This study provides an empirical examination of the design and modification of China’s urban social security programme. In doing so, this study complements the popular assumption regarding the correlation between economic growth and social security development. Focusing on the economic and political motivations behind the ruling party’s decision to implement social security, this study first discusses the modification of urban social security and welfare in China. It then empirically demonstrates the mechanisms behind the system’s operation. This study proposes the following hypothesis: in a country like China, a change in the doctrine of the ruling party will affect government alliances, negating the positive impact of economic growth on the development of social security. In demonstrating this hypothesis, this study identifies a political precondition impacting the explanatory power of popular conceptions of social security development.

Based on the research on 31 provincial-level administrative regions at the end of 2022, we used the geographic concentration index, geographic imbalance index, SPSS and ARCGIS spatial analysis techniques to study the spatial distribution, distribution factor correlation, and accessibility of national 5A-level scenic spots. The research results show that the overall distribution of my country's 5A-level scenic spots is unbalanced, with a low degree of concentration, showing a pattern of denseness in the east and sparseness in the west, with large inter-provincial differences. The density of traffic highways is positively correlated with the distribution density of 5A-level scenic spots. The traffic lines in the central and eastern regions are dense, and there are a large number of 5A-level scenic spots, especially the Beijing-Tianjin-Hebei region, the Yangtze River Delta region, and the middle and lower reaches of the Yangtze River and Yellow River. Therefore, the spatial distribution of China's 5A-level tourist attractions is mainly affected by the interaction of economic, transportation and social factors, among which GDP, transportation network and attraction of scenic spots are the most critical factors. These research results can provide a reference for optimizing the spatial layout of China's scenic resources and promoting regional socio-economic development.

The danger of riverbed processes is considered. Their speed varies from the first few months of the flood to the most dynamic process in nature. It happened in front of people. This may make life on the river bank and the utilization of river resources more difficult. This paper introduces the causes and consequences of the danger performance of riverbed processes, and focuses on the mapping methods of the danger assessment of riverbed processes: determining the danger degree of riverbed processes and different methods of displaying it on the map. An example of displaying danger on the previously drawn map is given, and the distribution of different types and expression degrees of dangerous riverbed processes under various natural conditions in Russia is briefly analyzed.

Based on the population change data of 2005–2009, 2010–2014, 2015–2019 and 2005–2019, the shrinking cities in Northeast China are determined to analyze their spatial distribution pattern. And the influencing factors and effects of shrinking cities in Northeast China are explored by using multiple linear regression method and random forest regression method. The results show that: 1) In space, the shrinking cities in Northeast China are mainly distributed in the “land edge” areas represented by Changbai Mountain, Sanjiang Plain, Xiaoxing’an Mountain and Daxing’an Mountain. In terms of time, the contraction center shows an obvious trend of moving northward, while the opposite expansion center shows a trend of moving southward, and the shrinking cities gather further; 2) in the study of influencing factors, the results of multiple linear regression and random forest regression show that socio-economic factors play a major role in the formation of shrinking cities; 3) the precision of random forest regression is higher than that of multiple linear regression. The results show that per capita GDP has the greatest impact on the contraction intensity, followed by the unemployment rate, science and education expenses and the average wage of on-the-job workers. Among the four influencing factors, only the unemployment rate promotes the contraction, and the other three influencing factors inhibit the formation of shrinking cities to various degrees.

The smallest administrative unit of the sixth national census-township (town) is selected as the basic unit, the population spatial distribution characteristics at the township (town) level in karst mountainous areas of northwest Guangxi are analyzed by using Lorenz curve and spatial correlation analysis method, and the influence intensity of natural factors on regional population spatial distribution is detected by using geographic detector method. The results show that: 1. the spatial distribution of population at the township (town) level has the characteristics of imbalance, showing generally significant positive correlation and certain aggregation; 2. There are significant differences in the impact of the spatial distribution of various natural factors on the population distribution. For the towns without karst distribution in the northwest and central south of the study area, the population density increases with the increase of factors conducive to human residence, but the average population density is only 79 people/km². In the towns with karst distribution in the East and south, the spatial distribution of population density and natural factors is not a simple increase or decrease relationship, but fluctuates with the change of karst distribution area. 3. The factor detection results of the geographic detector show that the altitude has the greatest impact on the spatial distribution of population. The interactive detection results show that the impact intensity of any two natural factors after superposition and interaction presents nonlinear enhancement and two factor enhancement. It can be seen that the karst mountain area in northwest Guangxi is similar to other areas. Altitude is one of the main factors affecting the spatial distribution of population, but the river network density and unique geological landform of karst mountain area have a strong catalytic effect on the spatial distribution of population. The superposition and interaction with other factors can further strengthen the impact on population distribution.

Using the rank scale rule, taking 47 major port cities in China from 2001 to 2015 as research samples, this paper discusses the rank scale characteristics and hierarchical structure of coastal port city system from a multi-functional perspective, and divides the coupling type of multi-functional development based on shipping logistics. The research shows that: 1) from 2001 to 2015, the scale-free area of manufacturing function order scale distribution in the coastal port city system appeared bifractal structure, the hierarchical segmentation characteristics appeared, and the other functions were single fractal; From the perspective of long-term evolution, only the order and scale distribution of shipping logistics function has developed from centralization to equilibrium, while the business function, manufacturing function (scale-free region I), modern service function and population distribution function are in a centralized situation. 2) The hierarchical structure of coastal port city system has gradually changed from pyramid structure to spindle structure, and generally formed five levels: national hub, regional hub, regional sub center, regional node and local node. 3) From the perspective of multi-functional coupling types, the traditional functions of port cities are generally ahead, while the high-end service functions lag behind, and the improvement speed of urban functions is slow and tends to be flat, indicating that the multi-functional development of China’s coastal port cities is still at a low level, and the industrial system structure needs to be further optimized. 4) From the perspective of port cities at different levels, the functions of regional hub cities and regional sub central cities are in the stage of rapid growth; regional and local node cities are still in the growth stage of traditional functions such as industry and commerce.