Comparative Changes of Influence Factors of Rural Residential Area Based on Spatial Econometric Regression Model: A Case Study of Lishan Township, Hubei Province, China

Spatial and temporal distribution of rural settlements and influencing mechanisms in Inner Mongolia, China

Revealing the patterns and influencing mechanisms of spatial and temporal distribution of rural settlements is crucial for rural revitalization and sustainable development. However, our limited understanding of the rural settlements in China’s ethnic minority border areas has hindered the process of their agricultural and rural modernization. Based on data on rural settlements in Inner Mongolia, China in four periods between 1990 and 2020, this study reveals its spatial and temporal distribution characteristics and describes the dynamic transformation process of settlement. Using a geographical detector approach, 17 factors are explored to identify the influencing mechanisms of each factor on the distribution of rural settlements in different regions. The results show obvious regional differences in the spatial distribution of rural settlements in Inner Mongolia, with the largest kernel density values in the west (Hetao irrigation area) and higher kernel densities in the central (Hohhot) and the east (Chifeng and Tongliao). While rural population decreases, rural settlements expand into cultivated land, grassland, and unused land resources. Its spatial distribution is significantly influenced by the factors of distance to cultivated land, distance to towns, and population density. The east of the study area is mainly controlled by temperature, while vegetation type and vegetation coverage have a greater impact in the west. The interactions between two influencing factors possess bilinear or nonlinear enhancement relationships. This study enriches the understanding of the rural settlements in ethnic minority border areas, which provide reference for the improvement of rural human settlement environment in Inner Mongolia.

Theoretical Development Model for Rural Settlements against Rural Shrinkage: An Empirical Study on Pingyin County, China

China’s rural areas face population loss and expanded residential land in the context of rapid urbanization. The increasing hollowing of villages leads to extensive land use, making it necessary to optimize and consolidate rural settlements immediately. Therefore, how to choose an appropriate development model for rural settlements is at issue. This article builds a theoretical development model for rural settlements based on their primary development conditions and spatial patterns. It determines the development model according to the classification matrix formed by interweaving different elements in each dimension. Finally, it demonstrates the model through a case study on Pingyin County, China. The empirical findings for Pingyin County are as follows. (1) The scale of rural settlements increased from 2010 to 2020, and the agglomeration and spatial correlation intensified, but they tended to be irregular. (2) The various elements of the development foundation showed apparent spatial differentiation, and the spatial distribution of rural settlements at different levels presented a core–edge structure. (3) The development of rural settlements was reduced to six models: in-situ urbanization, satellite urbanization, competitive-industry-driven, characteristic-tourism-driven, modern-agriculture-driven, and village relocation. Finally, the article proposes different development paths for different development models.

The Spatial-Temporal Characteristics of Cultivated Land and Its Influential Factors in The Low Hilly Region: A Case Study of Lishan Town, Hubei Province, China

Cultivated land is a basic resource that is related to the sustainable development of the global economy and society. Studying the spatial and temporal distribution of cultivated land and its influential factors at the township scale is an important way to improve its sustainable use. Based on the land use data in 2009 and 2015, this paper comprehensively uses kernel density estimation, spatial autocorrelation analysis, and the spatial autoregressive model to analyze the spatial distribution characteristics and influential factors of cultivated land. The results show that in 2009 and 2015, the maximum kernel density of cultivated land in Lishan Town was 31/km2 and 38/km2, respectively, and there is an increasing tendency for it in the future. The global spatial autocorrelation Moran’s I of the proportion of cultivated land area in the administrative villages of Lishan Town in 2009 and 2015 was 0.5251 and 0.3970, respectively. Cultivated land has significant spatial self-positive correlation agglomeration characteristics in spatial distribution. Based on spatial error model (SEM) analysis, the regression coefficients of the village were 0.236 and 0.196 in 2009 and 2015, respectively. The regression coefficients of the road were 0.632 and 0.630, respectively. The regression coefficients of the water system were 0.481 and 0.290, respectively. The regression coefficients of the topographic position index were −0.817 and −0.672, respectively. By comparing 2015 with 2009, the regression coefficients of each influential factor have been reduced to varying degrees.

Valuing Environmental Amenities in Peri-Urban Areas: Evidence from Poland

Ecosystems provide services that contribute to the well-being of people living within a city’s borders and on the urban–rural fringe. While benefits from green areas in urban settings are well investigated, peri-urban areas are significantly less addressed by researchers than cities. This study aims to evaluate the importance of environmental amenities in peri-urban areas using the hedonic pricing method to assess people’s willingness to pay for environmental goods and services. A local regression model (geographically weighted regression) and two global regression models (generalized spatial two-stage least squares and ordinary least square) are used to identify the spatial patterns and level of influence of protected areas, forests, rivers, trees, and landscape diversity. This paper includes the Central European case study example of a peri-urban area of the city of Wroclaw, Poland. The results from the three models show that out of all of the environmental amenities included in this study, proximity to protected areas—such as Natura 2000 sites and landscape parks—and the diversity of land-use patches within the 500-m radius around the sites exert the strongest influence on plot prices. The overall impact of environmental amenities on vacant plot prices in peri-urban areas is low or, as in the case of river and streams, not significant. The results of the analysis reveal the preferences of the new peri-urban inhabitants concerning green spaces that have an effect on the real estate market in Poland.

Spatiotemporal Variation and Inequality in China’s Economic Resilience across Cities and Urban Agglomerations

Economic resilience is a critical indicator of the sustainable development of an urban economy. This paper measures the urban economic resilience (UER) of 286 major cities in China from six indicators—economic growth, opening up, social development, environmental protection, natural conditions, and technological innovation—using a subjective and objective weighting method and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods. Furthermore, kernel density estimation (KDE) was used to reveal the spatial and temporal trends in UER across cities, and a social opportunity function was applied to access the opportunity for economic resilience and the fairness of opportunities for economic resilience in 19 urban agglomerations in China. The results show that the UER was, in general, low across all cities but increased over time. Geographically, the UER disperses from the eastern coast to inland cities. Amongst urban agglomerations in China, the economic resilience opportunity index also varies spatially and increases over time. On the other hand, the opportunity fairness index of UER remained largely stable and substantial inequalities exist across all urban agglomerations, indicating the need for differentiated policy intervention to ensure equality and the sustainable development of the region. The methodology developed in this research can also be applied in other cities and regions to test its re-applicability and to understand the UER in different contexts.