Grassland plays a crucial role in the global cycles of matter, energy, water and, climate regulation. Biomass serves as one of the fundamental indicators for evaluating the ecological status of grassland. This study utilized the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP) from meteorological data and the Global Inventory Monitoring and Modeling System (GIMMS) Normalized Difference Vegetation Index (NDVI) remote sensing data for northern China’s temperate and alpine grasslands from 1981 to 2015. NPP was subsequently converted into aboveground biomass (AGB). The dynamic changes in grassland AGB were analyzed, and the influence of climate change was examined. The results indicate strong agreement between AGB estimations from the CASA model and Gill method based on field-measured AGB, confirming the model’s reliability for these regions. The dynamic changes in AGB exhibited a significant increasing trend of 1.31 g/m². Grazing intensity (GI), soil moisture, and mean annual precipitation are identified as key factors influencing changes in grassland AGB. Our findings indicate that precipitation and soil moisture are the primary drivers of AGB accumulation during the growing season (spring, summer, and autumn), while temperature plays a critical role in supporting biomass accumulation during winter. Higher temperatures in winter contributes to increased AGB in the following spring, particularly in desert steppe and alpine meadow ecosystems. These insights highlight the complex interaction between climate factors and human activities in shaping grassland productivity across different seasons.

The spatial equality of urban public services and their accessibility are a crucial aspect of urban sustainability. However, there is currently a lack of a composite proxy that can effectively assess public service equality with fine granularity. To address this gap, we have developed a new indicator based on the concept of location dominance. This indicator accumulates access opportunities to public services with a time-weighted decay function at granular level. Our findings reveal that location dominance in Shijiazhuang follows a pronounced core–periphery pattern. Efficient travel modes can significantly enhance location dominance and increase spatial equality, aligning with people’s travel preferences. Additionally, we discovered an extremely strong linear correlation between three key urban development elements (i.e., nighttime lighting data, land use intensity, and population retention rate) and location dominance. The discussion of these findings confirms the validity of our method and the reliability of our results. Consequently, this method and its outputs can aid policymakers and urban planners in swiftly identifying subtle disparities in spatial accessibility for public services, thereby promoting urban equality and sustainability.