Urban ecosystem dysfunction, habitat fragmentation, and biodiversity loss caused by rapid urbanization have threatened sustainable urban development. Urban habitat quality is one of the important indicators for assessing the urban ecological environment. Therefore, it is of great practical significance to carry out a study on the driving mechanism of urban habitat quality and integrate the results into urban planning. In this study, taking Zhengzhou, China, as an example, the InVEST model was used to analyze the spatial differentiation characteristics of urban habitat quality and Geodetector software was adopted to explore the driving mechanism of habitat quality at different grid-scales. The results show the following: (1) LUCC, altitude, slope, surface roughness, relief amplitude, population, nighttime light, and NDVI are the dominant factors affecting the spatial differentiation of habitat quality. Among them, the impacts of slope, surface roughness, population, nighttime light, and NDVI on habitat quality are highly sensitive to varying grid-scales. At the grid-scale of 1000 to 1250 m, the impacts of the dominant factors on habitat quality is closer to the mean level of multiple scales. (2) The impact of each factor on the spatial distribution of habitat quality is different, and the difference between most factors has always been significant regardless of the variation of grid-scales. The superimposed impact of two factors on the spatial distribution of habitat quality is greater than the impact of the single factor. (3) Combined with the research results and the local conditions of Zhengzhou, we put forward some directions of habitat protection around adjusting urban land use structure, applying nature-based solutions and establishing a systematic thinking model for multi-level urban habitat sustainability.

Urban parks serve as essential carbon sinks in cities, mitigating climate change by sequestering atmospheric CO₂. Maximizing the carbon sequestration potential within constrained urban spaces is a critical step toward carbon neutrality. However, few studies have systematically examined how the internal spatial composition and shape of green spaces affect their vegetation carbon sequestration capacity. This study analyzes the relationship between landscape indices and vegetation carbon sequestration density (VCSD) using field surveys and high-resolution remote sensing data from 123 urban parks in Zhengzhou, China. The results indicate that Zhengzhou’s parks sequester 14.03 Gg C yr⁻¹, with a VCSD of 0.53 kg C m⁻² yr⁻¹. Significant differences in VCSD were observed among park types, with theme parks having the highest average VCSD (0.69 kg C m⁻² yr⁻¹) and community parks the lowest (0.43 kg C m⁻² yr⁻¹). The key drivers primarily consist of landscape indices that characterize green space distribution and configuration, including the proportion of green space (Pg), largest green patch index (LPI), number of green patches (NP), green patch dispersion index (SPL), and landscape shape index (LSI), with specific thresholds identified for each. Based on these findings, category-specific spatial composition strategies are proposed to precisely enhance the carbon sequestration of park vegetation. This study provides actionable guidance for urban park designers to maximize the carbon sequestration potential of green spaces, thereby mitigating climate change and promoting human health and well-being through green space design.

Understanding the relationship between different essential urban land use categories and the urban thermal environment is essential for urban planning, resource allocation and decision support. However, most of the spatiotemporal correlations between land use types and LST are focused on industrial land use and urban green space, and there are fewer discussions on the totality of urban land use types. Here, using multi-source remote sensing images, correlation analysis and the stepwise regression method, we elaborate the relationship between landscape structure and land surface temperature (LST) across the different seasons of 850 planning management units in Jiaozuo, China. Our results show that the degree of explanation of surface temperature by landscape structure increased with a fine division of land use. The imprint of urban–rural gradients on LST was largely masked by the land use categories at the regional scales. Moreover, the tridimensional structure of buildings significantly affected the LST of residential regions, and the large number of low-rise buildings in urban planning practice contributes to high LSTs. This study provides a comprehensive analysis of the effects of each land use type and landscape structure on surface temperature in urban space and also provides strategies and methods for urban planning in rapidly developing regions of the country.