Ecological corridors play a key role in promoting the flow of ecological processes, guaranteeing ecological function services and maintaining biodiversity. Based on ecological sensitivity and ecological service values, ecological corridors in typical karst areas of Ningyuan County were constructed to lay the foundation for ecological environmental protection and land development and utilization in the county. Based on the current land use situation in 2020, the ecological source sites were identified by the combined results of ecological sensitivity evaluation and ecosystem service value analysis, and then potential corridors were generated based on the minimum cumulative resistance model (MCR) and the minimum cost path method, and key corridors were identified by the gravity model. The results show that (1) the areas exhibiting strong sensitivity are concentrated within regions characterized by better ecological environment quality; the ecosystem service value and ecological sensitivity have a similar distribution pattern, and those with high ecological value are mainly distributed in areas with better habitat quality such as woodlands and along water systems. (2) The total area of ecological source land in Ningyuan County is 879.14 km², accounting for 35.15% of the county area, mainly distributed in the south and north of the county. (3) There are nine ecological corridors in Ningyuan County, which are radially distributed in a spider-web manner, five important ecological corridors and four general ecological corridors, with total lengths of 96 km and 120.87 km, respectively.

With the continuous advancement of urbanization and industrialization, non-grain production on cropland (NGPCL) is gradually becoming more widespread. This phenomenon will compress the space for grain production and trigger a global food crisis. How to scientifically understand and effectively control NGPCL has become a scientific issue. This study, conducted at the plot scale, establishes a measurement index for NGPCL and further explores the characteristics and driving mechanisms of NGPCL in mountainous areas. The results indicate the following: (1) Compared to plots for food-growing, plots for non-grain production tend to be more dispersed, with terraces showing the most significant dispersion, while plains exhibit the highest degree of aggregation. (2) In terms of irrigation conditions, irrigated land and dry land are more likely to undergo NGPCL. In terms of topography, slope croplands have the highest probability of being used for NGPCL. (3) Regions with steeper slopes, higher elevations, greater differences in altitude from the settlement, farther distances from settlements and roads, yet closer proximity to forests, are more likely to engage in NGPCL. (4) Different plot characteristics have varying impacts on NGPCL. Plot characteristics primarily affect the costs and returns of grain production, driving farmers to change their production patterns and triggering NGPCL.

Achieving rural revitalization is the aim of building a strong modern socialist country. However, regional heterogeneity exists in rural development in general, and studying regional differences in rural development quality is an important prerequisite for developing specific policies for rural revitalization. This paper takes 20 prefecture-level cities in Guangdong Province as the research objects and constructs a rural-development-quality-evaluation system based on four dimensions: industrial revitalization, rural affluence, social development, and environmental livability; combines the entropy value method, hierarchical analysis method, and TOPSIS to complete the evaluation process; uses a spatial autocorrelation model and cold–hot spot analysis to explore the characteristics of regional heterogeneity of rural development in Guangdong Province; and relies on stepwise regression analysis to clarify the main influencing factors. The results show the following: (1) The average value of rural development quality in the province is 0.342, with “high in the middle and low in the surrounding area” as the main spatial characteristic. (2) The average value of environmental livability dimension is 0.580, and the high-value area is found in the northeastern part of the province. There is an outer circle distribution structure with Dongguan City as the core of the high-value area, and the score gradually decreases outward, while the average value of all other dimensions is less than 0.350. The mean value of all other dimensions is less than 0.350. (3) The social development dimension shows a cold–hot spot distribution of “hot in the northeast and low in the middle”, the rural development quality and other development dimensions show a cold–hot spot spatial pattern of “high value gathering in the middle and low value gathering in the northeast”, and there is no cold spot gathering in the environmental livability dimension. (4) The average collective assets and the construction rate of science-based communities are the main driving factors of rural development, while the coverage rate of service institutions and the Engel coefficient are the main hindering factors. This paper enriches the rural development level measurement system, clarifies the spatial differentiation and main influencing factors of rural development in Guangdong Province, and helps to provide scientific support and a theoretical basis for the differentiated promotion of rural revitalization.

Based on the data regarding the rural population and cultivated land at the county level in Guangdong Province in 2000, 2010 and 2020, this paper analyzes the changes in rural population and cultivated land area at the county level and their spatio-temporal coupling characteristics based on GIS technology and model methods such as the elastic coefficient, and reveals the transformation process of the rural “man–land” relationship in Guangdong Province. The results show that the rural population of Guangdong Province shows a continuous growth trend, and the cultivated land area and per capita cultivated land area show a trend of continuous reduction. From 2000 to 2010, the rural population grew by 1.37% annually, while the cultivated land area and per capita cultivated land area decreased by 0.09% and 1.28% annually, respectively. From 2010 to 2020, the rural population grew by 0.07% annually, while the cultivated land area and per capita cultivated land area decreased by 1.09% and 1.15% annually, respectively. The overall coupling type of rural population and cultivated land change in Guangdong Province presents a trend of mainly maladjusted types and gradually changing to coordinated types. From 2000 to 2010, 70.64% of the counties displayed maladjusted development types. From 2010 to 2020, the number of counties with maladjusted development types decreased, while the proportion of coordinated types increased. The natural environment, economic development level and governmental decision-making behaviors were all driving factors of coupled development of rural population and cultivated land, and the driving mechanisms of different factors have clear spatial differences in different regions of Guangdong Province. The governments and relevant departments should stick to the red line of cultivated protection, make intensive use of cultivated land and improve the livelihoods of farmers. Moreover, the Pearl River Delta, eastern Guangdong, western Guangdong and northern Guangdong should improve the cooperation mechanism for rural revitalization. The study is conducive to providing a scientific basis for rural population and cultivated land utilization management, rural revitalization and new rural construction, and promoting urban–rural integration development under the new situation.

Urbanization is a significant indicator of city progress, and as urbanization advances, carbon emissions exhibit an increasing trend that must not be disregarded. Therefore, it is imperative to thoroughly examine the spatial and temporal variations as well as the factors influencing carbon emissions during the urbanization process. In this paper, based on the 2009–2019 PRD region, carbon emissions are measured from energy consumption, industrial production process, solid waste, and wastewater according to the IPCC coefficients, and spatial and spatial differences in carbon emissions are combined with spatial analysis and the drivers analyzed using the gray correlation scale. The results show that: (1) The total carbon emissions in the PRD region have been increasing over the study period, and the distribution of total carbon emissions shows a pattern of “strong in the east and weak in the west”, with energy consumption accounting for the highest proportion of carbon emissions. (2) The global Moran Index of carbon emissions in the PRD has been decreasing, with low and low clustering concentrated in Shaoguan and Zhaoqing, high and high clustering concentrated in Dongguan and Shenzhen, and low and high clustering concentrated in Shenzhen and Guangzhou, with cold spots mainly concentrated in Zhaoqing and hot spots mainly distributed in Guangzhou, Shenzhen, and Dongguan. (3) The degree of economic growth has a substantial influence on carbon emissions in the PRD cities, and the influence of technical advancement has intensified. Guangzhou City is propelled by low-carbon regulations that have a more equitable influence on all elements. Zhuhai City has a more significant influence on energy intensity, while Foshan City has a more noticeable decrease in the effect of foreign investment. To address the issue of carbon emissions, the government should establish appropriate rules to regulate carbon emissions in areas with high emissions, foster collaborative efforts across cities, and encourage the growth of environmentally friendly enterprises.