More and more studies on land transfer prices have been carried out over time. However, the influencing factors of the industrial land transfer price from the perspective of spatial attributes have rarely been explored. Selecting 25 towns as the basic research unit, based on industrial land transfer data, this paper analyzes the influencing factors of the price distribution of industrial land in Dingzhou City, a rural land system reform pilot in China, by using a geographically weighted regression (GWR) model. Eight evaluation factors were selected from five aspects: economy, population, topography, landform, and resource endowment. The results showed that: (1) Compared with the traditional ordinary least squares (OLS) model, the GWR model revealed the spatial differentiation characteristics of the industrial land transfer price in depth. (2) Factors that have a negative correlation with the industrial land transfer price include the proportion of cultivated land area and distance to the city. Factors that have a positive correlation with the industrial land transfer price include the population growth rate, economic growth rate, population density, and number of hospitals per unit area. (3) The results of GWR model analysis showed that the impact of different factors on the various towns of different models had significant spatial differentiation characteristics. This paper will provide a reference for the sustainable use of industrial land in developing countries.

Integrated development in urban and rural areas has led to a new form of urban–rural interdependence, which promotes rural territorial functional evolution and land use changes. Rural land use transition, showing the synchronous development between cities and villages, is an important window through which to observe integrated development in urban and rural areas. We focus on uncovering the association between rural land use transition and urban–rural integration development (URID), put forward a dynamic relationship assumption between rural land use transformation and URID stages based on the transmission mechanism of urban–rural linkages, and undertake empirical analysis using the panel regression model with the data of county-level administrative units in Shandong Province, China. The results show that rural land use transition has maintained a close association with URID, and that the changes in cultivated land, forest land, and surface-water area are highly related to URID. There are different leading urban–rural linkages in rural areas around big-sized cities, mid-sized cities, and small-sized cities, which determine whether rural areas are in different URID stages of high, medium, or low levels. Further, rural areas can take different actions to promote URID at different stages through strengthening or introducing urban–rural linkages driven by economies of scale and deepening urbanization. This provides a reference for developing countries to formulate rural land use policies on achieving the goal of URID.

Rurality highlights the intrinsic differences between urban and rural communities. The comprehensive rurality evaluation index system is difficult to obtain indicators that reflect purely rural or urban characteristics; in addition, most of the data used in the evaluation index system come from statistical data, and the authenticity of the data cannot be guaranteed. Taking 25 towns in Lixia County and Shanghe County in Jinan city as the study area and using land use data and economic statistics data, the rurality evaluation system based on the land use transformation was constructed, the changes of the rurality index and intensity from 2009 to 2015 were calculated, and the driving factors of the rurality were analyzed. The results showed that, from 2009 to 2015, the rurality difference among towns in Lixia County decreased, the rurality difference among towns in Shanghe County increased, the rurality intensity of Lixia County was lower than that of Shanghe County, and the rurality index gap between the two counties was increasing. In 2009, the rurality grade of Lixia County was dominated by weak intensity (84.62%), and the rurality of the county changed greatly in 2015, with a large proportion (76.92%) still being weak intensity. In 2009, the proportion of relatively strong intensity was dominated (33.33%) in Shanghe County; in 2015, weak intensity accounted for a large proportion (41.67%). Changes of rurality intensity in Lixia County and Shanghe County were different. There was a significant correlation between the rurality index and geographical elevation, GDP, and the distance from the center of the town government, the road construction level, the urbanization level, and the education level. This paper can provide an empirical reference for rurality index research.

Taking the Bohai Economic Rim as the research area and 44 prefecture-level cities as research objects, on the basis of deepening the connotation of urban land use morphology, we constructed a multi-dimensional indicator system for urban land use transition based on the dominant and recessive morphologies of land use. The patterns of change and transition type are described by single-morphology and comprehensive morphology indices, respectively, while a decoupling elastic coefficient model was used to analyze the coupling relationship and evolution process between the dominant and recessive morphologies of urban land use. The results showed the following: (1) From 2000 to 2020, the single-morphology and comprehensive morphology indices of urban land use in the Bohai Economic Rim both improved, to a certain extent. Overall, the transition types of dominant and recessive morphologies of urban land use showed a development trend, in which the degree of recessive morphology transition was higher than the degree of dominant morphology transition, and the spatial difference of its distribution pattern was obvious. (2) From 2000 to 2020, the type of coupling relationship between the dominant and recessive morphologies of urban land use in the Bohai Economic Rim experienced an evolution, from a single-morphology recession decoupling to a single-morphology leading positive hook. The whole region was in the benign development stage of close coupling, where the degree of transition showed the spatial characteristics of Beijing–Tianjin–Hebei > Liaodong Peninsula > Shandong Peninsula. (3) Differences in the economic levels and urbanization processes of different cities led to different paths, speeds, and degrees of urban land use transition, showing stable, volatile, and non-transition paths. The direct influence of different influencing factors, as well as their potential effects, drive the dominant and recessive morphologies of urban land use to grow, in terms of coupling and synergy, promoting the realization of urban land use transition.

In response to the challenges of rural chronic poverty caused by insufficient self-development ability, establishing a development model conducive to poverty alleviation and stimulating rural development potential have become core tasks of deepening rural revitalization. Resources and environment play an important role in invigorating rural vitality. Based on symbiosis theory, we have constructed a new conceptual framework to analyze dynamic performance of rural areas in population, industry and facilities, and dynamic constraints in resources and environment. Using an improved TOPSIS evaluation method and panel Tobit model, we have selected 106 rural revitalization model towns from Shandong province as research samples, empirically analyzed the performance of rural vitality and its resources and environment constraints, explored differences of rural vitality performance and vitality constraints of different village types, and put forward long-term mechanisms to maintain rural vitality. Results show that from 2012 to 2019, rural vitality of rural revitalization model towns in Shandong province was gradually improved, among which industrial development had contributed the most; agriculture-tourism towns are more dynamic than industrialized agriculture towns and characteristic agricultural towns. Through analysis of resources and environment constraints on rural vitality, we found that resources had the greatest impact on rural vitality, and the short-term constraints of total amount restriction on rural vitality were not obvious; binding force of ecological environment on rural vitality changed from weak to strong and increasingly became the bottleneck restricting rural vitality. We have further proposed a long-term mechanism to stimulate rural vitality from the aspects of promoting comprehensive utilization of rural residential land, strengthening concept of ecological priority and green development, taking the road of urban–rural integration, and promoting integrated development of rural industries.