Abstract
Rapid urbanization resulted in widespread urban expansion and the fragmentation and isolation of large-scale ecological sources. Ecological sustainability has propelled the popularity and implementation of intensive land use programs worldwide, in China particularly. In this study, we explored the spatial spillover effect through ecological networks on intensive urban land use and the underlying driving mechanism using the Wuhan urban agglomeration as the case study area. First, we comprehensively measured land use intensity (LUI) from three dimensions: input, output, and landscape aggregation. Second, ecological sources were identified on the basis of land use maps, and ecological networks were constructed using the “minimum cumulative resistance” model. Then, the “gravity model” was applied to measure the spatial interaction among ecological sources and to construct spatial weight matrices for spatial modeling. Lastly, we devised a spatial Durbin model using the designed “ecological” spatial weight matrices to examine the influencing factors and the potential spatial interactions or constraints. The results showed that the average values of LUI in 2017 were almost 70 times higher than that in 2005 and the Jianghan District had the highest increment (91 times) from 2005 to 2017. LUI was primarily driven by socioeconomic development. Gross domestic product and proportion of tertiary sector exerted positive influences, whereas agricultural output value exhibited a negative effect on LUI in 2005 and 2017. A positive spatial autocorrelation of LUI was observed at the county level, and the spatial spillover effect was confirmed through ecological networks during intensive land use, indicating that ecological spatial influence is an important factor in explaining LUI. The findings help in exploring the spatial influence through ecological networks on LUI at the regional level and provide references for formulating relevant policies to achieve the ecological security of terrestrial ecosystems and coordinated and balanced regional sustainable development.
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