Format:
1 Online-Ressource (15 Seiten)
Content:
Urbanization causes tremendous pressure on biodiversity and ecosystems at the global scale. China is among the countries undergoing the fastest urban expansion. For a long time, ecological environment protection has not been a priority in China’s urban planning process. Current urban growth optimization research has some limitations regarding the selection of more scientific ecological constraint indicators and the interaction between urban expansion and ecological factors. This paper at first aimed to establish a reasonable comprehensive biodiversity constraint indicator based on the indicators of net primary productivity, habitat connectivity and habitat quality, and then conducted a case study in Beijing and compared biodiversity loss and urban growth patterns under different developing situations. The integrated valuation of ecosystem services and trade-offs model and GIS-related methods were used to obtain biodiversity and ecological spatial distribution layers. Then an ecological priority-oriented urban growth simulation method was proposed to search for minimum biodiversity loss. The results showed that the important biodiversity security areas were mostly distributed in the western part of the study area and that the ecological degradation in 2000 had a radial pattern and was well in line with the urban construction and ring road distribution patterns. Meanwhile, biodiversity loss with the biodiversity constraint was much less than actual urban growth in 2000–2010. Under the guidance of ecological optimization, urban growth in the research results reflects decentralized and multi-center spatial development characteristics. This type of urban growth not only provides a new model for breaking the inertia of urban sprawl but also proposes ‘biodiversity security’ as an applicable regulatory tool for urban planning and space governance reforming.
Content:
Peer Reviewed
In:
Bristol : IOP Publ., 14,12
Language:
English
DOI:
10.1088/1748-9326/ab55aa
URN:
urn:nbn:de:kobv:11-110-18452/25853-9
URL:
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