The contribution of multi-objective land use optimization to reducing ecological risk: A case study of the Lanzhou-Xining urban agglomeration
Shunjie Xin, Zhongguo Li, Ning Chen, Ziyi Zhang, Xingzhong Zhang, Hongxiang Chen, Xinshu Ma, Ligang Kang
Abstract
• Analyzed the LULC and ecological risks of the Lanzhou Xining urban agglomeration. • Constructed a multi-objective land use optimization and evaluation coupling model. • Determined the contribution level of driving factors that affect LULC changes. • Ecological risk and LULC structure show consistency in changes. • Multi objective land use optimization can reduce ecological risks. Land use/land cover (LULC) affects regional ecological risk (ER) by altering ecosystem services (ES). In order to weigh the value of the land and reduce the ER by optimizing the LULC. In this study, taking the Lanzhou-Xining urban agglomeration(LXUA) as an example, we couple the NSGA-Ⅱ, the PLUS model, and the InVEST model to construct a multi-objective land use optimization(LUO) model oriented to ER reduction, and set four different LULC scenarios for natural development (ND), high-risk development (HR), low-risk development (LR) and sustainable development (SD) in 2024. The evolution patterns of ES under different scenarios were predicted, and the contribution of LULC models to reducing ER under different scenarios was analyzed. The results show that during the period 2000–2020, the change of LULC in LXUA is mainly reflected in the transfer of grassland to forestland, cultivated land, construction land, and unutilized land. The change of LULC and ES show a significant spatiotemporal consistency, and the change of LULC will indirectly affect the ER, and the ER index (ERCI) increases from 0.6338 to 0.6434 in 20 years. In the future, the ER of LR (0.6325), SD (0.6317), ND (0.6548), and HR (0.7085) scenarios will increase sequentially. The ND scenario had the lowest eco-economic value, while the HR scenario had the highest economic value. The LR scenario, which sacrificed economic value, had the highest ecological value. The SD scenario has the highest comprehensive value and low ER, which is the optimal path for the future development of LULC in the LXUA. This research provides a feasible optimization model for reducing the ER of ecologically fragile areas and provides a scientific solution for land management in urban agglomerations.