Accurately identifying potential land use conflicts (LUCs) is critical for alleviating the ever-intensifying contradictions between humans and nature. The previous studies using the method of suitability analysis did not take full advantage of the current land use and multi-function characteristics of land resources. In this study, an improved model of suitability analysis was realized. In order to explore the LUCs status, including the types, intensity and distribution, a multi-objective suitability evaluation model was constructed from the perspective of production-living-ecological functions. And it was applied to Hengkou District, a typical region of the Qin-Ba mountainous area in the central part of China. The results show that the suitability distribution of living- production-ecological functions vary widely from the center to the periphery with altitude in Hengkou District; 22.03% of the land is at a risk of land use conflict. Among them, the high potential conflict areas account for 55.32%, and the conflicts between production and ecological lands (L2P1E1, L3P1E1) are the largest, which are located at the fringe of the central urban and ecologically dominant area. Therefore, it is necessary to adopt effective strategies to achieve a balance between the differential demands of land use. This research could better reflect the true situation of land use in ecologically sensitive mountainous areas and would provide theoretical and methodological support for the identification and prevention of potential LUCs.

A slime mould algorithm (SMA) is a new meta-heuristic algorithm, which can be widely used in practical engineering problems. In this paper, an improved slime mould algorithm (ESMA) is proposed to estimate the water demand of Nanchang City. Firstly, the opposition-based learning strategy and elite chaotic searching strategy are used to improve the SMA. By comparing the ESMA with other intelligent optimization algorithms in 23 benchmark test functions, it is verified that the ESMA has the advantages of fast convergence, high convergence precision, and strong robustness. Secondly, based on the data of historical water consumption and local economic structure of Nanchang, four estimation models, including linear, exponential, logarithmic, and hybrid, are established. The experiment takes the water consumption of Nanchang City from 2004 to 2019 as an example to analyze, and the estimation models are optimized using the ESMA to determine the model parameters, then the estimation models are tested. The simulation results show that all four models can obtain better prediction accuracy, and the proposed ESMA has the best effect on the hybrid prediction model, and the prediction accuracy is up to 97.705%. Finally, the water consumption of Nanchang in 2020–2024 is forecasted.

Tourism plays an important role in rural restructuring, especially in mountainous areas. Mismatches between tourism and rural in terms of the development level and efficiency have given rise to a variety of challenges. In order to achieve the orderly growth of tourism and sustainable rural restructuring, there is an urgent need to explore the interaction between the two. Thus, we introduce the concept of synergistic development potential (SDP) and construct an assessment framework using coupling analysis. Southern Shaanxi, in the Qin-Ba mountainous area, a Chinese region rich in ecological tourism resources, was selected as a case study to evaluate the SDP during the period 2013 to 2018. In our framework, a comprehensive index system with 21 indicators was developed to evaluate the tourism development levels (TDL) and rural development levels (RDL) in 2013 and 2018, and the tourism development efficiency (TDE) and rural restructuring efficiency (RRE) during this period. Secondly, correlations between TDL and RDL, as well as correlations between TDE and RDE, were quantified using the coupling coordination degree model (CCDM). Finally, the SDP evaluation model was constructed through combing the coupling coordination degrees of current development levels and development efficiencies. The case study results indicate that the primary-level coordination counties are both dominated in this region in terms of the relationship of development levels as well as the development efficiencies. Additionally, the SDP results show a significant difference in 25 counties, with 36% of them having low potential, 48% having medium potential, and 16% having high potential. This study could intuitively show the development differences among various units and provide theoretical and methodological support for the rural tourism zoning strategies.

In the context of escalating global concerns for “carbon neutrality and peak carbon” and the urgent need for ecological conservation, deciphering the spatiotemporal interactions between carbon emissions and the ecosystem service value (ESV) in relation to land use changes becomes critically significant. Identifying areas to bolster ecosystem services and curtail carbon emissions, especially within the Guanzhong urban agglomeration, is crucial for advancing sustainable and low-carbon regional development. The study focuses on the urban agglomeration of Guanzhong, using land use and socio-economic data from three periods between 2010 and 2020. Methods such as grid analysis and bivariate spatial autocorrelation models are employed to explore the temporal and spatial evolution characteristics and interaction patterns of carbon emissions and ESV in relation to land use. The findings reveal: (1) during 2010–2020, the Guanzhong urban agglomeration experienced varied transitions in land use types, marked by a significant net decrease in arable land and net increases in grasslands and urban construction areas. (2) The ESV in the Guanzhong urban agglomeration witnessed a consistent rise, exhibiting a spatial distribution pattern with higher values in the southwest and lower in the northeast. Among the categorized ecosystem service functions, services related to hydrological and climate regulation stood out. (3) The Guanzhong urban agglomeration observed an average annual growth rate of 5.03% in carbon emissions due to land use, with a spatial trend that was higher in the center and tapered towards the periphery. Predominant carbon sources included arable lands and urban construction areas, while forests accounted for 94% of carbon sequestration. (4) A pronounced negative correlation between the ESV and carbon emissions was discerned in Guanzhong. Regions with a stronger correlation were primarily centered in Guanzhong, notably around Xi’an and Baoji. The results emphasize the pivotal role of the primary sector’s qualitative development in harmonizing the ESV and carbon emission dynamics in the Guanzhong urban agglomeration. This research provides valuable insights for optimizing land resource management, aligned with the rural revitalization strategy, streamlining carbon dynamics, bolstering ESV, augmenting carbon sequestration efficiency, and guiding ecological spatial planning.

Urban areas with parks tend to have the best outdoor thermal comfort in regions with high urban heat island effects during summer. This study analyzed the synergistic cooling effects of 94 urban parks and the adjacent built-up areas in six districts of Xi’an City using four cooling indicators: park cooling intensity (PCI), park cooling area (PCA), park cooling effect (PCE), and park cooling gradient (PCG). The results showed that 84 out of 94 parks exhibited significant cooling effects, with an average PCI of 1.98 °C, PCA of 51.7 ha, PCE of 6.6, and PCG of 8.2 °C/km. Correlation analyses indicated that the intrinsic park attributes, external buffer zone building height, and building density were the main factors affecting the cooling effect. The park landscape configuration, building height, and density significantly influenced the PCI and PCG, while the park shape and size were crucial for the PCA (positive) and PCE (negative). The optimal park areas for improving the thermal environment were identified as 26 ha (cooling area focus, building density <13%) and 15 ha (cooling intensity focus, building height 32%). This study provides theoretical guidance for planning urban parks and the surrounding areas based on cooling effects, offering insights for future climate resilience planning.

Urban parks are vital for mitigating high urban temperatures, yet optimizing their design for maximum cooling benefits remains a challenge. This study investigates the cooling mechanisms of 65 parks in Tianjin, assessing their characteristics and spatial equity regarding cooling capacity. Results show that 63 parks significantly lower temperatures, with an average Park Cooling Area (PCA) of 45.0 hectares, Park Cooling Efficiency (PCE) of 8.09, Park Cooling Gradient (PCG) of 16.4 °C/km, and Park Cooling Intensity (PCI) of 2.64 °C. Key factors influencing cooling effectiveness include park albedo and nearby water bodies, with optimal albedo values between 3 and 3.6, and water bodies of at least 2.5 hectares enhancing efficiency. Notably, only 38.9% of residents can easily access park cooling services. While neighborhood parks in dense urban areas provide high economic benefits, they serve fewer residents; comprehensive parks cover more people but are less accessible. This study offers new insights into the cooling effects of coastal urban parks, aiding planners in addressing marginalized residents’ needs and enhancing urban resilience amid climate change.