Assessment of Urban Green Space Based on Bio-Energy Landscape Connectivity: A Case Study on Tongzhou District in Beijing, China

Kunyuan Wanghe, Xinle Guo, Xiaofeng Luan and Kai Li
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Kunyuan Wanghe: School of Nature Conservation, Beijing Forestry University, No. 35 Qinghua East Road, Beijing 100083, China
Xinle Guo: School of Nature Conservation, Beijing Forestry University, No. 35 Qinghua East Road, Beijing 100083, China
Xiaofeng Luan: School of Nature Conservation, Beijing Forestry University, No. 35 Qinghua East Road, Beijing 100083, China
Kai Li: School of Nature Conservation, Beijing Forestry University, No. 35 Qinghua East Road, Beijing 100083, China

Sustainability, 2019, vol. 11, issue 18, 1-15

Abstract: Green infrastructure is one of the key components that provides critical ecosystems services in urban areas, such as regulating services (temperature regulation, noise reduction, air purification), and cultural services (recreation, aesthetic benefits), but due to rapid urbanization, many environmental impacts associated with the decline of green space have emerged and are rarely been evaluated integrally and promptly. The Chinese government is building a new city as the sub-center of the capital in Tongzhou District, Beijing, China. A series of policies have been implemented to increase the size of green urban areas. To support this land-use decision-making process and achieve a sustainable development strategy, accurate assessments of green space are required. In the current study, using land-use data and environmental parameters, we assessed the urban green space in the case study area. The bio-energy and its fluxes, landscape connectivity, as well as related ecosystem services were estimated using a novel approach, the PANDORA model. These results show that (1) in the highly urbanized area, green space is decreasing in reaction to urbanization, and landscape fragmentation is ubiquitous; (2) the river ecology network is a critical part for ecosystem services and landscape connectivity; and (3) the alternative non-green patches to be changed to urban, urban patches which can improve landscape quality the most by being changed to green, and conservation priority patches for biodiversity purposes of urban green were explicitly identified. Conclusively, our results depict the spatial distribution, fluxes, and evolution of bio-energy, as well as the conservation prioritization of green space. Our methods can be applied by urban planners and ecologists, which can help decision-makers achieve a sustainable development strategy in these rapidly urbanizing areas worldwide.

Keywords: urban planning; green space; landscape connectivity; bio-energy; PANDORA model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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