TY - JOUR
T1 - Large-scale ecological red line planning in urban agglomerations using a semi-automatic intelligent zoning method
AU - Lin, Jinyao
AU - Li, Xia
N1 - Publisher Copyright:
© 2019 Elsevier Ltd
PY - 2019/4
Y1 - 2019/4
N2 - 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.
AB - 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.
KW - Ecological planning
KW - Environmental management
KW - Genetic algorithm
KW - Protected area
KW - Spatial optimization
UR - https://www.scopus.com/pages/publications/85060546459
U2 - 10.1016/j.scs.2018.12.038
DO - 10.1016/j.scs.2018.12.038
M3 - 文章
AN - SCOPUS:85060546459
SN - 2210-6707
VL - 46
JO - Sustainable Cities and Society
JF - Sustainable Cities and Society
M1 - 101410
ER -