Urban area is a major source of CO₂ and other greenhouse gases. Urban green space (UGS) is an essential element to increase carbon sequestration directly and reduce emission indirectly. In this study, the net primary production (NPP) and net ecosystem productivity (NEP) was monitored in order to enhance the carbon sequestration function of UGS and promote urban low-carbon development. Based on the Sentinel-2 L2A satellite images, meteorological data, and vegetation type data in 2019, we used the optimized Carnegie Ames Stanford Approach (CASA) model to estimate the NPP values of UGS types including attached green space, park green space, protective green space, and regional space in Beijing, Guangzhou, Shanghai, Shenyang, and Xi’an. The NEP values were evaluated based on NPP and soil heterotrophic respiration (R_H) to quantify the vegetation carbon sink capacity. The accuracy test shows that the estimated NPP values based on the optimized CASA model are effective. The results indicate that the average NPP values (1008.5 gC·m⁻²·a⁻¹) and vegetation carbon sink capacity (771.49 gC·m⁻²·a⁻¹) of UGS in Beijing rank first among the cities, which is followed by the values in Guangzhou. The regional green space and park green space in five cities function as carbon sinks with high NPP values and have vegetation carbon sink capacity, whereas the attached green space in Shanghai and Xi’an as well as the protective green space in Guangzhou and Xi’an function as carbon sources. Moreover, the NEP distribution shows obvious spatial aggregation characteristics, that is, the high NEP values of UGS are clustered in mountainous forest areas in the west and north of Beijing, Northeast Guangzhou, and South Xi’an whereas the low NEP values are mostly concentrated in the urban built-up areas under strong influences of human activities. This research provides a new method for NPP and NEP estimation of UGS at the city scale and the scientific basis for the improvement of the vegetation carbon sink capacity of UGS.

Balancing ecological conservation with development pressures remains a critical challenge in regions hosting mega-events like the Winter Olympics. This study evaluates the ecological impacts of pre-Olympic construction in Chongli, China (2016–2021), through the integrated analysis of ecosystem service value (ESV) and landscape ecological risk (LERI). Using Sentinel-2 imagery and spatial statistics, we quantified land-use changes, applied benefit transfer methods for ESV assessment, and calculated the LERI using landscape pattern indices. The results revealed a 4.6% increase in the total ESV (266.4 to 278.7 million CNY), which was driven by afforestation initiatives that expanded the area of shrub-grassland and forests. Concurrently, the proportion of high/moderate LERI areas decreased by 12.3%, indicating reduced ecological vulnerability. Spatial correlation analysis demonstrated significant negative relationships between the ESV and LERI, particularly in zones that were undergoing ecological restoration. However, urban expansion weakened these synergies locally. The findings of this study highlight that strategic greening effectively enhanced ecosystem services while mitigating landscape risks during preparations for the Olympics. We propose an adaptive zoning framework that emphasizes dynamic ESV-LERI monitoring, tourism carrying capacity regulation, and payment for ecosystem service mechanisms to optimize post-event management. This integrated approach provides a transferable model for ecological governance in ecologically sensitive areas facing rapid development pressures, demonstrating the value of dual assessment methodologies in sustainable spatial planning.

Urban and regional ecosystems are increasingly challenged by the compounded effects of climate change and intensive land use. In this study, a predictive assessment framework for ecosystem resilience in the Beijing–Tianjin–Hebei region was developed by integrating multi-source remote sensing data, with the aim of quantitatively evaluating the coupled effects of climate change and land use change on future ecosystem resilience. In the first stage of the study, the SD-PLUS coupled modeling framework was employed to simulate land use patterns for the years 2030 and 2060 under three representative combinations of Shared Socioeconomic Pathways and Representative Concentration Pathways (SSP1-2.6, SSP2-4.5, and SSP5-8.5). Building upon these simulations, ecosystem resilience was comprehensively evaluated and predicted on the basis of three key attributes: resistance, adaptability, and recovery. This enabled a quantitative investigation of the spatio-temporal dynamics of ecosystem resilience under each scenario. The results reveal the following: (1) Temporally, ecosystem resilience exhibited a staged pattern of change. From 2020 to 2030, an increasing trend was observed only under the SSP1-2.6 scenario, whereas, from 2030 to 2060, resilience generally increased in all scenarios. (2) In terms of scenario comparison, ecosystem resilience typically followed a gradient pattern of SSP1-2.6 > SSP2-4.5 > SSP5-8.5. However, in 2060, a notable reversal occurred, with the highest resilience recorded under the SSP5-8.5 scenario. (3) Spatially, areas with high ecosystem resilience were primarily distributed in mountainous regions, while the southeastern plains and coastal zones consistently exhibited lower resilience levels. The results indicate that climate and land use changes jointly influence ecosystem resilience. Rainfall and temperature, as key climate drivers, not only affect land use dynamics but also play a crucial role in regulating ecosystem services and ecological processes. Under extreme scenarios such as SSP5-8.5, these factors may trigger nonlinear responses in ecosystem resilience. Meanwhile, land use restructuring further shapes resilience patterns by altering landscape configurations and recovery mechanisms. Our findings highlight the role of climate and land use in reshaping ecological structure, function, and services. This study offers scientific support for assessing and managing regional ecosystem resilience and informs adaptive urban governance in the face of future climate and land use uncertainty, promotes the sustainable development of ecosystems, and expands the applicability of remote sensing in dynamic ecological monitoring and predictive analysis.

Exploring the dynamic changes and trade-offs/synergies among ecosystem services is essential to urban ecological protection and sustainable development. In this study, we quantified the spatio-temporal changes in nine ecosystem service values in Beijing from 2000 to 2020 based on land-use data and the equivalent factor method. Correlation analysis and geographically weighted regression were combined to explore the trade-offs and synergies between ecosystem services. The results show that (1) the total ecosystem service value of Beijing increased from CNY 15 billion to 52 billion from 2000 to 2020, and the value was mainly contributed to by forest, cropland, and water. The regulating services covered the largest proportion of the total ecosystem service value, followed by the supporting services; (2) the high-ESV area was mainly located in the mountainous area with abundant forest resources, and the low values were mainly concentrated in central urban areas; (3) most of the ecosystem service pairs had synergies, while the trade-offs mainly existed between food supply services and other services. Measures, such as controlling built-up areas, increasing the area of green space and enhancing vegetation protection, as well as implementing high-quality agriculture, should be taken in order to balance the relationship between ESs and improve ecosystem management in Beijing.

Urban carbon emissions significantly contribute to climate change, exacerbating environmental issues such as global warming. Understanding carbon metabolism is vital for identifying key emission sources and implementing targeted mitigation strategies. This study presents an innovative carbon metabolism analysis framework that integrates an ecological network analysis (ENA) with land use dynamics, enriching the theoretical system and providing policy recommendations for sustainable urban development. We investigated carbon metabolism in the Beijing–Tianjin–Hebei Urban Agglomeration (BTHUA) from 2000 to 2020 using land use and statistical data. The ENA method quantified the ecological relationships between land use compartments. Our findings revealed that industrial and transportation land exhibited the highest carbon emission density, while forest land demonstrated the highest carbon sequestration density. Notably, the negative net horizontal carbon flow indicated that land use changes exacerbated the disorder of carbon metabolism. The increasing mutualism index suggested a reduction in the negative impacts of land use changes on carbon metabolism. This study highlights the importance of spatial planning in transforming ecological relationships and provides a comprehensive understanding of carbon metabolism dynamics influenced by land use changes. The insights gained can inform effective mitigation strategies in the BTHUA and similar urban agglomerations, ultimately contributing to sustainable urban development.

In the context of global change, assessing the sustainability of ecological restoration in water-scarce regions presents a critical scientific challenge. The Haihe River Basin (HRB), vital to China’s food and water security, has experienced extensive greening over the past two decades. However, the hydrological cost of this greening remains uncertain. This study leverages multi-source satellite remote sensing data (MODIS, CLCD) from 2001 to 2023 to investigate the hydrological implications of this greening. Our analysis reveals a stark ‘decoupling’: despite significant increases in Gross Primary Production (GPP) (9.45 g C·m⁻²·yr⁻¹, p < 0.01), the basin-wide Water Use Efficiency (WUE) exhibited a gradual yet statistically significant decline (slope = −0.01 g C·m⁻²·mm⁻¹·yr⁻¹, p < 0.01). In contrast, Carbon Use Efficiency (CUE) demonstrated no significant basin-wide trend but exhibited significant spatial decreases in mature forest areas. Spatially, the trends are heterogeneous; while 40.80% of the basin showed improved WUE, a significant decrease was observed in only 2.88% of the area, primarily in high-productivity agricultural zones. This localized decline, however, was substantial enough (with mean rates of decrease exceeding −0.06 g C·m⁻²·mm⁻¹·yr⁻¹) to influence the basin-wide average downward. Attribution analysis identified that climate change, particularly rising temperatures and the associated increase in vapor pressure deficit (VPD), were the dominant drivers of this decline by stimulating evapotranspiration (ET) at a rate faster than GPP enhancement. Collectively, our findings suggest that the observed greening trajectory in the HRB, while increasing carbon uptake, is becoming progressively less water-efficient, indicating a path of hydrological unsustainability. This research highlights the urgent need for hydrologically informed policies in ecological restoration, shifting the focus from simple ‘greening’ towards achieving ‘sustainable and hydrologically sound greening’.