Spatial Optimization of Land Use Pattern toward Carbon Mitigation Targets—A Study in Guangzhou

Shouyi Ding, Shumi Liu, Mingxin Chang, Hanwei Lin, Tianyu Lv, Yujing Zhang and Chen Zeng ()
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Shouyi Ding: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Shumi Liu: Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China
Mingxin Chang: Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China
Hanwei Lin: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Tianyu Lv: Guangzhou Collaborative Innovation Center of Natural Resources Planning and Marine Technology, Guangzhou 510060, China
Yujing Zhang: Guangzhou Urban Planning & Design Survey Research Institute, Guangzhou 510060, China
Chen Zeng: Department of Land Management, Huazhong Agricultural University, Wuhan 430070, China

Land, 2023, vol. 12, issue 10, 1-19

Abstract: Global climate change is one of the major challenges facing the world, and the spatial optimization of land use patterns has been regarded as critical in realizing carbon mitigation. In this study, the linear programming model and the Markov Chain model are integrated in different scenarios to optimize land use structure for low-carbon development. The land use pattern is then simulated through the adjusted convolutional neural network and cellular automata model, taking Guangzhou City as the case study area. The results reveal that construction land with high economic efficiency will increase its area, and the reaming types will experience slight changes, in 2035 in the natural development scenario and the economic priority scenario. Ecological land such as forest land, grassland, and water is partly occupied by construction land in the urban–rural fringe areas. The total carbon emissions decrease by 2.32% and 1.57% in these two scenarios. In the low-carbon-oriented scenario, the expansion of construction land is restricted, and the forest land and grassland undergo great expansion. The total carbon emission decreases by 18.95%—a figure much larger than that in the natural development scenario and the economic priority scenario. Our paper embeds the needs and constraints in land spatial planning into the spatial optimization of the land use pattern, which provides valuable references for low-carbon city development in the future.

Keywords: carbon emission; land use; spatial optimization; scenario simulation; Guangzhou City (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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