Exploring land use evolution and its impact on carbon storage is crucial for mitigating climate change in resource-based cities and promoting green, low-carbon development. This study constructs a GMOP-PLUS-InVEST coupled model and utilizes remote sensing data from five phases of land use from 2000 to 2020. Four scenarios are established to simulate the future patterns of land use and carbon storage changes in Jining City. The results indicate that: (1) from 2000 to 2020, farmland, forest land, and grassland in Jining City show a declining trend; while construction and waters increase, resulting in a reduction of carbon storage from 167.35 × 10⁶ t in 2000 to 159.85 × 10⁶ t in 2020; (2) coal mining significantly influences nearby land utilization types and carbon storage, leading to a decline in nearby carbon reserves; (3) compared to the other three scenarios, the coordinated development scenario exhibits higher land use efficiency and carbon storage, with lower levels of human disturbance; balancing the local economy and environment, and serving as a sustainable pattern of land use for the area. The outcomes of this paper quantitatively reflect the relationship between land use, coal mining, and carbon storage in high-water-level resource-based cities; providing guidance for the local economy, urban development, and ecological environment protection.

As the construction of ecological civilization has become more and more important in recent years, ecological restoration and its effect assessment have also received increasing attention. Taking the Wangping coal mine in Beijing as an example, based on Landsat TM/OLI series remote sensing data, we chose five metrics, i.e., fraction vegetation coverage, humidity, heat, dryness, and black particulates, to construct the model for the modified remote sensing ecological index (MRSEI). It was also combined with the Hurst index to conduct dynamic monitoring, spatiotemporal analysis, and prediction studies of the ecological environment quality in the study area. The results showed that: (1) Compared with the RSEI, the first principal component of the MRSEI better integrates the information of each component indicator, has a better average correlation with each indicator, and better reflects the habitat condition in the study area. (2) The mean value of the MRSEI in the study area increased from 0.433 in 1990 to 0.722 in 2021, an increase of 40.03%. (3) From 1990 to 2001, the poor and fair MRSEI-grade areas in the study area were concentrated in the northeastern and southwestern parts of the area. After the ecological restoration project was carried out, the environmental quality of the Wangping coal mine improved year by year, and a small number of poor areas were concentrated in the northeastern border area. (4) The MRSEI of the Wangping coal mine predicted that the future ecological environment of the study area would show a general trend of continuous improvement, but a certain percentage of the area in the northeast had a weak antisustainability trend. The results of the study could provide a reference for ecological restoration planning, sustainable development, and the management of mining areas.

Reasonable land use planning and management efficiently allocates land resources, promotes socio-economic development, protects the ecological environment, and fosters sustainable development. It is a crucial foundation for achieving harmonious coexistence between humans and nature. Optimizing land use is key to land use planning and management. Four scenarios are established: an economic development scenario (EDS), an ecological protection scenario (EPS), a natural development scenario (NDS), and a coordinated development scenario (CDS). This study simulates land use patterns under these scenarios through the coupling of the GMOP and PLUS models. It analyzes the land use efficiency transformation index, landscape ecological index, comprehensive land use benefits, and ecosystem service value (ESV) for each pattern. The optimal land use pattern is determined by balancing these factors. The results indicated that under the CDS, the areas of wasteland, grassland, forest land, water bodies, construction land, and unused land in Lvliang City were 6724.29 km², 6664.74 km², 6581.84 km², 126.94 km², 1017.33 km², and 0.42 km², respectively. This represented the optimal land use plan for Lvliang City. The plan minimized human interference with the landscape pattern, achieved the highest land use efficiency transformation index, and reached a reasonable balance between land use benefits and ESV. The research findings provide valuable insights and decision support for regional land use planning, territorial space planning, and related policy formulation.