Intangible cultural heritage (ICH) reflects a region’s history and culture, serving as a significant indicator of regional identity and cohesion. The Grand Canal Basin in China is rich in historical traditions, containing a rich array of ICH resources. Analyzing the spatiotemporal distribution characteristics and influencing factors of ICH within the Grand Canal Basin of China can provide a scientific basis for developing cultural industries and promoting sustainable regional economic growth. This study employed GIS-based spatial analysis methods, including kernel density estimation, the mean nearest neighbor index, and standard deviation ellipse, to investigate the spatiotemporal distribution of 504 national-level ICH items (including extensions) in the Grand Canal Basin of China. The results demonstrate the significant spatial clustering of ICH, with concentrations in high-density regions, particularly at the northern and southern ends of the canal. There is significant regional disparity in the distribution of ICH, with an uneven quantity and structure, predominantly featuring traditional skills and traditional drama categories. The average centroid shift of ICH exhibits a north-to-south oscillatory trajectory. However, overall, it demonstrates a southward-moving trend. This study also underscores the impacts of urbanization, population density, economic development, and transportation infrastructure on ICH distribution. Among these factors, urbanization exerts the strongest influence on the spatial distribution of ICH. The impact of the natural environment is relatively minor; however, it remains a significant element that cannot be overlooked during development. This research offers valuable data and insights for local governments and institutions to formulate evidence-based strategies for the protection and sustainable utilization of ICH resources, promoting sustainable cultural and economic development in the Grand Canal Basin.

Accurate estimation of terrestrial ecosystem carbon storage and the scientific formulation of ecological conservation and land use policies are essential for promoting regional low-carbon sustainable development and achieving the goal of “carbon neutrality.” In this study, the FLUS–InVEST model was used to evaluate the carbon stocks of the Jiangsu coastal zone in China from 1995 to 2020 and scientifically forecast the changes in carbon stocks in 2030 under three scenarios: natural exploitation, ecological protection, and economic development. The results are as follows: (1) From 1995 to 2020, carbon storage in the coastal zone initially remained stable before declining, a trend closely linked to the accelerated urbanization and economic growth of Jiangsu Province. (2) By 2030, carbon storage under the three scenarios exhibits a pattern of “S1 decrease–S2 increase–S3 decrease,” with a more significant increase in construction land under the natural development and economic development scenarios compared to the ecological protection scenario. (3) The sensitivity of carbon storage to land use changes varies across scenarios. In the natural development scenario, carbon storage is most affected by forest reduction and construction land expansion. In the ecological protection scenario, it is more responsive to increases in non-construction land. In the economic development scenario, the expansion of construction land leads to the most significant decrease in carbon storage. Therefore, when formulating future territorial spatial planning policies and urban development strategies, it is essential to consider ecological protection and economic development scenarios comprehensively, taking into account carbon sequestration capabilities. This approach will ensure effective conservation and restoration of damaged ecosystems while safeguarding the robust development of urban economies and societies.

Analyzing the spatiotemporal evolution characteristics of urban land use and habitat quality is crucial for the sustainable development of urban ecological environments. This study utilizes the land use data of Jiangsu Province for the years 2000, 2010, and 2020, applying the FLUS model to investigate the driving force behind land expansion and to simulate a prediction for the land use of 2030. By integrating the InVEST model and landscape pattern indices, this study analyzes the spatiotemporal evolution characteristics of habitat quality in Jiangsu Province and uses geographical detector analysis to examine the synergistic effects of influencing factors. The results indicate that, from 2000 to 2020, habitat degradation in Jiangsu Province progressively increased, with the spatial distribution of degradation levels showing a gradual change. Under the ecological protection scenario in 2030, habitat fragmentation was alleviated. Conversely, under the economic development scenario, habitat quality further deteriorated, resulting in the largest area of low-quality regions. Minimal changes occurred under the natural development scenario. (2) The landscape indices in Jiangsu Province experienced significant changes from 2000 to 2020. The continuous expansion of urban land into other land use types led to a trend of fragmentation, with a clear increasing trend in dispersion, sprawl, and Shannon’s diversity index, accompanied by a decrease in cohesion. (3) The dominant interacting factors affecting habitat quality were combinations of socioeconomic factors with other factors, indicating that the economy largely determines the spatial distribution pattern of habitat quality. The findings of this study provide optimization strategies for future spatial planning of land use types in Jiangsu Province and offer references for habitat quality restoration efforts in the region.

This study integrates the analysis of surface temperature data with natural and anthropogenic factors closely related to the urban thermal environment in Nanjing from 2000 to 2020, exploring the spatiotemporal variation characteristics of the urban heat island effect and the interactive relationships among its influencing factors. The research findings are as follows: (1) Between 2000 and 2020, the urban heat island effect in Nanjing exhibited an expansion trend radiating from the city center to the periphery, with the heat island phenomenon primarily concentrated in the old urban areas characterized by developed commerce, industry, and dense populations. Surface temperatures gradually decreased from the city center to the suburbs, forming a distinct spatial distribution gradient. Both the standard deviation ellipse and the centroid of high-temperature areas showed a southward shift. (2) Significant differences in surface temperatures were observed across different land use types, with built-up areas and arable land maintaining relatively stable and higher surface temperatures, while water bodies and forests exhibited lower and stable surface temperatures. (3) Vegetation coverage, normalized water body index, elevation, dispersion, and the Shannon diversity index were negatively correlated with surface temperature, while the normalized difference bare land index, building index, dispersion index, and patch cohesion index were positively correlated with surface temperature. In Nanjing, the interactive effects of dual factors on the urban heat island effect were found to be greater than those of individual factors, with vegetation coverage identified as the most critical factor affecting surface temperature. Considering multidimensional factors together enhances the understanding of the spatial patterns and causes of the urban heat island effect, clarifies the interrelationships and degrees of influence among natural, socio-economic, and landscape pattern factors, and provides a scientific basis for improving the quality of the living environment in Nanjing.

Automated external defibrillators (AEDs) are portable emergency medical devices critical for resuscitating individuals experiencing sudden cardiac arrest. The installation of AEDs in public spaces is essential for enhancing society’s emergency response capabilities. However, many cities in China currently face issues such as inadequate AEDs deployment and uneven distribution. This study aims to explore a rational layout plan for AEDs through systematic site optimization. Initially, this paper evaluates the current spatial configuration of AEDs in the central urban district of Nanjing using various spatial analysis methods. Subsequently, a coverage model is constructed to simulate the coverage capacity of potential emergency needs for new facilities, and a genetic algorithm is utilized to solve it. Finally, an AED site selection experiment is conducted, and the site selection results are discussed and analyzed in conjunction with practical conditions. The research conclusions are as follows: (1) AED distribution in Nanjing’s central urban district is clustered, with some areas lacking facilities, and the coverage rate of AEDs within 100 m and 200 m ranges is relatively low, particularly across different types of venues; and (2) the optimization experiment, with 90 new site selection points, effectively addressed AED distribution gaps, significantly improved coverage, and ameliorated the overall distribution across various public venues. This study provides a scientific basis for the rational placement of AEDs in urban public spaces through systematic analysis and optimization experiments. It enhances the efficiency of current AED deployment in the main urban areas of Nanjing and offers significant insights for the optimization of urban emergency resource allocation.

With the severe challenges resulting from global climate change, the role of land use/land cover (LU/LC) optimization in mitigating carbon emissions and promoting carbon cycle balance has gained increasing attention. This study takes Jiangsu Province as a case study, analyzing the changes in LU/LC from 1995 to 2020 and their impacts on carbon emissions and carbon storage. For Jiangsu Province’s five development scenarios in 2030 (business-as-usual, carbon emission, carbon storage, and carbon neutrality scenarios), objective functions and constraints were constructed. The PLUS model was employed to simulate land use for 2030, predicting carbon storage, economic benefits, and ecological benefits under each scenario and evaluating the impact of each scenario on achieving carbon peaking and carbon neutrality goals. The findings indicate that (1) from 1995 to 2020 there were great changes in land use types in Jiangsu Province, with an overall downward trend in carbon storage. (2) The simulated land use quantity structure and spatial patterns for 2030 under different scenarios exhibited significant differences. Compared with the Business-as-Usual Scenario, the other four optimized scenarios achieved a better balance between economic and ecological values. (3) The Integrated Scenario realized optimal synergy between farmland protection, ecological expansion, and economic output, representing the best compromise under multiple objectives.