This paper examines the rise of informal economies in China, a hidden driving force overlooked in studies on China’s urbanization. Estimating the size of informal economies using the multiple indicators multiple causes model, the paper employs mathematical models to examine the driving effect of informal economies on urbanization and to reveal the paths by which such effect works. The results were as follows. (1) In 2018, the size of the informal economy in China accounted for 23.5% of GDP with an output value of 21.16 trillion yuan. (2) The informal economy had a driving effect on China’s urbanization, and every 1-percentage- point increase in its share of the GDP led to an increase of 0.291 percentage points in the urbanization rate. (3) The informal economy’s effect on urbanization showed regional differences, decreasing in size from the eastern to the central to the western regions. (4) The informal economy drives urbanization through four paths - by promoting foreign direct investment (FDI), fixed asset investment (FAI), social consumption (SC), and secondary sector employment (SSE). Their effect sizes are ranked in descending order as follows: FDI > FAI > SC > SSE. This paper contributes to theories on urbanization dynamics and process in China by highlighting the role of the informal economy as a hidden economic power lurking in the city.
Global urbanization has led to drastic land use change, interfering the ecosystem services (ES) supply-demand balance, in turn threatening the well-being of humans. However, existing studies mainly stranded at the historical and current analysis, and the effects of urban spatial expansion on the relationship between ES supply and demand in the future are less clear, in particular at an urban agglomeration scale. This study was constructed with a framework of assessing the effects of urban spatial expansion on ES supply-demand mismatching under different future scenarios in the Guanzhong Plain Urban Agglomeration (GPUA) by using the Future Land Use Simulation (FLUS) model and expert-based Land-Use and Land-Cover Change (LUCC) matrix. The results showed that: (1) Urban expansion is significant in the natural development (ND) scenario, mainly manifesting the great transfer of dry land to construction land. (2) The gap between total ES supply and demand is narrowed from 2000 to 2030 and the mismatch between ES supply and demand is mainly reflected in the spatial distribution pattern in the GPUA. The ES budgets were in high surplus in Northern Qinling Mountains and northeast mountain areas, while they were in severe deficit in urban center areas. The budgets deficit under the ND scenario in 2030 is the most severe. (3) The gradient differences of ES budgets of the GPUA between urban centers and suburbs increase from 2000 to 2030 under two scenarios. The deficit region expands largest under ND scenario. The findings revealed that ES declining and supply-demand mismatching were triggered by the drastic land-use change driven by rapid urban expansion. The expansion has brought about an increasing material demand and growing industries, threatening the sustainability of ecosystems. Scenarios setting could contribute to coordinating the relationship between future urban development and ecological protection, and the policy strategies proposed in the study could inform ecological management and urban planning in the regions facing the similar urbanization situation.
Accelerating economic growth in formerly destitute areas and narrowing the economic gap with other regions are essential tasks for poverty alleviation in China after 2020. In this study, the spatio-temporal characteristics of economic growth in 14 formerly destitute areas of China were identified. Moreover, the spatial heterogeneity of various influencing factors was analyzed using a geographically weighted regression model. The results were as follows: (1) The economic level of the formerly destitute areas was low, but their economies grew rapidly after 2011, with annual per capita GDP growth of 10.54% until 2018, higher than the national average of 9.14%. Western and southern counties grew faster economically than central and northern counties. (2) The impact of various factors on the economic growth of counties exhibited clear spatial heterogeneity. The influences of secondary industry growth and level of financial development on economic growth were mainly positive, whereas the effects of initial economic level and market location were mainly negative. (3) Six economic growth driving modes were identified for the 14 contiguous destitute areas, among which the secondary industry-driven mode was the most common. The study can serve as a scientific reference for differentiating regional policies.
It is of great theoretical and practical importance to carry out research on the spatio-temporal evolution of urban air pollution and its driving forces, which helps to facilitate a deeper understanding of the mutual feedback mechanisms between the urban environment and socio-economic systems. Comprehension of these mechanisms will contribute to the design and implementation of efficient environmental policies that ultimately will improve the quality of urbanization development. This paper illustrates the spatio-temporal evolutionary characteristics of six urban ambient air pollutant concentrations, namely, CO, NO2, O3, PM10, PM2.5, SO2, in 286 sample cities above the prefecture level in China from 2014 to 2019. The interactions between the pollutant concentrations are analyzed based on panel regression models. A random forest model is then employed to explore the correlations between the concentrations of these six pollutants and 13 natural and socio-economic impact factors to isolate the most crucial ones. The results reveal three aspects. First, within the research period, the average annual concentration of O3 increased while that of other pollutants decreased year by year. Second, there were significant interactions between concentrations of the six pollutants, leading to obvious compound air pollution in urban areas. Third, the impact of natural and socio-economic factors on urban air quality varied greatly among different air pollutants, with air temperature, vegetation coverage, urbanization level and traffic factors ranking high and the different response thresholds to the dominant influencing factors. In light of the limited ability of humans to control the natural environment and meteorological conditions, it is recommended that urban air quality be further improved by optimizing urban density, controlling anthropogenic emission sources, and implementing strict air pollution prevention and control measures.
The geospatial distribution pattern in traditional Chinese settlements (TCSs) reflects the traditional harmony between humans and nature, which has been learned over centuries. However, TCSs have experienced serious disturbances by urbanization and migration. It is crucial to explore the local wisdom of geospatial patterns and dominant factors for TCSs at the national scale in China. This study sought to determine the geospatial wisdom of traditional settlements to enrich our future settlement development with the aim of establishing Chinese settlement values for modern living. Herein, a dataset of 4000 TCSs were analyzed and clustered for environmental factors that affect their geospatial patterns by machine learning algorithms. We concluded that (1) five geospatial patterns of TCSs were clustered on a national scale, and the threshold of environmental factors of TCS groups was detected. (2) Environmental conditions and settlement concepts interacted and determined the similarities and differences among TCS groups. (3) The key boundary for TCSs and the dominant factors for each zone were determined, and topographical conditions and hydrologic resources played significant roles in all five TCS zones. This study provides a better understanding of the adaptability of the environment in relation to the TCSs and aids in planning TCS conservation and rural revitalization.
The effective modeling of urban growth is crucial for urban planning and analyzing the causes of land-use dynamics. As urbanization has slowed down in most megacities, improved urban growth modeling with minor changes has become a crucial open issue for these cities. Most existing models are based on stationary factors and spatial proximity, which are unlikely to depict spatial connectivity between regions. This research attempts to leverage the power of real-world human mobility and consider intra-city spatial interaction as an imperative driver in the context of urban growth simulation. Specifically, the gravity model, which considers both the scale and distance effects of geographical locations within cities, is employed to characterize the connection between land areas using individual trajectory data from a macro perspective. It then becomes possible to integrate human mobility factors into a neural-network-based cellular automata (ANN-CA) for urban growth modeling in Beijing from 2013 to 2016. The results indicate that the proposed model outperforms traditional models in terms of the overall accuracy with a 0.60% improvement in Cohen’s Kappa coefficient and a 0.41% improvement in the figure of merit. In addition, the improvements are even more significant in districts with strong relationships with the central area of Beijing. For example, we find that the Kappa coefficients in three districts (Chaoyang, Daxing, and Shunyi) are considerably higher by more than 2.00%, suggesting the possible existence of a positive link between intense human interaction and urban growth. This paper provides valuable insights into how fine-grained human mobility data can be integrated into urban growth simulation, helping us to better understand the human-land relationship.
Satellite technologies provide valuable areal precipitation datasets in alpine mountains. However, coarse resolution still limits the use of satellite precipitation datasets in hydrological and meteorological research. We evaluated different time scales and precipitation magnitudes of Tropical Rainfall Measurement Mission 3B43 V7 (TRMM) and Global Precipitation Measurement (GPM) products for alpine regions using ground precipitation datasets from January 2015 to June 2019 obtained from 25 national meteorological stations and 11 sets of T-200B weighing precipitation gauges in the Qilian Mountains. The results indicated that GPM outperformed TRMM at all temporal scales at an elevation <3500 m with a higher probability of detection (POD), false alarm ratio (FAR), and frequency bias index (FBI) and performed best at 3000 m; TRMM performed better than GPM at an elevation >3500 m, with the best performance at 4000 m. GPM and TRMM had the best estimation accuracy in areas with monthly precipitation of 30 mm and 40 mm, respectively. Both TRMM and GPM products underestimated mid to large daily precipitation and overestimated light daily precipitation averaging <2 mm/d. This research not only emphasizes the superiority of GPM/TRMM in different regions but also indicates the limitations of precipitation algorithms.
Submarine cable network is one of the most important connectivity infrastructures in the digital era. In the past 20 years, the submarine cable network of Chinese mainland has formed a complex connectivity structure. This paper focuses on exploring the structure and evolution of the submarine cable network of Chinese mainland. The results show that the evolution can be divided into four stages: an initial stage (1993-1998), a developmental stage (1999-2002), a stagnation stage (2003-2015) and an accelerated stage (2016-2018). The connectivity structure can be analyzed at micro, meso and macro scales. Statistically, the connectivity increased significantly overall, but showed significant differences in space. For the microscale, the landing cities were characterized by “extensive but low, exclusive and high”; for the mesoscale, the connectivity of countries or regions was characterized by “distance attenuation” as a whole, but, in part, by a “regional identity”; for the macroscale, intercontinental connectivity differences have been declining. The hierarchy has been upgraded from a “3 system” to a “2 + 3 system”. Finally, this paper discusses the interaction between submarine cable network construction and international relations, and puts forward policy suggestions for China’s submarine cable construction.
National parks are useful entities for looking at coordinated efforts to improve the Tibetan Plateau’s function as an ecological safety barrier and the region’s green development. Research on the characteristics of the function structures of the Tibetan Plateau’s national parks is vital to promoting their systematic and coordinated development. This paper combines the pressure-state-response model, the rank-size rule and a coupling and coordination model to identify and evaluate the functions of national parks on the Tibetan Plateau and to analyze the categories, hierarchy and structures behind those functions. The results indicate the following: (1) The Tibetan Plateau National Park Cluster needs to maintain internal and external relations. Internally it needs to rationally allocate resources between ecological protection, recreation and community development, and externally it needs to promote its role as an ecological security barrier and promote regional green development by rationally ranking and organizing the individual national parks, so as to handle their co-evolution of functions at multiple scales. (2) Ecological protection, recreation and community development are the most prominent functions of the Tibetan Plateau National Park Cluster, but there is scope to develop their scientific research and education functions. The Zipf index shows that their multi-functional level conforms with the rank-size rule, indicating balanced development. Individual national parks need to strengthen their optimal functions according to their characteristic localization. (3) The degree of coupling between the functions of the Tibetan Plateau National Park Cluster is 0.7809, and the degree of coordination is 0.6227, which indicates a very strong coupling and moderate coordination. The coupling strength and degree of coordination between the multiple functions vary greatly among the individual national parks, which reflects their different function structures. There are four function structure types: fully coordinated, optimally developed, moderately developed and moderately underdeveloped. This study contributes to research on evaluating the functions of national park clusters and analyzing their structures, and it serves as a reference on optimizing and sustainably developing the Tibetan Plateau National Park Cluster.
The trade-offs and synergies of forest ecosystem service are important research topics for several disciplines. The multi-scale analysis of service trade-offs and synergies assists in the implementation of more effective forest resource management. Based on multi-source data including forest distribution, topography, NDVI, meteorology and soil conditions, key forest ecosystem services, including total forest volume, carbon storage, water yield, soil retention and habitat quality were mapped and evaluated for the Funiu Mountain Region through integrated deployment of the CASA model, the InVEST3.2 model and the ArcGIS10.2 software. The characteristics of trade-offs and synergies among different ecosystem services were then mapped and considered across multiple spatial scales (i.e., by region, north and south slopes, vertical belt) using the spatial overlay analysis method. The main results are as follows: (1) Mean forest volume is 49.26 m3/ha, carbon density is 156.94 t/ha, water yield depth is 494.46 mm, the unit amount of soil retention is 955.4 t/ha, and the habitat quality index is 0.79. (2) The area of forests with good synergy is 28.79%, and the area of forests with poor synergy is 10.15%, while about 61.06% of forests show severe trade-offs and weak trade-offs. The overall benefits of forest ecosystem services in the study area are still low. In the future, bad synergy and severe trade-off areas should be the focus of forest resource management and efficiency regulation. (3) Synergy between ecosystem services is better for forest on south slope than that on north slope. Deciduous broad-leaved forest belt at moderate elevations on south slope in the mountains (SIII) has the highest synergies, while that at low elevations on north slope (NI) exhibits the lowest synergy levels.
