Exploring the spatial pattern and its influencing mechanism of cultural heritage is of great significance for the systematic protection, inheritance and utilization of cultural heritage. In this study, the national-level cultural heritage of China as the research object, and the spatial patterns of the cultural heritage (CH), tangible cultural heritage (TCH) and intangible cultural heritage (ICH) are analyzed are summarized using the multiple geospatial analysis method, and their spatial distribution differences. Then, the optimal parameter geodetector model was further used to analyze the influencing and interaction effect of natural environment (NE) factors, socioeconomic and cultural environment (SCE) factors on the spatial distribution of CH, TCH and ICH, and the interaction mechanism was deeply discussed. The results show that high-density region of CH are mainly located in the southeastern Heihe-Tengchong Line of China, while low-density region are mostly located in the northwestern Heihe-Tengchong Line. In terms of local spatial differences, the spatial distribution of material cultural heritage is different in different river basins, different terrains and different climates. The spatial distribution of ICH mainly shows significant differences in terrain and climate, and does not show significant differences in river basins. In terms of influencing factors, sociocultural environment, education level, historical settlement environment, road traffic, climate, economy, population and terrain factors all have a significant impact on the spatial distribution of CH and TCH. Sociocultural environment, education level, historical settlement environment, road traffic, climate, economy and population have a significant impact on the spatial distribution of ICH, while topographic factors and water system factors have no significant impact on the spatial distribution of ICH. Compared with ICH, TCH is more likely to be directly affected by topographic conditions (altitude, relief of terrain) and hydrological conditions (production and living water sources and flood risk) during its formation stage. At the same time, topographic and hydrological conditions can also indirectly affect the spatial distribution of TCH by directly affecting human agricultural activities, economic activities and cultural activities.

The income imbalance between urban and rural areas has seriously affected social fairness and justice and has become a key factor restricting the sustainable development of the economy and society. The analysis of the spatiotemporal laws and causes of urban-rural income disparity is of great significance to realizing the coordinated and integrated development of regional urban and rural areas. In this study, the coefficient of variation, Theil decomposition index, spatial autocorrelation method and GeoDetector model were used to analyze the spatiotemporal characteristics of the urban-rural income gap and its driving force in the Yangtze River Economic Belt from 2000 to 2017. The results show that the per capita disposable income of urban and rural residents in the study area shows a trend of rapid growth from 2000 to 2017. The urban-rural income gap in the study area showed an inverted "U"-shaped development process as a whole, and the relative difference showed an increasing trend. Regarding the spatial pattern, the study area showed a significant east-west differentiation pattern. The spatial distribution of the urban-rural income gap in the study area has an obvious positive spatial correlation, that is, the phenomena of high-value agglomeration and low-value agglomeration were significant. The economic development level, the industrial structure, the regional development policy, transportation, topographical conditions and resource endowments can strongly explain the spatial differentiation pattern of the urban-rural income gap in the study area. The spatial differentiation pattern of the urban-rural income gap is affected by both natural factors and socioeconomic factors. Among them, socioeconomic factors are the dominant factors, followed by natural factors. There is a significant interaction between natural factors and socio-economic factors, and the combination of socio-economic factors and adverse natural factors can significantly affect the regional urban-rural income gap.

Quantitative assessment can scientifically determine the health status of a regional ecosystem, identify regional eco-environmental problems, and assist in promoting regional sustainable development and environmental management. Taking China’s important ecological function region, the Yellow River affected area as an example, this study constructed an extended evaluation index system based on the pressure-state-response framework, and remote sensing and GIS techniques were used to dynamically evaluate the spatial and temporal characteristics of ecosystem health in the study area. Furthermore, influencing factors on ecosystem health in the study area were extensively analyzed using the GeoDetector model. The results show that the ecosystem health level in the study area shows significant spatial heterogeneity from 1995–2015, and showed a fluctuating change process. Areas with large fluctuations in health level were mainly distributed in extreme climate areas, ecologically fragile areas, on plains and in hilly areas. Spatial differences of ecosystem health were well explained by using the biological abundance index, relief degree of land surface, soil type, annual average precipitation, elevation, annual average temperature, and population density. Influencing factors have significant interactive effects on ecosystem health.