Cities and the countryside have long been an inseparable organic whole. China’s new model of high-quality urbanization requires integrated urban and rural development and rural vitalization. Problems inherent to urban areas are caused by problems inherent to rural areas, and vice versa. Such problems are closely linked, and the compound each other to create “urban-rural problems.” As such, rural vitalization is necessary to prevent problems associated with growing cities, and the new model of urbanization is required to prevent problems in rural areas. Based on a review of domestic and foreign research on integrated urban and rural development, this study analyzes the root causes of persistent urban and rural problems and their counterposing patterns on a theoretical level; analyzes the main factors and driving mechanisms as well as the underlying pattern and sustainability of integrated urban and rural development; constructs a measurement test for integrated urban and rural development; and proposes a triangular model of integrated urban and rural development. It confirms that China’s integrated urban and rural development is in the late period of urbanization, which features a high degree of integration and more urban areas and fewer rural areas. Subsequently, it will enter the final period of urbanization and a stage of deep integration, with more urban and fewer rural areas. In the future, it will be necessary to implement a strategy of deeply integrated urban and rural development and use new urbanization and rural vitalization to solve urban-rural problems and improve the quality of urban and rural development. New theories and methods of integrated urban and rural development will need to be created and an evaluation system to judge quantitatively the depth of integrated urban and rural development will need to be established, in order to create desirable urban and rural areas. Future efforts should aim to develop greater synchronization, deeper integration, and mutual success between the new model of urbanization and rural vitalization, so as to improve the high-quality development of, and modernize, both urban and rural areas.
This study analyzes cities in China at the prefecture level and above to calculate indices for “urban economic efficiency” (the relationship between input factors and output) and “urbanization economic efficiency” (the relationship between newly increased output and increased economic input), based on the Stochastic Frontier Analysis (SFA) method. We compare and analyze the factors influencing change and their spatial distributions. The results show that capital and labor rather than urban land could effectively improve urban and urbanization economic efficiency. And, although the proportion of wages to GDP has a significant negative impact on urban economic efficiency, for social equity and stability, the proportion should be increased; if appropriate, it would not significantly reduce urbanization economic efficiency. Additionally, population density, population urbanization rate, and government fiscal expenditure significantly positively impact urban and urbanization economic efficiency. However, we also found that increases in the degree of industrial structure deviation and urban landscape fragmentation are harmful to urbanization economic efficiency. In terms of spatial distribution, the urbanization economic efficiency of most of China’s northeastern and eastern coastal areas is significantly lower than that of other regions; at the same time, the urban economic efficiency of most of these cities has been decreasing, especially in the northeast, which warrants greater policy attention.
Development zones are important growth poles for promoting regional economic development. However, the spatiotemporal relationship between development zone construction and urban land growth is still unclear. This paper analyzes the spatiotemporal changes of national-level development zones (NDZs), approximately 219 national economic development zones, and 156 high-tech development zones during 1990-2018 in China. The impact of development zone establishment on the growth of surrounding urban land was quantitatively explored using circle buffering analysis and time series comparative analysis. The results show that China’s NDZs spread from the southeast coast to the inland area from 1990 to 2018, and the establishment of the development zones has an obvious promoting effect on the surrounding urban land growth. The scope and intensity of influences of the development zone established in different periods present distinct nonstationarity in space and time. Overall, the impact on urban land (IU) of China’s NDZs established in different years was mostly highest at the 100 m buffer zone radius, while the slope of the IU was mostly negative, which meant that the 100 m buffer zone radius of the development zone center was the most efficient scale to promote urban land growth. In the meantime, the curve of IU of NDZs established before 1990, during 1996-2000 and 2001-2005 has a clear inflection point, which indicates that the most efficient scales of NDZs established before 1990, during 1996-2000, and 2001-2005 are 1300 m, 900-1000 m, and 800 m, respectively. NDZs established in other periods do not have the most obvious efficient scale. The development zone played the greatest role in promoting urban land growth from 2000 to 2010. Three association modes, including post-growth, pre-growth and steady-growth, were identified based on the differences in geographical location, establishment time, and type of development zones. We quantitatively identify the impact of the growth pole of NDZs on urban land growth from the perspective of spatiotemporal evolution. The findings would provide decision-making support for optimizing the spatial relationship between development zone construction and urban land growth.
The spatial relationships between traffic accessibility and supply and demand (S&D) of ecosystem services (ESs) are essential for the formulation of ecological compensation policies and ESs regulation. In this study, an ESs matrix and coupling analysis method were used to assess ESs S&D based on land-use data for 2000, 2010, and 2020, and spatial regression models were used to analyze the correlated impacts of traffic accessibility. The results showed that the ESs supply and balance index in the middle reaches of the Yangtze River urban agglomeration (MRYRUA) continuously decreased, while the demand index increased from 2000 to 2020. The Gini coefficients of these indices continued to increase but did not exceed the warning value (0.4). The coupling degree of ESs S&D continued to increase, and its spatial distribution patterns were similar to that of the ESs demand index, with significantly higher values in the plains than in the montane areas, contrasting with those of the ESs supply index. The results of global bivariate Moran’s I analysis showed a significant spatial dependence between traffic accessibility and the degree of coupling between ESs S&D; the spatial regression results showed that an increase in traffic accessibility promoted the coupling degree. The present results provide a new perspective on the relationship between traffic accessibility and the coupling degree of ESs S&D, representing a case study for similar future research in other regions, and a reference for policy creation based on the matching between ESs S&D in the MRYRUA.
Urbanization has caused significant landscape changes in rural areas, leading to the emergence of urbanized landscapes (ULs), which have been generally criticized by authorities and professionals. However, perceptions of ULs among local residents have rarely been studied. In this study, we chose five typical categories of ULs from rapidly transforming villages in Fujian Province, China - hardened water bank (HWB), big pavilion (BPA), big memorial arch (BMA), big ornamental lawn (BOL), and big square (BSQ) to do the study. We identified how these ULs were rated and ranked by on-site surveys, as well as how related aesthetic and multifunctional landscape characters (LCs) played a role. The results (N=550) showed that 1) residents supported the construction of ULs, and the most preferred category was that with the most natural elements (BOL) that was simultaneously well maintained. 2) For the residents, the longer they had resided in the village and the fewer connections they had with the city, the more in favor they were of the ULs, and the more eager they were for landscape change. In addition, residents with higher education and Communist Party of China membership valued the naturalness related LCs more highly. 3) Two contradictory preference features, naturalness and livability, should be well coordinated and balanced to construct an improved favorable village for the residents, to realize a balanced and sustainable development path. This study makes great theoretical contributions to landscape research and provides new insights into rural planning and construction.
Using the system dynamics simulation software Vensim PLE, we built a model to simulate the development of resilient human settlement in Changsha. This model includes five subsystems: living, economy, society, ecology and engineering. The model simulates various scenarios, based on different parameter settings to predict the trend of human settlement from 2019-2040 in Changsha. It puts forward four development programs under different simulation scenarios. The results show that the current system of human settling lacks self-regulation and feedback, where simple increases in the economy and urbanization cannot drive the internal system to progress positively. In contrast, the resilient human settlement program is more reasonable and scientific, up to the year 2040, the production, living and ecological environment of residents will be markedly improved in terms of per capita disposable income, per capita floor space and medical insurance coverage; these will increase by 98.9%, 39.7%, and 170.7%, respectively. This system of developing resilient human settlement provides feedback according to the internal relation loops and thus drives itself to adjust and recover, achieving harmonious and sustainable development. In the forthcoming development, we should take the initiative to optimize economic development and upgrade industrial structures, establish emergency plans and response mechanisms to enhance human quality of life.
Geomorphic dynamics of alluvial rivers in response to upstream damming have substantial impacts on navigation, habitat protection, and channel stability. The purpose of this study was to determine how flow and sediment regimes, and meander characteristics affect the morphological adjustment of bends in the Lower Jingjiang Reach (LJR) before and after the Three Gorges Project (TGP). Based on detailed field measurements and hydrological and topographic datasets from 1991 to 2016, banks and point bars morphodynamics of 12 continuous bends in the LJR were comprehensively analyzed. Point bars in the LJR mainly experienced a net deposition before the TGP operation, but substantially deteriorated with a net erosion rate of 4.6 million m3 yr?1 in the post-TGP periods (2003-2016), and erosion on heads and upstream margins of point bars was a general adjustment pattern in the 12 bends. The most significant morphological changes of point bars and banks occurred in 2006-2011, indicating a delayed response of the channel evolution of the LJR to damming. Detailed observations suggested that the medium discharges (16,000-18,000 m3 s?1) were the most contributive discharges in shaping the morphology of point bars and banks in the LJR after damming. In addition, we revealed the importance of sediment supply on meander deformation of the LJR, driven by sediment exchange over point bars, and more upstream planform deformation tended to occur in bends with high sinuosity (>2.0) in the LJR after damming. The relationship between meander deformation and sinuosity was manifested through the geometric adjustment range of point bars. The morphological adjustments of point bars in the highly curved or compound bends of the LJR were more conducive to cause flow deflections, leading to form concave-bank bars after the TGP operation.
Alluvial fans are an important land resource in the Qinghai-Tibet Plateau with the expansion of human activities. However, the factors of alluvial fan development are poorly understood. According to our previous investigation and research, approximately 826 alluvial fans exist in the Lhasa River Basin (LRB). The main purpose of this work is to identify the main influencing factors by using machine learning. A development index (Di) of alluvial fan was created by combining its area, perimeter, height and gradient. The 72% of data, including Di, 11 types of environmental parameters of the matching catchment of alluvial fan and 10 commonly used machine learning algorithms were used to train and build models. The 18% of data were used to validate models. The remaining 10% of data were used to test the model accuracy. The feature importance of the model was used to illustrate the significance of the 11 types of environmental parameters to Di. The primary modelling results showed that the accuracy of the ensemble models, including Gradient Boost Decision Tree, Random Forest and XGBoost, are not less than 0.5 (R2). The accuracy of the Gradient Boost Decision Tree and XGBoost improved after grid research, and their R2 values are 0.782 and 0.870, respectively. The XGBoost was selected as the final model due to its optimal accuracy and generalisation ability at the sites closest to the LRB. Morphology parameters are the main factors in alluvial fan development, with a cumulative value of relative feature importance of 74.60% in XGBoost. The final model will have better accuracy and generalisation ability after adding training samples in other regions.
Against the background of global warming, environmental and ecological problems caused by frozen ground degradation have become a focus of attention for the scientific community. As the temperature rises, the permafrost is degrading significantly in the frozen ground region of northeast China (FGRN China). At present, research on FGRN China is based mainly on data from meteorological stations, and the research period has been short. In this study, we analyzed spatial and temporal variation in the ground surface freezing index (GFI) and ground surface thawing index (GTI) from 1900 to 2017 for FGRN China, with the air freezing index (AFI) and air thawing index (ATI) using the University of Delaware (UDEL) monthly gridded air temperature dataset. The turning point year for annual mean air temperature (AMAT) was identified as 1985, and the turning point years for GFI and GTI were 1977 and 1996. The air temperature increased by 0.01 ℃ per year during 1900-2017, and the GFI and GTI increased at rates of -0.4 and 0.5 ℃ d per year before the turning point year; after the turning point, these rates were -0.7 and -2.1 ℃ d per year. We utilized a surface frost number model to study the distribution of frozen ground in FGRN China from 1900 to 2017. When the empirical coefficient E value is 0.57, the simulated frozen ground distribution is basically consistent with the existing frozen ground maps. The total area of permafrost in FGRN China decreased by 22.66×104 km2 from 1900 to 2017, and the permafrost boundary moved northward with obvious degradation. The results of this study demonstrate the trend in permafrost boundary degradation in FGRN China, and provide basic data for research on the hydrological, climate, and ecological changes caused by permafrost degradation.
Understanding climatic effects on cropland water use efficiency at different elevations is imperative for managing agricultural water and production in response to ongoing climate change in climate-sensitive areas with complex topography, such as southwestern China. We investigated climatic effects on cropland water use efficiency in southwestern China at each 100-m elevation bin during 2001-2017. The maximum water use efficiency was 1.71 gC kg-1 H2O for the 1900-1999 m elevation bin under the growing season temperature and precipitation of 14.58±0.32°C and 965.40±136.45 mm, respectively. The water use efficiency slopes were dominated by the evapotranspiration slopes at elevations below 1999 m but were controlled by the gross primary productivity slopes at elevations above 2000 m. This difference was caused by the substantial responses of evaporation to climate change at lower elevations and the increased climatic sensitivity of gross primary productivity at higher elevations. In comparison to those at other elevations, croplands at lower elevations were more vulnerable to extreme drought because of the dominant role fluctuating evapotranspiration played in water use efficiency. The findings will improve cropland water management in the study area.
The precision remediation and redevelopment of contaminated sites are crucial issues for improving the human settlement and constructing a beautiful China. Three-dimensional delineation of soil pollutants at contaminated sites is a prerequisite for precision remediation and redevelopment. However, a contaminated site is a three-dimensional complex system coupling multiple spatial elements above- and under-ground. The complexity incurs high uncertainties about the three-dimensional delineation of soil pollutants based on sparse borehole and spatial statistics and inference models. This paper first systematically reviewed the objectives of fine three-dimensional delineation of soil pollutants, the sampling strategies for soil boring, the commonly used models for delineating soil pollutants, and the relevant cases of applying these models at contaminated sites. We then summarized the effects of borehole data and three-dimensional models on soil pollutants’ delineation results from biased characteristics and nonstationary conditions. The present research status and related issues on correcting the biased characteristics and nonstationary conditions were analyzed. Finally, based on the problems and challenges, we suggested the three- dimensional delineation of soil pollutants in the underground “black box” for future research from the following six priority areas: multi-scenarios, nonstationary, non-linearity, multi-source data fusion, multiple model coupling, and the delineation of co-contaminated sites.
