Urbanization has significantly altered urban landscape patterns, leading to a continuous reduction in the proportion of green spaces. As critical carbon sinks in urban carbon cycles, urban green spaces play an indispensable role in mitigating climate change. This study aims to evaluate the carbon capture and storage potential of urban green spaces in Luohe, China, and identify the landscape factors influencing carbon sequestration. The research combines on-site data collection with high-resolution remote sensing, utilizing the i-Tree Eco model to estimate carbon sequestration rates across areas with varying levels of greenery. The study reveals that the carbon sequestration capacity of urban green spaces in Luohe City is 1.30 t·C·ha⁻¹·yr⁻¹. Among various vegetation indices, the Enhanced Vegetation Index (EVI) explains urban green space carbon sequestration most effectively through an exponential model (R² = 0.65, AIC = 136.5). At the city-wide scale, areas with higher greening rates, better connectivity, and more complex edge morphology exhibit superior carbon sequestration efficiency. The explanatory power of key landscape indices on carbon sequestration is 78% across the study area, with variations of 71.5%, 62%, and 84.9% for low, medium, and high greening rate areas, respectively. Moreover, when greening rates reach a certain threshold, maintaining and optimizing the quality of existing green spaces becomes more critical than simply expanding the green area. These insights provide valuable guidance for urban planners and policymakers on enhancing the ecological functions of urban green spaces during urban development.

Land use change has had a crucial impact on ecological and socioeconomic systems. This study takes the main urban area of Zhengzhou as an example and constructs a comprehensive analysis framework based on the “transfer-conversion-change” centroid model, which precisely illustrates the trends of urban land use change from 2010 to 2020. The results indicate that: I. From 2010 to 2020, the area of building land, forest land, and grassland continuously increased, while cultivated land decreased significantly. II. Spatial migration characteristics showed southwestward centroid shifts in building land, forest land, cultivated land, unused land, and water bodies. III. Dynamic conversion processes revealed divergent trajectories: forest land conversion drove northeastward centroid migration, while transitions of building land and grassland predominantly shifted southward, contrasting with the northward movement observed in cultivated land, unused land, and water body conversions. IV. Post-change aggregation patterns exhibited regional clustering, with grassland, cultivated land, and unused land centroids shifting northwest, forest and water areas moving southwest, and building land migrating northeast. This study established an integrated analytical framework through the centroid model, expanding its application in land use change analysis and addressing theoretical gaps in quantifying interactions between land use types.

The ecological network serves as a vital spatial strategy for addressing climate change, biodiversity loss, and habitat fragmentation. Addressing limitations in existing ecological network studies—such as strong subjectivity and insufficient accuracy in structural element identification, cross-regional integration, and resistance surface weighting—this research uses the Zhengzhou–Kaifeng–Luoyang region (ZKLR) as a case study. It introduces the self-organizing map (SOM) model to identify ecological sources and employs the XGBoost-SHAP model to optimize resistance surface weights, thereby reducing subjective weighting biases. Subsequently, the Linkage Mapper tool is utilized to construct the regional ecological network. The superiority of the SOM model for identifying ecological sources was confirmed by comparison with a traditional network based on morphological spatial pattern analysis (MSPA). Further integrating complex network topology theory, nodes attack the simulations-assessed network resilience and proposed optimization strategies. The results indicate the following: (1) The area of ecological sources identified by the SOM model is three times that of the MSPA model; (2) SHAP feature importance analysis revealed that elevation (DEM) exerted the greatest influence on the composite resistance surface, contributing over 40%, followed by land use and slope, with each contributing approximately 15%. High-resistance areas were primarily distributed in western and central mountainous regions and built-up urban areas, while low-resistance areas were concentrated in the central and eastern plains; (3) topological analysis indicates that the integrated ecological network (IEN) exhibits superior robustness compared to the structural ecological network (SEN). The edge-adding strategy generated 22 additional ecological corridors, significantly enhancing the overall resilience of the integrated ecological network; and (4) based on ecological network construction and optimization results, a territorial spatial protection strategy of “one belt, two cores, two zones, and three corridors” is proposed. This study provides a novel methodological framework for ecological network construction, with findings offering reference for ecological conservation and spatial planning in the ZKLR and similar areas.

Urban trees play a crucial role in regulating hydrological processes within urban ecosystems by intercepting rainfall to effectively reduce surface runoff and mitigate urban flooding. Current research lacks a systematic quantification of rainfall interception capacity and its community-level impacts at the urban scale. This study adopts a city-scale perspective, integrating field survey data with the i-Tree Eco model to systematically explore the contributions of 20 factors to the average annual rainfall interception of tree species and the average annual rainfall interception efficiency of communities. The study revealed that Deciduous broadleaf trees (1.28 m³ year⁻¹) and Pure coniferous forests (90.7 mm year⁻¹) exhibited substantial rainfall interception capacity. Relative Height, Average Tree Height, Average Crown Width, and Planting Density of trees significantly influence interception capacity. Urban planning can optimize the selection of tree species (e.g., Paulownia, Populus tomentosa, etc.) and community structure (e.g., mixed planting of conifers and deciduous broadleaf trees) to improve rainfall interception capacity, thereby effectively reducing stormwater runoff, mitigating the risk of urban flooding. These findings provide a scientific basis for designing urban vegetation to mitigate flooding, support water management, and advance sponge city development.

The wisdom embedded within traditional human settlements offers profound insights for addressing contemporary ecological challenges. This study systematically investigates the spatial management strategies and ecological wisdom of ancient settlements in the Yiluo River Basin (Luoyang Section), a cradle of Chinese civilization. A mixed-methods approach combined with historical document analysis was utilized, and the results reveal how these settlements achieved harmonious coexistence between human activities and the natural environment over millennia. The research uncovers a sophisticated system of ecological wisdom, primarily manifested across four key dimensions: (1) Macro-Topography-Responsive Siting Strategy: Settlement locations adhered to the principle of “nestling against mountains and facing water,” utilizing natural barriers and resources to mitigate flood risks and optimize microclimates. (2) Context-Adaptive Spatial Layout: The internal layout of settlements was attuned to local topography, water systems, and wind corridors, enhancing living comfort and aesthetic appeal. (3) Gray–Green–Blue infrastructure Synergy: Ancient water management systems were integrated with farmland and transportation routes, forming a synergistic network for irrigation, drainage, flood control, and transportation. (4) Culture–Nature Symbiosis: Cultural practices integrated human life cycles with natural landscapes, fostering regional identity and cultural sustainability. This study argues that the ecological wisdom of ancient Yiluo settlements—marked by its systematic and adaptive nature—provides a valuable historical paradigm for enhancing ecosystem services, building climate resilience, and achieving human–nature harmony in contemporary watershed management and urban–rural development.

Mountainous cultural landscapes, characterized by fragmented heritage sites, present significant challenges for integrated conservation and regional planning. Taking the Mount Song Culture Circle in Dengfeng City, China—a World Heritage site embodying the core of Chinese ritual civilization—as a case study, this study proposes an adaptive minimum cumulative resistance (MCR) gravity model to optimize heritage corridor resilience against spatial fragmentation and development imbalances. Based on a spatial database of 294 cultural relic units, the adaptive model introduces a dynamic cultural value weight (CVIndex = 0.82) and a time decay function (λ = 0.05) to capture the interplay between cultural significance and ecological constraints—features absent in traditional static approaches. The model identifies three optimized heritage corridor networks—”Seeking Wisdom in the Mountains”, “Searching for Culture in the Landscape”, and “Exploring the City Along the River.” Compared with a traditional static MCR model (αindex = 0.42; core area node density = 0.74 nodes/km²), the adaptive approach improves network connectivity by 37% (α-index = 0.58, p < 0.01) and increases core area heritage node density to 1.12/km². Space syntax analysis further confirms that optimized network integration values strongly correlate with cultural dissemination efficiency (R² = 0.78, p < 0.01, n = 48). This research offers a methodological innovation for resilient conservation of complex cultural landscapes in World Heritage contexts.