Optimizing distribution of urban land on the basis of urban land use intensity at prefectural city scale in mainland China

Liye Wang, Siyu Zhang, Lanping Tang, Yanchi Lu, Yanfang Liu and Yaolin Liu

Land Use Policy, 2022, vol. 115, issue C

Abstract: Urban land use intensity (ULUI) reflects the utilization status of urban land use. However, few studies have allocated urban land distribution across provinces or cities based on the ULUI. We propose an optimization method to allocate the urban land based on ULUI to make it effective and decrease the loss of ecosystem services. Using mainland China as the research area, we first estimated ULUI at the prefectural city level in 2015 and evaluated its spatial heterogeneity; urban land distribution in 2030 was then optimized by coupling the estimated ULUI and the LAND System Cellular Automata model for Potential Effects (LANDSCAPE). Specifically, we generated two scenarios: ULUI, and quota (QT). Results showed the following: (1) ULUI demonstrated a spatially heterogenous distribution in 2015. Cities with high ULUI were mainly centralized around urban agglomerations; those with low ULUI were distributed in the northwest and northeast of the research area, where there were economically undeveloped regions. (2) Using optimization, the total economic benefits (EBs) increased and the loss of ecosystem service value (ESV) decreased. Many prefectural cities increased economic output, and reduced ecological losses, even in some rapidly cities. Our research highlights that optimizing urban land based on ULUI is a reasonable method to increase EBs and reduce ESV loss.

Keywords: Spatial optimization; Cellular automata; Land use planning; Ecosystem services; Economic development (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (9)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:lauspo:v:115:y:2022:i:c:s0264837722000643

DOI: 10.1016/j.landusepol.2022.106037

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