To achieve the goals of “carbon peaking and carbon neutrality”, this paper puts forward the connotation and measurement method for the carbon emission intensity of urban industrial land and conducts an empirical study with the Yangtze River Economic Belt (YREB) as an example. We defined the carbon intensity of urban industrial land as the industrial carbon emissions per unit area of land, which is a spatial mapping of urban industrial economic development and carbon spillover and a key indicator for urban and territorial spatial planning oriented towards the “dual carbon” goal. Findings: The carbon emission density of industrial land in the YREB varied greatly between cities and exhibited significant positive spatial autocorrelation. In addition, the geographical pattern and spatio-temporal evolution model of the urban industrial land carbon emission density had a very complex driving mechanism, and different factors had significant synergistic effects. Therefore, it is suggested that while striving towards the goal of “dual carbon”, the government should incorporate the carbon emission density indicator of urban industrial land into the urban and territorial spatial planning system, and based on the threshold of the medium suitable density, they should design differentiated management policies according to concrete urban policies and encourage cooperation among cities to jointly promote carbon emission management of urban industrial land. In policy design, emphasis should also be placed on highlighting the interactive effects of foreign direct investment, fiscal expenditure, and the number of patent authorizations as well as constructing a combination of policies centered around them to better leverage the impacts of globalization, government intervention, and innovation.

Rurality is an important indicator to reflect the development of villages and reveal internal differences in rural areas. The unbalanced development of transportation infrastructure in the current period of rapid urbanization has become one of the principal elements triggering spatial differences in rurality and changes in rural territorial characteristics. However, there are few studies on the impact of transportation infrastructure accessibility on the multidimensional characteristics of rurality from the perspective of heterogeneity. This paper analyzed the spatio-temporal characteristics of transport accessibility (TA) and the county rurality index (CRI) in Guangdong in 2005, 2010, 2015 and 2020 using an accessibility model and the rurality index and explored the clustering characteristics and interactions of TA and the CRI through exploratory spatial data analysis (ESDA) and geographic weighted regression (GWR) modeling. The findings showed that (1) TA and the CRI in Guangdong were significantly unbalanced in terms of space. The CRI showed a weakening trend in general, forming a distribution pattern of “high in the north and low in the south, high in the west and low in the east”, while TA was on the rise, maintaining a stable pattern of “high in the middle and low in the periphery”. (2) Both TA and the CRI in Guangdong had a Moran’s I value greater than 0.6 during the study period, exhibiting strong spatial agglomeration, while the two showed a significant spatial negative correlation. (3) The influence of TA on the CRI in different dimensions showed dynamic changes in stages, with TA having a higher intensity of effect on society rurality and land rurality in 2005, while on society rurality and industry rurality in 2020. (4) This paper grouped 77 counties in Guangdong into four types of policy zonings—coordination types, lagged types of accessibility, lagged types of rurality and double lagged types—and put forward corresponding development recommendations. The study conducted in this paper contributes to an in-depth understanding of the impact of transportation infrastructure development on the multidimensional characteristics of rurality and provides a basis for policy formulation for coordinated urban–rural development and sustainable rural development.

Intercity railways are key transportation infrastructures in the interconnection of urban agglomerations. Their stations are usually distributed based on densely populated and economically active areas, and they also play roles as regional network nodes, intra-city nodes, and functional areas. However, the academic research on the spatial development of station areas is still very limited. In particular, there is no sufficient in-depth discussion about the coordinated development mechanism of the “regional node-place” and “urban node-place” of intercity railways. Based on the case study of Guangdong–Hong Kong–Macao Greater Bay Area in China (GBA), this paper provides an in-depth analysis of the regional node development level, urban node development level, station area development level, comprehensive station area development level, and coordinated development of “regional node-place” and “urban node-place” in the GBA in 2012, 2016, 2020, and 2023 by constructing a node-place model, development index of regional nodes, development level index, and coupling coordination degree model. Findings: (1) From 2012 to 2023, the development of regional nodes, urban nodes, and places of the GBA intercity railway saw a significant improvement, with the proportion of high-value stations increasing by 13.3%, 7%, and 8.8%, respectively. Despite some improvement on the whole, the three still exhibited an unbalanced spatial distribution of “high in the middle-low in the periphery”; (2) The relative gap in development levels between “regional node-place” and “urban node-place” of intercity railways decreased by 0.159 and 0.168, respectively, showing an overall upward trend, but still showing an unbalanced spatial distribution of “high in the middle-low in the periphery”; (3) The development level of regional nodes and urban nodes is lower than that of areas and is dominated by the unbalance place and dependence types, while the unbalance node and balance types account for less; (4) The coordination of the “regional node-place” and “urban node-place” of intercity railways is gradually improved, and the stations with high coordination and high coordination levels accounts for an increased proportion from 4% to 7% and 8%, respectively. However, the coordination remains at a low level on the whole, with most sites still in the low-level coupling and lower-level coupling stages. Some stations in Guangzhou, Shenzhen, Foshan, and Dongguan have witnessed a level leap and are showing a transition towards a medium to high level of coordinated development, with the surrounding areas moving away from low-level coupling and coordination.