Spatial-Temporal Evolution and Prediction of Carbon Storage: An Integrated Framework Based on the MOP–PLUS–InVEST Model and an Applied Case Study in Hangzhou, East China

Yonghua Li, Song Yao, Hezhou Jiang, Huarong Wang, Qinchuan Ran, Xinyun Gao, Xinyi Ding and Dandong Ge ()
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Yonghua Li: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Song Yao: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Hezhou Jiang: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Huarong Wang: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Qinchuan Ran: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Xinyun Gao: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Xinyi Ding: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China
Dandong Ge: Department of Regional and Urban Planning, Zhejiang University, Hangzhou 310058, China

Land, 2022, vol. 11, issue 12, 1-22

Abstract: Land-use/land-cover change (LUCC) is an important factor affecting carbon storage. It is of great practical significance to quantify the relationship between LUCC and carbon storage for regional ecological protection and sustainable socio-economic development. In this study, we proposed an integrated framework based on multiobjective programming (MOP), the patch-level land-use simulation (PLUS) model, and the integrated valuation of ecosystem service and trade-offs (InVEST) model. First, we used the InVEST model to explore the spatial and temporal evolution characteristics of carbon storage in Hangzhou from 2000 to 2020 using land-cover data. Second, we constructed four scenarios of natural development (ND), economic development (ED), ecological protection (EP), and balanced development (BD) using the Markov chain model and MOP, and then simulated the spatial distribution of land cover in 2030 with the PLUS model. Third, the InVEST model was used to predict carbon storage in 2030. Finally, we conducted a spatial correlation of Hangzhou’s carbon storage and delineated carbon storage zoning in Hangzhou. The results showed that: (1) The artificial surfaces grew significantly, while the cultivated land decreased significantly from 2000 to 2020. The overall trend was a decrease in carbon storage, and the changing areas of carbon storage were characterized by local aggregation and sporadic distribution. (2) The areas of artificial surfaces, water bodies, and shrubland will continue to increase up to 2030, while the areas of cultivated land and grassland will continue to decrease. The BD scenario can effectively achieve the multiple objectives of ecological protection and economic development. (3) The carbon storage will continue to decline up to 2030, and the EP scenario will have the highest carbon storage, which will effectively mitigate the carbon storage loss. (4) The spatial distribution of carbon storage in Hangzhou was inextricably linked to the land cover, which was characterized by a high–high concentration and a low–low concentration. The results of the study can provide decision support for the sustainable development of Hangzhou and other cities in the Yangtze River Delta region.

Keywords: carbon storage; land-use/land-cover change; multiobjective programming; PLUS model; InVEST model; multiple scenario simulation (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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