The distribution of urban parks is closely related to the opportunities of daily use by residents as well as the performance of the park system. The question as to whether parks are distributed equitably within cities is therefore becoming the focus of attention. However, only a few studies have explored a comprehensive and systematic procedure for urban park accessibility analysis and equity evaluation. In this study, by applying an improved two-step floating catchment area (2SFCA) method and K-means cluster analysis, based on the application of multi-source data, we provide insights into an equity study on park accessibility at the neighborhood scale and urban ring scale in the central urban area of Zhengzhou. These results suggest that the spatial access to parks in Zhengzhou is generally unevenly distributed among neighborhoods, and both the mean and standard deviation of accessibility show an increase from the center to the periphery. The cluster analysis reveals a set of four types of neighborhoods, including a high-supply medium-demand medium-accessibility type (HMM), a low-supply medium-demand low-accessibility type (LML), a high-supply low-demand high-accessibility type (HLH), and a medium-supply high-demand low-accessibility type (MHL), each with different characteristics and causes. The spatial distribution of the accessibility types exhibits both similarities and differences between the urban rings. The findings of this study could serve as a tool for identifying areas in which parks are underserved and the ways in which they differ from other areas, which can guide urban planning to address specific inequities.

Urban Vitality (UV) is a critical indicator for measuring sustainable urban development and quality. It reflects the dynamic interactions and supply–demand coordination within urban systems, especially concerning the human–land relationship. This study aims to quantify the UV of Luohe City, China, for the year 2023, analyze its spatial characteristics, and investigate the driving patterns of socio-ecological land functions on UV intensity and heterogeneity under different scenarios. Utilizing multi-source data, including human mobility data from Baidu Location-Based Services (LBSs), Landsat-9, MODIS, and diverse geo-information datasets, we conducted factor screening and comprehensive assessments. Firstly, Self-Organizing Maps (SOMs) were employed to identify typical activity patterns, and the Urban Vitality Index (UVI) was calculated based on Human Mobility Intensity (HMI) data. Subsequently, a framework for quantity–quality–structure assessments weighted and aggregated sub-indicators to evaluate the Land Social Function (LSF) and Land Ecological Function (LEF). Following the screening process, a Multi-scale Geographically Weighted Regression (MGWR) was applied to analyze the scale and driving relationships between UVI and the land assessment sub-indicators. The results were as follows: (1) The UV distribution in Luohe City was highly uneven, with high vitality areas concentrated within the built-up regions. (2) UV showed significant correlations with both LSF and LEF. The influence of LSF on UV was stronger than that of LEF, with the effectiveness of LEF relying on the well-established provisioning of LSF. (3) Artificial Surface Ratio (ASR) and Corrected Night Lights (LERNCI) were identified as key drivers of UV across multiple scenarios. Under the weekend scenario, the Green Space Ratio (GSR) and the Vegetation Quality (VQ) notably enhanced the attractiveness of human activities. (4) The impacts of drivers varied at the urban, township, and street scales. The analysis focuses on factors with significant bandwidth changes across multiple scenarios: VQ, Remote-Sensing-based Ecological Index (RSEI), GSR, ASR, and ALSI. This study underscores the importance of socio-ecological land functions in enhancing urban vitality, offering valuable insights and data support for urban planning.

With urbanization, the uncertainties faced by urban areas continue to increase, and in response, China's urban planning is transitioning from a focus on quantity to quality. Promoting system coupling and coordination helps to make urban areas more resilient to risk. This paper uses data from Luohe City (China) in 2022 as an example to calculate the inter-system coupling coordination degree (CCD), find the factors that obstruct resilience construction, and further explore the spatial heterogeneity of the obstacle factors. The synthetic evaluation model, coupling evaluation model, and obstacle diagnosis model are used to evaluate and analyze each subsystem. The results are as follows: According to the synthetic evaluation, the mean urban development value is 0.48, with high-value regions clustered in the Southeastern built-up zone. Mean value of urban coupling coordination is 0.66, the coordination level is 7 (Moderate Coordination). Urban development degree is positively correlated with CCD. Globally, the economy is the main factor obstructing resilient growth, but the core obstacle areas of the ecosystem are larger and have a wider impact. This study contributes to understanding the internal action of urban systems and provides data for balance development and urban resilience enhancement.