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.

As peri-urbanisation becomes widespread, quantitative methods for identifying peri-urban areas (PUAs) are increasingly abundant. This study aims to quantitatively compare the differences in the results obtained from multiple PUA identification methods within the same study area and to analyse the spatial patterns of the PUAs. The Threshold Method, Breakpoint Clustering, and Multilayer Perceptron were chosen to compare the identification results of PUAs in Zhengzhou City, China. The results show that the Threshold method identified the most PUAs but with the lowest accuracy. The accuracy of the Breakpoint Clustering was slightly lower than that of the Multilayer Perceptron. Regarding spatial layout, these identification results all show that the PUAs in the northeastern plains of Zhengzhou are more numerous than in the southwestern mountainous regions. Moreover, PUAs can generally be categorised into ring-shaped, belt-shaped, and patch-shaped forms. The spatial evolution of PUAs is influenced by urban expansion, geographical factors, and urban planning, and it can also provide timely reflections on urban development dynamics. These findings can provide valuable references for future research in selecting PUA identification methods, promoting in-depth longitudinal studies and cross-regional research, and enhancing the attention given to PUAs in urban planning and policy-making.

The process of peri-urbanization in the context of globalization has become a global phenomenon. Taking Budapest as a case study, this study aims to develop a breakpoint clustering method that combines breakpoint method and spatial clustering to identify peri-urban areas (PUAs). Landscape metrics were used to analyze the structure and characteristics of various landscapes within PUAs. The results indicate that PUAs in Budapest occupy 39.63% of the area, predominantly consisting of artificial surfaces and agricultural land. In PUAs, artificial surfaces are the dominant landscape type, water bodies exhibit high aggregation and strong connectivity, while agricultural areas, forests and semi-natural areas show high fragmentation. The identification and landscape analysis of PUAs will provide significant insights for urban studies and governmental planning.

The popularity of peri-urban landscapes (PULs) around the world has made them an important part of shaping urban landscapes and promoting sustainable urban development. This study aims to propose sustainable planning guidelines for PULs by analyzing the quantitative evolution of the type, morphology and structure of PULs in Zhengzhou. The methods employed in this study include the Land Cross Transfer Matrix, Morphological Spatial Pattern Analysis, and Landscape Metrics. The results show that agricultural landscapes and artificial landscapes dominate in PULs, and there is an obvious trend of transformation from agricultural PULs to artificial PULs. PULs presents the characteristics mainly in the form of large patches of cores, belt-shaped corridors, and blocks. In terms of structure, PULs show a trenddominated by the fragmentation of natural and semi-natural landscapes. The patch shapes of PULs become more complex and their heterogeneity increases. Based on the evolution trends of PULs, guidelines for planning adapted to local conditions were proposed. This study not only provides a methodological framework for the quantitative evolution analysis of PULs, but also offers insights for the optimization and management of PULs in other regions.

The Balaton region is Hungary’s most important recreational area, known for Central Europe’s largest freshwater lake and its traditional vineyard and horticultural landscapes. Since 1990, vineyard and orchard abandonment and intensified shoreline urbanization have increasingly threatened both landscape character and ecological balance. This study analyses land-use changes in the Balaton hinterland and evaluates the effectiveness of regional land-use regulation between 1990 and 2018, with a focus on the 2000 Balaton Law (BKÜRT), which sought to preserve traditional land uses by permitting construction only where at least 80% of vineyard parcels remained cultivated. Spatial–temporal analysis was based on CORINE Land Cover (CLC) data from 1990 to 2018, supplemented by change layers from the Copernicus Land Monitoring Service. The CORINE Land Cover classification is a three-level hierarchical system (5 Level-1 groups, 15 Level-2 classes, and 44 Level-3 classes) developed by the EEA to provide standardized, satellite-based land cover information across Europe. Land cover was aggregated into major categories (using Level-1 and Level-2 classes) relevant to the Hungarian landscape. To address CLC limitations related to representing vineyards as relatively homogeneous units despite substantial differences in the density and scale of built structures, detailed case studies were conducted in three C1 vineyard zones—Alsóörs, Paloznak, and Szentantalfa—using historical aerial photographs, Google Earth imagery, and the Hungarian Ecosystem Map (NÖSZTÉP). Despite the restrictive regulatory framework, the CLC database showed that the share of vineyards in the vineyard regulation zone (C-1, C-2) decreased between 1990 and 2018 from 45.4% to 35.8% (the share of gardens and fruit plantations had changed from 9.7% to 15.5%). In the whole Balaton region, there was an approximately 18% decline in vineyard areas. Considering the M-2 horticultural zone, the garden coverage increased from 18.9% in 1990 (17.7% in 2000) to 30.5% (share of vineyards changed from 54.3% (54.6% in 2000) to 38.8%). At the regional level, gardens and fruit plantations had a smaller decrease (3.2%). Although overall trends were more favorable than at the national level, regulatory measures proved insufficient to prevent the conversion of vineyards and orchards in sensitive areas, particularly on slopes overlooking the lake, in proximity to tourist hubs, and in areas exposed to strong development pressure. By 2018, the C1 zone had expanded spatially but became less targeted, as the proportion of vineyards within it decreased. Boundary refinements failed to substantially improve regulatory precision or effectiveness. The case studies reveal a gradient of regulatory strictness reflecting differing landscape protection priorities and stages of vineyard transformation, with Alsóörs responding to long-standing, partly irreversible changes while attempting to slow further landscape alteration. To counter ongoing negative trends, more targeted and enforceable regulations are required, including a clearer separation of cultivated and recreational land uses, a maximum building size of 80 m² for recreational properties, and a reassessment of vineyard zone boundaries to better reflect active cultivation and protect sensitive landscapes.

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.