*
  • , Xia Li
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

58 Scopus citations

Abstract

Ecological red line (ERL) planning is an effective measure for ecological protection and management. Although many attempts have been made in this field, most have targeted a single city. The task of ERL planning will become particularly difficult in large regions, given the complexity of city networks. Another concern is that ERL schemes cannot be easily coordinated with pre-existing land-use plans and may even conflict with one another, since every plan has its own boundaries, management policies, and other constraints. To address these problems, this study presents a novel framework for large-scale ERL planning whose contributions are twofold. First, we developed a top-down planning strategy that could ensure both the consistency of ecological management and equality for every city within large regions. Second, we propose a semi-automatic intelligent zoning method based on a modified genetic algorithm. The difference between “semi-automatic” and “automatic” is that the former allows users to manually identify some key protected areas. This integrated framework was applied to ERL planning in an urban agglomeration. Three groups of evaluations indicated that the planning schemes generated via the proposed framework are more practical and closer to reality than the results of traditional methods. For example, the comparison between semi-automatic and automatic methods suggested that the former can generate zoning schemes that are easily coordinated with previous land-use plans. Therefore, this comprehensive framework could facilitate large-scale ecological management and planning and will be helpful for the design of environmentally sustainable cities.

Original languageEnglish
Article number101410
JournalSustainable Cities and Society
Volume46
DOIs
StatePublished - Apr 2019
Externally publishedYes

Keywords

  • Ecological planning
  • Environmental management
  • Genetic algorithm
  • Protected area
  • Spatial optimization

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