The harmonious development of the ecological environment and the economy is extremely important to achieve regional ecological construction and sustainable development. To properly assess the status of the harmonious development of the ecosystem and the economy, this study constructed an improved ecosystem services value (ESV) and eco-economic harmony (EEH) model to analyze the coordination relationships between the ecosystem and the economy in this region, based on Landsat TM/OLI data of Anxi County in 1999, 2009, and 2019. The results were as follows. (1) Significant changes in land- use occurred in Anxi County between 1999 and 2019. While grassland, cultivated land, and water bodies decreased by 22.91%, 36.82%, and 8.18%, respectively, other land-use types expanded including construction land (206.10%), garden land (56.39%), forest land (10.37%), and unutilized land (90.43%). (2) The ESV decreased by CNY 41.02 billion during this period, with the largest contribution from forest land and the most important service function being regulating services, and mountainous townships made a great contribution to the total ESV. (3) The eco-economic system of Anxi County was at an inharmonic level. The evaluation model produced more favorable results, especially at the township scale, which is highly sensitive to economic policy. This can provide scientific evidence for inter-regional ecological compensation and sustainable development while providing reference and inspiration for similar areas around the world to carry out relevant research.

Investigating the spatial-temporal evolution of land use and its driving forces provides a scientific basis for policy formulation, land-use structure adjustment, and ecological civilization development. Using the Google Earth Engine (GEE) platform, this study analyzed remote sensing images from 2000, 2010, and 2020 to derive basic land-use data for Putian City and its five districts and counties. These data were then systematically analyzed using methodologies such as Single Land-use Dynamics and Geo-informatic Tupu to reveal the characteristics of land-use transitions (LUTs), and the spatial-temporal evolution pattern over the past two decades in Putian City, China. Subsequently, socioeconomic conditions and macro policies were identified as driving factors to further explore the mechanisms behind land-use evolution in the study area through canonical correspondence analysis (CCA). The findings revealed that: (1) The predominant land-use structure in Putian City consisted mainly of cultivated land and forest land, with other land types interspersed within them, while built-up land exhibited continual outward expansion. (2) Various regions within Putian City exhibited varying degrees of abandoned farmland, ultimately transforming into wasteland (grassland) with weed growth, presenting significant challenges for ensuring food security and mitigating the conversion of cultivated land to non-agricultural and non-grain uses. (3) Specific macro-economic development objectives during distinct periods, particularly urban expansion and the growth of the secondary industry resulting from municipal and county mergers, emerged as pivotal factors driving the spatial and temporal evolution of land use and influenced the differential distribution pattern across Putian City. Consequently, this study suggests bolstering scientific planning and implementing effective regulations concerning land use, and it advocates for the efficient utilization of space-time resources pertaining to cultivated land, integrating them with agriculture, culture, and tourism endeavors. Such measures are proposed to ensure the harmonized and sustainable development of the regional ecological economy.

Exploring and predicting the spatiotemporal evolution characteristics and driving forces of carbon storage in typical mountain forest ecosystems under land-use changes is crucial for curbing the effects of climate change and fostering sustainable, eco-friendly growth. The existing literature provides important references for our related studies but further expansion and improvements are needed in some aspects. This study first proposed an integrated framework comprising gray multi-objective optimization (GMOP), Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), the Patch-level Land Use Simulation Model (PLUS), and optimal parameter-based geographical detector (OPGD) models to further expand and improve on existing research. Then, the integrated model was used to analyze the spatial–temporal variation in land-use pattern and carbon storage at the county scale in China’s Daiyun Mountain’s Rim under four scenarios in 2032, and analyze the driving force of spatial differentiation of carbon storage. The results indicated that (1) land-use change primarily involves the mutual transfer among forest, cultivated, and construction land, with approximately 7.2% of the land-use type area undergoing a transition; (2) in 2032, the natural development scenario projects a significant reduction in forest land and an expansion of cultivated, shrub, and construction lands. Conversely, the economic priority, ecological priority, and economic–ecological coordinated scenarios all anticipate a decline in cultivated land area; (3) in 2032, the natural development scenario will see a 2.8 Tg drop in carbon stock compared to 2022. In contrast, the economic priority, ecological priority, and economic–ecological coordinated scenarios are expected to increase carbon storage by 0.29 Tg, 2.62 Tg, and 1.65 Tg, respectively; (4) the spatial differentiation of carbon storage is jointly influenced by various factors, with the annual mean temperature, night light index, elevation, slope, and population density being the key influencing factors. In addition, the influence of natural factors on carbon storage is diminishing, whereas the impact of socioeconomic factors is on the rise. This study deepened, to a certain extent, the research on spatiotemporal dynamics simulation of carbon storage and its driving mechanisms under land-use changes in mountainous forest ecosystems. The results can serve to provide scientific support for carbon balance management and climate adaptation strategies at the county scale while also offering case studies that can inform similar regions around the world. However, several limitations remain, as follows: the singularity of carbon density data, and the research scope being confined to small-scale mountainous forest ecosystems. Future studies could consider collecting continuous annual soil carbon density data and employing land-use simulation models (such as PLUS or CLUMondo) appropriate to the study area’s dimensions.

Exploring the mechanisms and processes of land-use transitions (LUTs) and their impact on ecosystem services can effectively elucidate the intricate interactions between human and natural systems, which is pivotal for advancing the sustainable development of regional economies and enhancing ecological environments. However, the existing literature lacks comprehensive analysis regarding the spatial and temporal evolution of LUTs, with insufficient integration of the “spatial pattern” and “time process”. Moreover, traditional assessments of the ecosystem services value (ESV) often overlook their negative costs. To address these gaps, this study first utilized the Google Earth Engine (GEE) cloud platform and employed the random forest algorithm to conduct supervised classification on Landsat remote-sensing images from the years 2000, 2010, and 2020 within the research area, thereby obtaining land-use data for three distinct periods. And then, we investigated the geographic features of LUTs and their ecological effects in the Ningde City of China from 2000 to 2020. The geo-informatic Tupu model and a newly revised method of benefit transfer were primarily employed for this purpose. The findings indicate the following: (1) Over the study period, the land-use structure of Ningde City predominantly comprised cultivated land and forest land, with continuous decreases in both types and a concurrent increase in built-up land. (2) Significant disparities exist in the spatial distribution of Tupu units, notably with “forest land → cultivated land” and “cultivated land → built-up land” as crucial units influencing ESV changes. (3) The ESV in Ningde City decreased from CNY 1105.54 × 10⁸ to CNY 1020.47 × 10⁸ over 2000–2020, while the ecosystem dis-services value exhibited an opposing trend, rising from CNY 12.68 × 10⁸ to CNY 20.39 × 10⁸. (4) The net ESV in Ningde City showed a decline over the same period, indicating a certain vulnerability in the city’s ecological system structure. This study aims to enhance our understanding of the influence of land-use patterns on ESV, offering valuable insights for regional ecological–environment management and land-use policy formulation, thereby fostering sustainable development in ecological, environmental, and socio-economic dimensions. Furthermore, the results serve as a reference for evaluating net ecosystem services value in other countries/regions.

Human actions have led to consistent and profound alterations in land use, which in turn have had a notable effect on the services provided by ecosystems. In this research, the Google Earth Engine (GEE) was initially employed to perform a supervised classification of Landsat satellite images from 2000 to 2020, which allowed us to obtain land-use data for Putian City, China. Next, the geo-informatic Tupu model and the revised valuation model were used to explore the spatial attributes and ecological effects of land-use changes (LUCs). Subsequently, EEH (eco-economic harmony), ESTD (ecosystem services tradeoffs and synergies degree index), and ESDA (exploratory spatial data analysis) methods were employed to further analyze the coordination level, trade-offs, synergies, and spatial patterns of ecological-economic system development. The findings revealed that: (1) The land-use composition in Putian City was predominantly cultivated land and forest land, with other types of land intermixed. Concurrently, there was an ongoing trend of expansion in urban areas. (2) ESV in Putian City exhibited an upward trend, increasing from 15.4 billion CNY to 23.1 billion CNY from 2000 to 2020. (3) ESV exhibited an imbalance in spatial distribution, with high-high agglomeration areas concentrated in the central part of Putian City and the coastal region of Hanjiang District, while low-low agglomeration areas were prevalent in Xianyou County in the southwest, Xiuyu District along the coast, and Licheng District in the urban center. (4) Synergistic relationships among ESs predominated, though the trade-off relationship showed a tendency to expand. (5) The ecological environment and economic progress in Putian City collectively faced a region of potential risk. The findings of this study are intended to serve as a guide for improving the distribution of land resources and for developing strategies that ensure the sustainable development of the region’s socio-economic framework.