Optimization of the Territorial Spatial Patterns Based on MOP and PLUS Models: A Case Study from Hefei City, China

Ran Yu (), Hongsheng Cheng, Yun Ye, Qin Wang, Shuping Fan, Tan Li, Cheng Wang, Yue Su and Xingyu Zhang
Additional contact information
Ran Yu: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Hongsheng Cheng: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Yun Ye: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Qin Wang: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Shuping Fan: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Tan Li: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Cheng Wang: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Yue Su: School of Economics and Management, Anhui Agricultural University, Hefei 230036, China
Xingyu Zhang: Wuxi Forestry Station, Wuxi 214000, China

IJERPH, 2023, vol. 20, issue 3, 1-15

Abstract: Optimization of the territorial spatial patterns can promote the functional balance and utilization efficiency of space, which is influenced by economic, social, ecological, and environmental factors. Consequently, the final implementation of spatial planning should address the issue of sustainable optimization of territorial spatial patterns, driven by multiple objectives. It has two components—the territorial spatial scale prediction and its layout simulation. Because a one-sided study of scale or layout is divisive, it is necessary to combine the two to form complete territorial spatial patterns. This paper took Hefei city as an example and optimized its territorial spatial scale using the multiple objective programming (MOP) model, with four objective functions. A computer simulation of the territorial spatial layout was created, using the patch-generating land use simulation (PLUS) model, with spatial driving factors, conversion rules, and the scale optimization result. To do this, statistical, empirical, land utilization, and spatially driven data were used. The function results showed that carbon accumulation and economic and ecological benefits would be ever-increasing, and carbon emissions would reach their peak in 2030. The year 2030 was a vital node for the two most important land use types in the spatial scale—construction land and farmland. It was projected that construction land would commence its transition from reduced to negative growth after that time, and farmland would start to rebound. The simulation results indicated that construction land in the main urban area would expand primarily to the west, with supplemental expansion to the east and north. In contrast, construction land in the counties would experience a nominal increase, and a future ecological corridor would develop along the route south of Chaohu County–Chaohu Waters–Lujiang County–south of Feixi County.

Keywords: territorial spatial pattern; spatial scale; spatial layout; MOP model; PLUS model (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1660-4601/20/3/1804/pdf (application/pdf)
https://www.mdpi.com/1660-4601/20/3/1804/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:20:y:2023:i:3:p:1804-:d:1040386

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().