The Spatial and Temporal Distribution of High-Quality Urbanization Development in Yellow River Basin Provinces

Abstract

The high-quality development of urbanization is strategically important for the sustainable economic and social development in the Yellow River Basin. It is necessary to establish a system of indicators to evaluate the high-quality development in terms of five aspects: innovation, coordination, green, openness and sharing. Spatial autocorrelation, local Moran indices and cluster analysis are used to study the spatial–temporal distribution of high-quality urbanization development in each province. The results indicate that the urbanization level of nine provinces in the Yellow River Basin showed an increasing trend from 2010 to 2018. However, the development of the five dimensions is not balanced. At the same time, the level of high-quality urbanization development in the Yellow River Basin has not shown significant spatial clustering characteristics and has not formed a good interactive relationship and aggregation effects. It is of great practical importance to promote the coordinated development of urbanization and the high quality of urbanization. The problems existing in the current development are found, and effective measures are proposed to make the urbanization development adapt to the economic and social development.

1. Introduction

The Yellow River is the second largest river in China, with a basin area of about 752,000 square kilometers, nurturing more than 60 large and medium-sized cities and 340 counties in nine provinces along the Yellow River, with 420 million inhabitants overall, making up nearly one-third (30.3%) of the country’s population [1]. The basic feature of the Yellow River Basin is that there are more people and less water, and the per capita water resource possession is only 383 cubic meters, which is only 18% of the national per capita level [2]. Affected by climate, topography, water resources, the population is unevenly distributed. The Yellow River Basin serves as a major source of energy and agricultural output. It is also the most important ecological barrier and economic area in northern China. The Yellow River Basin’s gross domestic product (GDP) totaled CNY 19.4 trillion in 2018, or 21.55 percent of the nation’s overall GDP [3].

The Yellow River Basin occupies an important position in China’s ecological and economic and social patterns, but its ecosystem is very fragile. Desertification is a serious problem in the northwest, soil erosion is serious in the Loess Plateau area, forest coverage in the Yellow River Basin is lower than the national average, and water consumption for industry, agriculture and domestic use has exceeded the carrying capacity of the Yellow River water resources. These complex and diversified problems have posed serious constraints on the sustainable development of the Yellow River Basin. The energy and heavy chemical industry’s massive development has aggravated the ecological problems of the Yellow River Basin. Irrational exploitation methods have led to the reduction of groundwater sources and pollution in local areas, and the growth of industrial water use has led to insufficient ecological water use and local ecological degradation [4]. Under the influence of climate change and human activities, the Yellow River Basin is facing a series of problems such as the acute conflict between water supply and demand, fragile ecological environment, complex relationship between water and sand, frequent natural disasters, incompatibility between human and land systems, etc. The sustainable development of the region is facing serious challenges, with a low level of development of the Yellow River economy, low quality of development and outstanding problems such as ecological environmental destruction. Therefore, the state has put forward a major national strategy for ecological protection and high-quality development of the Yellow River Basin, pointing out the direction for high-quality development of the Yellow River Basin.

There is an urgent need for high-quality development of the Yellow River Basin. The “ecological protection” and “economic development” of the Yellow River Basin are two major goals at present. At present, the economy has shifted from a phase of rapid expansion to a phase of high-quality development. The city as a senior form of people’s living style is an important symbol of human spiritual civilization. To a certain extent, the city’s high-quality development is also the region’s high-quality development. China’s urbanization rate has reached 60.60 percent in 2019, an increase of 42.7 percentage points over the 17.9 percent in 1987 when the reform and opening-up took place [5], China has rapidly developed from a country with a large agricultural population into a country with a predominantly urban population. Wan and Cheng [6] pointed out that the high-quality development of urbanization reflects the new development concept, focusing on harmonious development, improving the quality of life of urban and rural residents, taking a resource-saving and environmentally friendly route, and putting forward higher requirements for regional economic structure, ecosystems and production factors. The Yellow River Basin covers many regions of China, including the eastern coastal region (Shandong), the central region (Henan and Shanxi), the northwest region (Shaanxi, Gansu, Ningxia, Qinghai and Inner Mongolia) and the southwest region (Sichuan), with uneven urbanization development. In the eastern part of the Yellow River Basin, the transportation is convenient and the economy is more developed, for most of the city geographic location, urbanization development is faster; the central region has a high proportion of rural and agricultural population and the process of urbanization is slow; the western region is a remote region with special climatic conditions, a small population and slow urbanization [7].

High-quality development of urbanization can provide new opportunities for the provinces and cities in the river basin, improve the urban system, promote the transfer of capital and technology from cities to the countryside and improve the living conditions of the people in the river basin. Urbanization has been the inevitable trend of China’s economic and social development. However, the process of rapid urbanization is frequently accompanied by issues such as heavy metal pollution in air, water and soil, as well as ecological degradation, which put a great of strain on the environment’s carrying capacity and resources [8]. Increased energy consumption and serious pollution emissions also play a serious role in constraining the development of urbanization. Yuan et al. [9] pointed out that since the reform and opening-up, China’s urbanization has achieved tremendous things but also triggered serious air pollution, and it is very significant to deeply investigate the interaction mechanism between urbanization and air pollution to promote high-quality economic development. Chang and Guan [10] also pointed out that while the rapid urbanization of the Yangtze River Delta urban agglomeration has brought economic benefits, the contradiction is that the construction of ecological civilization is lagging and becoming more and more prominent. Therefore, it is of great importance to coordinate the development of urbanization and the construction of ecological civilization. The traditional extensive urbanization development model has brought many urban diseases and serious ecological pressure to the society while promoting economic development. Feng and Li [11] pointed out that urbanization, the most irreversible human activity, has caused rapid population growth and irrational exploitation of resources on the Tibetan Plateau, resulting in a trend of ecological degradation. Xu and Wang [12] pointed out that new urbanization pays more attention to resource conservation and environmental friendliness. Because of the problems that have emerged in the current stage of urbanization development, the development of high-quality urbanization can no longer be delayed. An and Li [13] argue that high-quality development is not only about pursuing rapid economic development but also about focusing on social and ecological aspects of high-quality development in the long-term interests. High-quality development embodies a new development concept and is the development that can produce greater benefits. For this reason, the high-quality urbanization of the Yellow River Basin needs research and attention.

This paper selects provinces in the Yellow River Basin as the objects of study, constructs a feasible evaluation index system to study the current status and changes in differences in the high-quality development of urbanization in the provinces in the Yellow River Basin to discover the problems existing in the current stage of development, and put forward effective measures to improve the quality of urbanization construction in the provinces of the Yellow River Basin.

2. Evaluation Indicators

2.1. Five Development Concepts Support Urbanization Development

The five development concepts have common development goals. They aim to solve the problem of “how to develop” and guide China’s faster and better economic and social development [14]. The five development concepts are an inseparable whole, promoting development together and integrating, and are indispensable.

Five development concepts support the development of urbanization, as shown in Figure 1. Innovation provides the driving force for the development of urbanization. In the long run, the support for the development of high-quality urbanization considers whether cities and towns have innovative resources and irreplaceable knowledge advantages [15]. The construction of new-type urbanization urgently needs innovation support and leadership. Coordination is the catalyst for the development of urbanization. At this stage, there is a large gap between city and countryside development, and future urbanization construction needs coordinated development, focusing on urban–rural coordination and integrated urban–rural development. Green is the core requirement of urbanization development, and the development of urbanization should avoid “quick success and instant profits”.

Openness is the accelerator of urbanization, introducing capital, technology, advanced concepts, and excellent talents to promote growth of China’s economy and provide strong support for the development of urbanization, and uphold two-way openness in both urban and rural areas to push the development of urbanization by facilitating the two-way flow of urban and rural elements [15]. Sharing is the destiny of urbanization and sharing requires that development starts and ends with the people, development depends on the people, and the achievements of development are shared by the people, and the high-speed and high-quality development of urbanization is also for sharing. The future development of urbanization needs to uphold the five concepts and walk out on a high-quality and sustainable new urbanization development path.

2.2. Study on Evaluation System of Urbanization Development

The development of urbanization is affected by many factors. Lin and Zhu [16] have found that the environmental factor is a large and important factor influencing the level of urbanization development. Tselios [17] analyzed the various factors that influence urbanization development and concluded that education and population quality are crucial in urbanization development and that urbanization development should focus on human resource development. Zhang et al. [18] studied the spatial layout of the comprehensive level of urbanization, pointing out that economic strength, the process of demonetization, the level of modernization of towns and villages and topographic and geomorphological conditions all have an effect on how urbanization develops. Lai and Zhao [19] argued that urbanization is a complex and comprehensive project, which is influenced by many factors, and that urbanization is determined by factors such as government macroeconomic policies, immigration, education level, natural growth differences between urban and rural populations, industrial structure and relevant institutions. Li [20] studied the data related to urbanization in 31 provinces and regions in China and analyzed the influencing factors, and concluded that the level of economic development, industrial structure non-agriculturalization, social security level, fixed asset investment and foreign direct investment in each province and region have a substantial part in promoting the new urbanization of provinces and regions. Han and Mou [21] analyzed the connotation of new urbanization and studied the influencing factors of urbanization in Sichuan province from two dimensions: in-province and out-province, and concluded that spatial factors and economic development, residents’ income structure, public service allocation structure, industrial structure and employment structure have important influences on new urbanization in Sichuan province.

There are numerous evaluation systems for urbanization development. Yang and Zhang [22] argued that the essence of urbanization is “urbanization of people”, involving urban and rural society, economy, politics, ecology and other aspects. In order to more precisely grasp the extent of urbanization development and have a deep understanding of the high-quality development of urbanization, scholars have researched the urbanization of regions or cities and established evaluation index systems. Due to the many factors influencing urbanization development, there are different perspectives for evaluating quality development. Most scholars use the composite index method to establish a more complete index system with multiple indicators from different perspectives. Shi [23] conducted a cluster study on the level of urbanization in 11 prefecture-level cities in Zhejiang Province, and constructed indicators such as the percentage of the secondary industry, tertiary industry and the percentage of market allocation of resources. While Li and Li [24], from an ecological perspective, argued that green low-carbon coordinated development is a powerful engine for economic development, constructed an impact factor index system for the coordinated development of a new type of green low-carbon urbanization, and suggested relevant countermeasures in terms of scientific and technological innovation, industrial structure, culture and education. On the other hand, Zheng and Wei [25] established a system of evaluation indicators in terms of economic development, social development, life, environment and space intensity. Zhao [26] conducted a comprehensive measurement and analysis of China’s urbanization development level using an improved entropy weight method based on four subsystems: economic foundation, population development, social function, and environmental quality, and focusing on eight indicators contained in the subsystems: economic efficiency, structural optimization, level improvement, full employment, functional improvement, urban–rural coordination, environmental improvement and ecological livability. Fan and Li [27] constructed a new urbanization evaluation framework including three dimensions of “employment urbanization”, “residential urbanization” and “behavioral urbanization” from a sociological perspective when studying new urbanization. This index system consists of seven three-level indicators, including employment status, employment services, housing status, housing services, basic public services, social participation and social identity, and 15 four-level indicators have been constructed. Song et al. [28] use the degree of coordination between population growth, land change, economic development, social development and ecological change as indicators for a comprehensive evaluation of the coordinated development of urbanization. Ren and Gong [29] constructed a comprehensive evaluation system for the coupling and coordination of urbanization and high-quality development in the Yellow River Basin. The urbanization part of the system comprehensively evaluates urbanization from four levels: population urbanization, economic urbanization, social urbanization and spatial urbanization. Zhang et al. [30] selected 11 indicators to measure the level of urban development from the perspectives of population development, economic development, living standards and social development. Shi et al. [31] studied the space–time characteristics and influencing factors of the coupling and coordination relationship between the high-quality development of urbanization and the ecological environment, and established an evaluation system for the high-quality development of urbanization that integrates population, economy, ecology, society and space.

By combing through the existing studies, we can find that most of the existing studies on urbanization quality development evaluate the level and quality of urbanization development from the national level or a certain province or city, but not from the basin level, and there is no intermediate level of quality development evaluation; only from a single object, no comparison of quality development of multiple provinces and cities and lack of consideration of the coordination of development within the basin. This paper takes the nine provinces of the Yellow River Basin as the starting point, combines the comparative advantages of the Yellow River Basin and the current situation of urbanization in the nine provinces as well as the characteristics of economic development and ecological environment, and constructs an urbanization development evaluation index system based on the five development concepts with the national strategy as the framework.

2.3. Evaluation Indexes System for Quality Urbanization Development

Focusing on the “Five Development Concepts”, a comprehensive evaluation indicator system for the high-quality development of urbanization in the Yellow River Basin provinces is established from five perspectives: innovation, coordination, green, openness and sharing. To facilitate the scale-free form of the initial data, we divide all the indicators into positive indicators (the larger the better), negative indicators (the smaller the better) and moderate indicators [32]. The specific indicators were selected as follows:

Innovation is the first driving force for leading economic development and the core driving force for high-quality regional development [33]. China’s economic development has entered a new normal, and there is an urgent need to change the mode and driving force of economic development. Realizing innovation to promote economic development is fundamental to high-quality development [34]. Thus, this paper selects seven indicators in innovation, including R&D investment intensity, per capita investment in science and technology, per capita investment in education, the proportion of technology market turnover in GDP, innovative product profitability, per 100,000 people of higher education students and per 10,000 people of patent applications. Detailed indexes are listed in

Table 1. Innovation dimension index.

Dimension	Index	Unit	Property	Meaning of Index	Source of Index
Innovation	R&D investment intensity	%	Positive	R&D expenditure/total GDP	[34]
	Per capita investment in science and technology	yuan	Positive	Average regional general public budget expenditure per person in science and technology	[35]
	Per capita investment in education	yuan	Positive	Regional general public budget expenditure on education on average per person	[35]
	Proportion of technology market turnover in GDP	%	Positive	Technology market turnover/total GDP	[36]
	Innovative product profitability	%	Positive	Innovative product sales revenue/industrial enterprise main business revenue	[37]
	Per 100,000 people of higher education students	person	Positive	Number of students in higher education × 100,000/total population	[38]
	Per 10,000 people of patent applications	piece	Positive	Number of patents granted × 10,000/total population	[34]

.

Coordinated development is the inherent requirement for the sustainable and healthy development of the region [38], and aims to solve the problems of imbalance and uncoordinated development in the process of development. Hence, in the course of high-quality urbanization development, attention should be paid to coordinating the level of urban and rural development, narrowing the urban–rural gap, adjusting the economic structure and promoting the coordinated development of regional economies. Therefore, this paper selects eight indicators for coordination: IU ratio, NU ratio, urbanization economic growth rate coordination index, share of the tertiary industry output in GDP, total dependency ratio, the urban–rural income level ratio, the urban–rural consumption level ratio and the urbanization rate. Among them, the IU ratio is the ratio of the industrialization rate of the labor force to the urbanization rate, and the nu ratio is the ratio of the non-agriculturalization rate of the labor force to the urbanization rate. The IU ratio and nu ratio are used to measure the degree of coordinated development of urbanization, industrialization and non-agriculturalization in a region [39]. Detailed indexes are listed in

Table 2. Coordination dimension index.

Dimension	Index	Unit	Property	Meaning of Index	Source of Index
Coordination	IU ratio	none	Moderate	Labor force industrialization rate/urbanization rate	[40]
	NU ratio	none	Moderate	Labor force de-agriculturalization rate/urbanization rate	[40]
	Urbanization economic growth rate coordination index	none	Positive	The average annual growth rate of urbanization rate/average annual growth rate of GDP per capita	[40]
	Share of the tertiary industry output in GDP	%	Positive	Tertiary industry output/total GDP	[41]
	Total dependency ratio	%	Negative	Non-working-age population/working-age population in the total population	[42]
	Urban–rural income level ratio	%	Negative	Urban disposable income per capita/rural disposable income per capita	[36]
	Urban–rural consumption level ratio	%	Negative	Urban consumption expenditure per capita/rural consumption expenditure per capita	[36]
	Urbanization rate	%	Positive	Urban resident population/total population	[43]

.

Green is the new yardstick for measuring the quality of economic and social development [44] and represents the basic requirements for high-quality regional development. Advantageous resource conditions and ecological environment will attract more funding and talented people and promote the prosperity of urban society and economy [45]. Green development needs to solve the problem of harmonious coexistence between man and nature, with emphasis on adhering to the principles of resource conservation and environmental friendliness and integrating environmental conservation into all aspects and the whole process of high-quality urbanization development [46]. Therefore, this paper selects total water consumed per unit of GDP, per capita emissions of main pollutants in exhaust gases (sulfur dioxide + nitrogen oxides + smoke (powder) dust), domestic waste pollution-free treatment rate, urban sewage treatment rate, the comprehensive utilization rate of general industrial solid waste, green coverage in the built-up areas and average per capita water resources: seven indicators to measure the green economy quality development status. Detailed indexes are listed in

Table 3. Green dimension index.

Dimension	Index	Unit	Property	Meaning of Index	Source of Index
Green	Total water consumed per unit of GDP	cubic meter per yuan	Negative	Total water consumption/total GDP	[47]
	Per capita emissions of main pollutants in exhaust gases (sulfur dioxide + nitrogen oxides + smoke (powder) dust)	ton per person	Negative	Emissions of main pollutants (sulfur dioxide, nitrogen oxides, smoke (powder) dust) in exhaust gas/total population	[34]
	Domestic waste pollution-free treatment rate	%	Positive	Amount of household garbage pollution-free treatment/household garbage production	[48]
	Urban sewage treatment rate	%	Positive	Urban domestic sewage treatment volume/urban domestic sewage generation volume	[38]
	The comprehensive utilization rate of general industrial solid waste	%	Positive	The amount of solid waste extracted from general industrial solid waste or converted into usable resources, energy and other raw materials/amount of general industrial solid waste generated	[49]
	Green coverage in the built-up urban areas	%	Positive	Green coverage of urban built-up areas/urban built-up areas	[49]
	Average per capita water resources	cubic meter per person	Positive	Average amount of water resources per head of population in an area for a given period of time	[47]

.

Open development is the only means to improve the quality of economy and social development [44], paying equal attention to bringing in and going out to develop a higher level of the open economy [38]. Over the past 40 years of reform and opening-up, China’s foreign trade development has had a positive trend. With China’s reform and opening up deepening, the disadvantages of using a trade surplus and foreign capital utilization quota to characterize the degree of opening up have gradually emerged. In the new period, we should focus more on trade balance and the quality of foreign capital utilization [49]. Therefore, in the aspect of opening up, this paper focuses on the selection of three indicators, namely, the openness of foreign investment, dependency on foreign trade and actual foreign capital utilized as a percentage of GDP to reflect the level of urban economic openness. Detailed indexes are listed in

Table 4. Openness dimension index.

Dimension	Index	Unit	Property	Meaning of Index	Source of Index
Openness	The openness of foreign investment	%	Positive	Total foreign investment/total GDP	[37]
	Dependency on foreign trade	%	Positive	Total imports and exports/total GDP	[9]
	Actual foreign capital utilized as a percentage of GDP	%	Positive	The total amount of foreign capital actually utilized/total GDP	[49]

.

Sharing is the starting point and ending point of high-quality development in the improvement in people’s quality of life. The ultimate goal is to ensure that people share the fruits of development and meet the growing demand for a better life. Therefore, sharing is the fundamental goal of high-quality development [41]. Therefore, from the aspects of medical treatment, transportation, education, insurance and employment, this paper selects six indicators, namely, per 1000 people of health technical personnel, per 10,000 people public transport vehicles, per capita of library holdings, participation rate of urban basic endowment insurance, urban registered unemployment rate and per capita GDP to reflect the level of social sharing development. Detailed indexes are listed in

Table 5. Sharing dimension index.

Dimension	Index	Unit	Property	Meaning of Index	Source of Index
Sharing	Per 1000 people of health technical personnel	person	Positive	Number of health technicians × 1000/total population	[36]
	Per 10,000 people public transport vehicles	standard station	Positive	Number of public transport vehicles × 10,000/total population	[50]
	Per capita of library holdings	book per person	Positive	Public library stock/total population	[51]
	Participation rate of urban basic endowment insurance	%	Positive	Number of participants in urban basic pension insurance/total population	[49]
	Urban registered unemployment rate	%	Negative	Number of urban registered unemployed/(number of urban employed + number of urban registered unemployed)	[37]
	Per capita GDP	yuan per person	Positive	Total GDP/total population	[50]

.

3. Data Sources and Research Methods

3.1. Study Area and Data Sources

The study areas of this study are Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia, Shaanxi, Shanxi, Henan and Shandong in the Yellow River Basin. Among them, Qinghai, Sichuan, Gansu, Ningxia and Inner Mongolia belong to the upper reaches of the Yellow River Basin, Shaanxi and Shanxi are located in the middle reaches, and Henan and Shandong are located in the lower reaches. The study area spans the three major geomorphological terraces of east, middle and west China, with obvious characteristics of diversified geographical structure. The geographical distribution of the study area is shown in Figure 2.

The data used in this paper are mainly from China Statistical Yearbook 2011–2021, Qinghai Statistical Yearbook 2011–2021, Sichuan Statistical Yearbook 2011–2021, Gansu Statistical Yearbook 2011–2021, Ningxia Statistical Yearbook 2011–2021, Inner Mongolia Statistical Yearbook 2011–2021, Shaanxi Statistical Yearbook 2011–2021. 2011–2021, Shanxi Statistical Yearbook 2011–2021, Henan Statistical Yearbook 2011–2021, Shandong Statistical Yearbook 2011–2021, as well as the Statistical Bulletin of National Economic and Social Development of individual provinces, some of which are derived from secondary calculations of relevant indicators.

3.2. Research Methods

Index standardization. There are differences in unit dimensions among the indicators, and the positive and negative orientations are also different. Therefore, the extremum method should be used to normalize the data. Assuming there are m objects to be evaluated and n indicators, (m = 9, n = 31 in this paper). Use x_ij to represent the value of the indicator j for the i evaluation object and x′_ij to represent the value of the indicator j for the i object after standardization. The specific calculation is as below:

When the indicator is positive:

$${{\displaystyle x}}_{ij}^{\prime }=\frac{{{\displaystyle x}}_{ij}-{{\displaystyle x}}_j^{\min }}{{{\displaystyle x}}_j^{\max }-{{\displaystyle x}}_j^{\min }}$$

(1)

When the indicator is negative:

$${{\displaystyle x}}_{ij}^{\prime }=\frac{{{\displaystyle x}}_j^{\max }-{{\displaystyle x}}_{ij}}{{{\displaystyle x}}_j^{\max }-{{\displaystyle x}}_j^{\min }}$$

(2)

When the indicator is moderate:

$${{\displaystyle x}}_{ij}^{\prime }=\frac{{{\displaystyle x}}_j^{\max }-\left|{{\displaystyle x}}_{ij}-{{\displaystyle t}}_{}\right|}{{{\displaystyle x}}_j^{\max }-{{\displaystyle x}}_j^{\min }}$$

(3)

where t is the moderate value, the moderate value of the IU ratio is 0.5 and the moderate value of the NU ratio is 1.2 [40]. Obtain the indicator weights. The objective method is a series of calculations to obtain weights based on the raw data collected. In this paper, the entropy weight method of objective weighting is used to determine the weight of indicators.

In order to make sense of the data arithmetic process, zero values must be eliminated, so the standardized data is smoothed as a whole, namely, ${{\displaystyle y}}_{ij}={{\displaystyle x}}_{ij}+\alpha$. To maximize the retention of original data, here $\alpha =0.0001$.

The calculation steps are as below:

(1)

Calculation of the proportion of the value of indicator i for index j:

$${{\displaystyle p}}_{ij}=\frac{{{\displaystyle y}}_{ij}}{{\displaystyle \sum _{i=1}^n{y}_{ij}}}$$

(4)

(2)

Calculate the entropy value for indicator j:

$$e_j=-\frac{1}{\ln m}{\displaystyle \sum _{i=1}^n{p}_{ij}\ln }{p}_{ij}$$

(5)

(3)

Calculate the weight for indicator j:

$$w_j=\frac{1-e_j}{{\displaystyle \sum _{j=1}^n(1-e_j)}}$$

(6)

Comprehensive evaluation score. In this paper, the linear weighted function method is used to calculate the comprehensive evaluation score of the level of high-quality urbanization development in each province, with the following formula:

$${{\displaystyle S}}_{ij}={\displaystyle \sum _{j=1}^n({{\displaystyle w}}_j\times {{\displaystyle y}}_{ij}})$$

(7)

Spatial autocorrelation analysis. The spatial autocorrelation contains global and local spatial autocorrelation. This study used global Moran’s I to represent global spatial autocorrelation and check the similarity and correlation of adjacent units. Local spatial autocorrelation is represented by local Moran scatter plot, which is used to prove the spatial cluster characteristics. The global Moran’s I is as fowling:

$$I=\frac{{\displaystyle \sum _{i=1}^n{\displaystyle \sum _{j=1}^n{w}_{ij}\left(x_i-\overline{x}\right)\left(x_j-\overline{x}\right)}}}{{{\displaystyle s}}^2{\displaystyle \sum _{i=1}^n{\displaystyle \sum _{j=1}^n{w}_{ij}}}}$$

(8)

where n is the number of spatial units, x_i and x_j are the indicator values of the i and j spatial units, respectively, $\overline{x}$ is the mean of all spatial unit indicator values, ${\omega }_{ij}$ is the spatial weight matrix and ${{\displaystyle S}}^2$ is the variance of the x_i and x_j values. The range of values of the Moran index is (−1, 1). When it is greater than 0, it means positive spatial correlation, and the closer it is to 1, the more spatial units with similar properties tend to cluster; when it is less than 0, it means negative spatial correlation, and the closer it is to −1, the more spatial units with dissimilar properties tend to cluster.

The local Moran index is:

$${{\displaystyle I}}_i=\frac{{{\displaystyle x}}_i-{{\displaystyle \overline{x}}}_{}}{{{\displaystyle s}}^2}\left[{\displaystyle \sum _{i=1}^n{w}_{ij}({{\displaystyle x}}_i-{{\displaystyle \overline{x}}}_{})}\right]$$

(9)

When the local Moran index is positive, it indicates that the regions with the same type of feature attribute values are close to each other, and when the local Moran index is negative, it indicates that the regions with different feature attribute values are close to each other. According to the Moran index scatter diagram, four local agglomeration patterns can be divided, namely, high–high clustering pattern (H-H), high–low clustering pattern (H-L), low–low clustering pattern (L-L) and low–high clustering pattern (L-H).

Cluster analysis. The principle of classification is to make individuals in the same class have greater similarity, while individuals in different categories have great differences. In this paper, the systematic clustering method is used to classify the type of urbanization quality development level in nine provinces in the Yellow River Basin, with the following calculation steps:

(1)

Calculate the Euclidean distance between the composite scores for each item:

$${{\displaystyle d}}_{ij}={{\displaystyle \left[{\displaystyle \sum _{k=1}^m{{\displaystyle \left({{\displaystyle x}}_{ik}-{{\displaystyle x}}_{jk}\right)}}^2}\right]}}^{\frac{1}{2}}\left(i,j=1,2,3\cdots ,m\right)$$

(10)

(2)

Construct the distance matrix from the resulting distances:

$$D={{\displaystyle \left({{\displaystyle d}}_{ij}\right)}}_{m\times m}=\left(\begin{array}{ccc}{d}_{11}& \dots & d_{1m}\\ ⋮& \ddots & ⋮\\ a_{m1}& \cdots & a_{mm}\end{array}\right)$$

(11)

(3)

Use the longest distance method to find the maximum distance between classes:

$${{\displaystyle D}}_{pq}=\underset{x_i\in Gp,x_j\in Gp}{{\displaystyle \max }}{{\displaystyle d}}_{ij}$$

(12)

where D_pq represents the distance between the two classes of class Gp and class Gq, and its value is equal to the distance between the two farthest items in class Gp and class Gq. Re-classify class Gp and class Gq into a new class, calculate the distance of the new class from the other classes, and repeat the above steps until the classification objects are grouped into one class.

4. Results and Discussion

4.1. Comprehensive Situation of High-Quality Urbanization Development

Based on the raw data and the weights calculated above, the formula was applied to calculate a comprehensive score for the level of high-quality urbanization development in each of the Yellow River Basin provinces from 2010 to 2020 as shown in

Table 6. Composite score for the level of high-quality urbanization development in the Yellow River Basin provinces, 2010–2020.

	2010	2011	2012	2013	2014	2015	2016	2017	2018	2019	2020
Qinghai	0.270	0.290	0.334	0.264	0.320	0.369	0.445	0.608	0.577	0.586	0.741
Sichuan	0.164	0.193	0.296	0.278	0.327	0.413	0.417	0.504	0.652	0.720	0.859
Gansu	0.240	0.229	0.323	0.397	0.426	0.511	0.532	0.625	0.670	0.672	0.801
Ningxia	0.181	0.191	0.257	0.287	0.322	0.370	0.413	0.558	0.604	0.657	0.788
Inner Mongolia	0.211	0.223	0.324	0.339	0.377	0.491	0.491	0.612	0.618	0.596	0.723
Shaanxi	0.201	0.252	0.292	0.336	0.421	0.532	0.622	0.653	0.692	0.752	0.842
Shanxi	0.168	0.237	0.309	0.407	0.413	0.399	0.516	0.533	0.642	0.613	0.757
Henan	0.139	0.159	0.226	0.261	0.351	0.445	0.540	0.626	0.726	0.719	0.878
Shandong	0.201	0.270	0.305	0.370	0.367	0.407	0.431	0.470	0.518	0.561	0.817

.

In order to more easily and intuitively analyze the time-varying characteristics of the level of high-quality urbanization development in each province of the Yellow River Basin, the individual years in the above table are visualized in ArcGIS as follows: Figure 3.

As we can see from Table 6 and Figure 3, the maximum value has gradually increased from 0.270 (Qinghai) in 2010, 0.532 (Shaanxi) in 2015 to 0.878 (Henan) in 2020, and the level of high-quality urbanization development in the Yellow River Basin has been continuously improved in the last 11 years. The 11-year increases can be calculated for each province as 0.471 (Qinghai), 0.695 (Sichuan), 0.572 (Gansu), 0.607 (Ningxia), 0.512 (Inner Mongolia), 0.641 (Shaanxi), 0.589 (Shanxi), 0.739 (Henan) and 0.616 (Shandong), respectively. From the above two sets of data, it can be concluded that while the overall urbanization high-quality development of the Yellow River Basin provinces has shown a growth trend, the development of the provinces is uneven, indicating that the provinces have indeed made some achievements in urbanization development and construction, but it should not be overlooked that there are still considerable differences between the provinces in the development.

The differences are first seen in Henan Province, which has grown most rapidly over the 11 years, rising from the bottom of the nine-province rankings in 2010 to first place in 2020, in contrast to Inner Mongolia, where the rate of high-quality urbanization development is the lowest of the nine provinces and, although the overall score has been rising, the ranking has fallen from third place in 2010 to last among the provinces in 2020, Sichuan only had a significant fall back in 2013 to continue its upward trend and is ranked among the top nine provinces in terms of growth (second). Shaanxi, like Inner Mongolia, saw a continuous rise in the level of urbanization quality development between 2010 and 2020, but the rate of increase was larger than that of Inner Mongolia, and the ranking of the growth rate was third; the high-quality development level of urbanization in Ningxia maintained a continuous growth state, and the growth rate was large from 2016 to 2017 and from 2019 to 2020, respectively, 0.145 and 0.131; the overall growth trend of the high-quality development level of urbanization in Shanxi Province was obvious, but the development fluctuated greatly, which decreased slightly in 2014 and 2018 and increased significantly from 2015 to 2016 and 2019 to 2020; the level of urbanization quality development in Shandong basically maintained growth, with only a slight decrease in 2014; in Gansu, there was a slight decline in 2011, but the overall growth trend was still growing.

From the above analysis, it can be concluded that the level of high-quality urbanization development in the Yellow River Basin is uneven and uncoordinated among provinces, but in general, the level of urbanization development in the central and western provinces is lower than that in the eastern provinces, i.e., the level of high-quality urbanization development in the lower provinces of the Yellow River Basin is higher than that in the upper and middle provinces.

4.2. The Average Level of High-Quality Urbanization Development

According to the average data of each indicator from 2010–2020, the comprehensive average score of urbanization high-quality development level of provinces in the Yellow River Basin from 2010 to 2020 is calculated, as shown in Figure 4.

According to the data of the average level of various indicators from 2010 to 2020, the scores of the five dimensions of urbanization high-quality development in the Yellow River Basin from 2010 to 2020 are calculated as follows:

Table 7. Average scores of each dimension of high-quality urbanization development.

	Innovation Development	Coordination Development	Green Development	Open Development	Shared Development
Qinghai	0.281	0.583	0.506	0.046	0.655
Sichuan	0.323	0.481	0.356	0.588	0.363
Gansu	0.252	0.469	0.172	0.048	0.376
Ningxia	0.343	0.475	0.184	0.309	0.476
Inner Mongolia	0.147	0.548	0.283	0.228	0.390
Shaanxi	0.641	0.404	0.386	0.439	0.686
Shanxi	0.181	0.804	0.267	0.368	0.352
Henan	0.231	0.189	0.467	0.409	0.364
Shandong	0.576	0.523	0.636	0.867	0.705

.

In order to more clearly see how the level of urbanization quality development fluctuates across the five dimensions in the provinces of the Yellow River Basin, the above table is made into a line graph as shown in Figure 5.

The average scores of the comprehensive level of high-quality urbanization development are, in descending order, Shandong (0.667) > Shaanxi (0.502) > Sichuan (0.423) > Qinghai (0.390) > Shanxi (0.374) > Henan (0.341) > Ningxia (0.340) > Inner Mongolia (0.303) > Gansu (0.242).

The average comprehensive score of urbanization high-quality development level of nine provinces in the Yellow River Basin is 0.398. The scores of Sichuan, Shaanxi and Shandong are higher than the average, while the other provinces are not. Among the nine provinces in the Yellow River Basin, Shandong has the highest score, which is much higher than other provinces in the Yellow River Basin. Gansu Province has the lowest score.

From the perspective of the five dimensions, Shandong Province is the only one among the nine provinces with good development, while the other provinces have weaknesses. Gansu is below average in all five dimensions, and far below average in open development, with a score of 0.048. Qinghai is above average in coordination, green and sharing, and slightly below average in innovation, but scores only 0.046 in open development, far below average, and the opening-up level still needs to be improved. Only the opening level of Sichuan is outstanding and far higher than the average level, but the other four aspects are slightly lower than the average level. For Sichuan, it has only an outstanding and well-above-average level of openness but is slightly below average in the other four areas. The comprehensive level of high-quality urbanization development in Sichuan ranks third, which is also attributed to its open level, while several other dimensions need to be emphasized and developed. The score of green development in Ningxia is only 0.184, accounting for 29% of the highest value of 0.636, and the score of openness, coordination and sharing in Ningxia is also lower than the average level. Ningxia is located in the western region. While introducing heavy industry and promoting development, we should take care of ecological conservation. In the past 11 years, Inner Mongolia has paid attention to coordinated development, but the score of innovation is low, only 0.147, while the score of green, open and sharing has not reached the average level. Shaanxi has achieved remarkable innovation and green development, with the highest innovation score and the second highest green score. Except for the two indicators of green and sharing, the scores of the other three indicators in Henan are lower than the average.

4.3. The Time Differences of Urbanization High-Quality Development in Each Dimension

Innovation dimension. As shown in Figure 6, the innovation dimension shows a fluctuating upward trend from 2010 to 2020, but the rate of increase has some variability. The five provinces of Sichuan, Shaanxi, Henan and Shandong have steadily increased in the past 11 years, Shanxi, Inner Mongolia and Ningxia Provinces all experienced large fluctuations during the period 2012–2020. Qinghai as a whole showed an upward trend, but there were large fluctuations in 2019; Gansu Province increased year by year from 2010 to 2015, and showed a steady trend from 2016 to 2018, and a rapid upward trend in the next two years. Henan’s index is the highest in 2020. In 2010, the top three innovation scores were Qinghai (0.1512), Shaanxi (0.1312) and Inner Mongolia (0.1176); in 2015, the top three were Gansu (0.5976), Sichuan (0.4262) and Shaanxi (0.4058); in 2020, the top three were Henan (1.0001), Sichuan (0.9928) and Shandong (0.9781). In terms of ranking and innovation development index, nine provinces have experienced rapid innovation development during these 11 years. Among them, Henan Province grew steadily from 2010 to 2017. The growth rates in 2018 and 2020 are significant, which is the biggest increase in nine years. The trend of the Innovation Development Index (IDI) shows that the provinces are paying particular attention to innovation and have achieved significant results in this regard, and according to the trend, the IDI will continue to increase in the coming years. The trend in the Innovation Development Index (IDI) shows that the provinces are paying particular attention to innovation, and that they have achieved significant results in this area. The trend predicts that the index will continue to increase in the coming years. Innovation is the first driving force of development, and the high-quality development of urbanization cannot be separated from innovation.

Coordination dimension. As shown in Figure 7, from the perspective of coordination degree, the coordination development index of the nine provinces in the Yellow River Basin from 2010 to 2020 has great volatility, but the overall trend is upward. Ningxia had the largest increase in the Coordinated Development Index (CDI) of 0.8415 over the 11 years, followed by Sichuan with a 0.8189 increase. The smallest increase was in Shadong, only 0.1754, followed by Shanxi, with an increase of 0.2555. In 2010, the top three in the Coordinated Development Index were Shandong (0.3648), Shanxi (0.3559) and Shaanxi (0.3346). In 2015, the top three were Shanxi (0.7410), Shandong (0.7056) and Inner Mongolia (0.7046). In 2020, the top three were Ningxia (0.8415), Sichuan (0.8189) and Qinghai (0.7661). Overall, the coordinated development of the nine provinces has improved, but the coordinated development index is lower than 0.85, and the coordinated development fluctuates greatly. The coordinated development index of Qinghai, Sichuan, Inner Mongolia and Shandong showed a significant turn in 2019. Except for Shaanxi and Henan, the coordinated development index of the other seven provinces showed an upward trend in 2020, Among them, Sichuan, Ningxia, Qinghai and Shandong increased significantly, 0.3368, 0.3069, 0.2818 and 0.1380, respectively. It means that the problem of unbalanced development still needs to be considered, and there is still a lack of development in coordination.

Green dimension. As shown in Figure 8, from 2010 to 2020, the green development indices of nine provinces in the Yellow River Basin showed alternating trends of decline and increase, but the overall trend was upward. Except for Qinghai, Shaanxi and Shanxi Provinces, the green development indicators of the other five provinces showed a downtrend in 2011, and the green development level of nine provinces was the lowest. In addition to the year-on-year growth trend of Qinghai after 2015, the green development indicators of the other eight provinces fluctuated greatly from 2010 to 2020, with a significant turn in 2019 and an upward trend in 2020. In 2010, Shandong (0.4395), Ningxia (0.3770) and Shaanxi (0.3753) ranked the top three in the green development index; in 2015, the top three were Inner Mongolia (0.5423), Shaanxi (0.5308) and Shandong (0.5274); in 2020, the top three were Gansu (0.9649), Henan (0.9289) and Qinghai (0.8807). In terms of ranking and green development index, there was a big gap in green development among provinces, and the level of green development in economically underdeveloped areas was relatively high, which indicated that we should be concerned about the simultaneous development of the economy and environment in the course of economic development. In 2020, the green development index of all provinces in the Yellow River Basin was in the rising stage, which indicated that although the ecological environment of each province had been greatly improved, the level of green development still needs to be improved. Therefore, in the course of high-quality development and construction of urbanization, provinces should focus on the development of green industry, reduce the total water consumed per unit GDP, develop clean energy and reduce the per capita main pollutants in exhaust gas discharge capacity; adopt more advanced science and technology or process to improve the pollution-free treatment rate of domestic waste; and promote the transformation of the pipe network system to improve the treatment rate of urban sewage. Through the comprehensive utilization rate of general industrial solid waste, the improvement in green coverage rate of built-up area and the increase in per capita water resources, the high-quality development of urbanization can be promoted in Figure 8.

Openness dimension. As shown in Figure 9, from the openness dimension, the opening development indexes of Qinghai, Sichuan, Gansu, Ningxia and Shandong showed a downward trend from 2010 to 2014. The opening index of Sichuan and Gansu provinces showed a significant turning point in 2016, and then showed an uptrend. The opening development index of Shaanxi increased steadily in the past 11 years, while Inner Mongolia and Shanxi fluctuated greatly, but the overall situation was still on the rise. Ningxia and Henan peaked in 2017. Only Shaanxi grew steadily. According to the trend in the figure, the open development index of most provinces and cities decreased from 2010 to 2015 and increased significantly except Qinghai in the following years. The highest opening development index reached 1.0001 points in 2020. It can be seen from the figure that there had been an obvious turning point in the opening development from 2015 to 2017, which may be due to policy changes; the opening development index of Qinghai, Sichuan, Gansu, Ningxia, Inner Mongolia and Henan provinces showed a downward trend in 2020, which may be due to the ravage of novel coronavirus and the national epidemic prevention policy. In recent years, although the state has encouraged opening-up and the provinces have paid attention to it, due to the epidemic prevention and control, the opening-up development of the provinces has been restricted to a certain extent. From the perspective of the trend, it will still decrease in the following years.

Sharing dimension. As shown in Figure 10, from the sharing dimension, the sharing development index of provinces in the Yellow River basin changed greatly from 2010 to 2020, and it was basically on the rise. Except for Sichuan, Ningxia and Shaanxi, the sharing development index of other six provinces showed an upward trend in 2020. Among them, Inner Mongolia, Shangdong, Henan, Gansu and Qinghai showed a sustained growth trend, and the growth rates were 0.9272, 0.9248, 0.8793, 0.8097 and 0.6601, respectively. Sichuan, Ningxia, Shaanxi and Shanxi showed an upward trend of fluctuation. In 2010, the sharing development level of all provinces was at a low level. The top three shared development indexes were Qinghai (0.1882), Sichuan (0.0426) and Shandong (0.0392); in 2015, the top three were Shaanxi (0.6709), Ningxia (0.6337) and Henan (0.6189); in 2020, the shared development index was greater than 0.8257, and the top three were Shandong (0.9640), Inner Mongolia (0.9273) and Shanxi (0.9149). These changes showed that in the high-quality development of urbanization, the urban–rural gap had been narrowing, the public serviceability had been improved. The livelihood work such as social security had been carried out well, and the improvement in shared development level had made all members of society have a greater sense of gain and happiness.

4.4. Spatial Correlation Analysis

Global spatial autocorrelation. The purpose of spatial autocorrelation analysis is to study whether there is a spatial correlation of urbanization development level in each province. The Moran index is used to measure the correlation between two adjacent regions, and its value range is between (−1, 1). When the Moran index is greater than 0, it indicates that there is a positive correlation between the urbanization level of the observed area and the adjacent areas, showing the agglomeration effect, and the larger the value, the stronger the spatial correlation; on the contrary, when the Moran index is less than 0, the observed area and the adjacent areas present a negative spatial correlation; when the Moran index is 0 and the test result is significant, it indicates the urbanization of the observed area The horizontal distribution was independent and random. This paper uses the global Moran index to reflect whether there is spatial correlation in urbanization level on the basis of spatial correlation analysis of the adjacent spatial weight matrix. Stata16.0 software was used to calculate the global Moran index of urbanization level (

Table 8. Overall Moran index of urbanization development level.

Year	I	Z	P
2010	−0.032	0.433	0.333
2015	−0.304	−0.780	0.218
2020	−0.027	0.432	0.333

) and draw a Moran scatter diagram (Figure 11). The table below shows that the annual averages of 2010, 2015 and 2020 did not pass the significance test (z > 1.96, p < 0.05), demonstrating that there was no spatial correlation between the urbanization development levels of provinces in the Yellow River Basin, and there was no obvious spatial clustering feature.

Partial spatial autocorrelation. The Moran scatterplot (Figure 11) was drawn using Stata 16.0 software to perform local spatial autocorrelation analysis on the level of high-quality urbanization development in nine provinces in the Yellow River Basin from 2010 to 2020, which more intuitively reflects the focused level of urbanization in each province. This paper gives the Moran scatter plots based on the adjacency spatial weight matrix for 2010, 2015 and 2020. It should be noted here that the numbers 1–9 in the figure correspond to nine provinces in the Yellow River Basin: Qinghai, Sichuan, Gansu, Ningxia Hui Autonomous Region, Inner Mongolia Autonomous Region, Shaanxi, Shanxi, Henan and Shandong provinces, respectively.

According to Figure 11, we can see that the provinces of the Yellow River Basin in the coordinate system position are more scattered, and the slope of the line always has negative values, which shows that the nine provinces of the Yellow River Basin urbanization of high-quality development level do not exhibit the spatial aggregation phenomenon, which also shows again that the Yellow River Basin provinces of urbanization of high-quality development do not exhibit spatial autocorrelation, the development of the provinces shows no synergistic characteristics.

4.5. Systematic Clustering Analysis

The average indicator data of nine provinces in the Yellow River Basin from 2010 to 2020 were systematically clustered using SPSS26.0 to obtain a spectral map, which mainly reflects the process of gradual merging of samples, and the clustering results are more intuitive, as shown in Figure 12.

From the spectral map obtained from the cluster analysis, this paper divides the nine provinces in the Yellow River Basin pathway into four categories: the first category includes Shandong and Inner Mongolia, with the highest level of high quality urbanization development; the second category includes Henan, Shanxi, Shaanxi, Sichuan and Ningxia, with relatively high quality urbanization development; the third category includes Qinghai, with relatively low quality urbanization development; and the fourth category includes Gansu, with the lowest development. Although there is no spatially aggregated feature of high-quality urbanization development in each province of the Yellow River Basin, there is some quantitatively clustered feature. The resulting ArcGIS visualization of the level of high-quality urbanization development in each province of the Yellow River Basin is shown in Figure 13.

Figure 13 shows that the overall urbanization quality development level is strong in the lower reaches of the Yellow River Basin and weak in the midstream and upstream. As the region with the highest level of urbanization development, Shandong has unique geographical conditions, convenient transportation, a high level of economic development and openness to the outside world, ecological emphasis on environmental protection and remediation, high environmental quality and better promotion of livelihood security; Sichuan, Ningxia, Shaanxi, Shanxi and Henan, as regions with a relatively high level of urbanization development, are mainly concentrated in the central and western regions, with good urbanization development trends and achievements in recent years. However, the main reason for restricting the development of urbanization is the uncoordinated and unbalanced development of regional urbanization, the weak driving force of regional central cities, and the small number of big cities, which will have difficulty playing the role of driving urbanization; Qinghai and Gansu, as two provinces with a low level of urbanization development, are located in the inland northwest, and the inconvenient transportation makes the opening up not strong enough, and the economic level is seriously lagging, which makes it impossible to attract a large number of talents and leads to urbanization. The process has been slow, and the next step is to continue to integrate deeply into the “One Belt, One Road” development strategy and promote the optimization and upgrading of the economic structure of the western region.

The study found that the urbanization development level of nine provinces in the Yellow River Basin showed an increasing trend from 2010 to 2020. The growth in the quality level of urbanization has benefited from the development of the five dimensions in each province, with the innovation, coordination, green and sharing indexes fluctuating but showing an overall uptrend, but the openness index showed a descending trend in some provinces from 2010 to 2014 before increasing, which to some extent restricted the improvement of the quality level of urbanization development in their provinces. The development of the provinces in the five dimensions is not balanced, and most of them are underdeveloped in one or more aspects. The high-quality urbanization development of the provinces in the Yellow River Basin has been growing rapidly in the past nine years, and the urbanization level of each province in 2020 is no longer the same compared to 2010, in which Sichuan Province has increased the most, while Inner Mongolia still falls in the ranking despite the growth, and the development among the provinces is mixed. At the same time, through the spatial correlation analysis, it is found that there is no obvious clustering feature in the urbanization quality development level of each province in the Yellow River Basin, indicating that each province still develops relatively independently and has not formed a good interaction, but the urbanization quality development level of nine provinces has a numerical clustering feature. The level of urbanization development in the Yellow River Basin declines from downstream to midstream to upstream provinces, and the level of urbanization in the lower Yellow River provinces is much higher than that in the upper and middle provinces. Such spatial differences are related to the geographical location, resource conditions and policy support of the nine provinces, with the lower Yellow River having favorable geographical conditions, convenient transportation, better development of secondary and tertiary industries, and a higher level of urbanization. The middle reaches of the Yellow River, that is, the central part of China, is generally an agricultural area, with a relatively large agricultural population, and the urbanization process is not as fast as in the eastern part of the Yellow River basin. The upstream of the Yellow River, that is, the western part of China, has a remote location, inconvenient transportation, harsh climatic conditions, and the process of urbanization is slightly slow.

Urbanization is multifaceted and the statistical data in this paper are still incomplete, and due to limited research capacity, it is difficult to exhaust all relevant indicators of quality development, and only the most representative ones were selected to the maximum extent possible. Meanwhile, this paper mainly analyzed the level of high-quality development of urbanization in nine provinces in the Yellow River Basin from the aspects of time and space but did not argue the specific factors that influence the high-quality development of urbanization. With the proposal of ecological conservation and high-quality development strategy of the Yellow River Basin in 2019, it is necessary to further explore how the influencing factors act on the high-quality development of urbanization, which can be followed up with further research in terms of influencing factors.

5. Conclusions and Suggestion

The Yellow River Basin is vital to China’s economic and social development and eco-safety. The high-quality development of urbanization in the basin can promote the economic transformation of individual provinces. However, the Yellow River Basin ecosystem is characterized by diversity and relative vulnerability. In recent years, the rapid urbanization of the Yellow River Basin provinces has led to uneven development, while the ecological environment of the Yellow River Basin has also been seriously damaged, posing serious challenges to the sustainable development of the region. The study of the quality development of urbanization in the Yellow River Basin can effectively improve the quality of urbanization construction and put forward improvement measures and suggestions according to the existing problems at the present stage to better carry out urbanization construction. To this end, this study referred to the relevant literature on the urbanization development index system and constructed an evaluation index system on the basis of the actual circumstances of urbanization in the Yellow River Basin provinces, adopted the standardized method to quantize the raw index data, determined the weight of each index by entropy method, and applied the linear weighting function method to calculate the comprehensive score of urbanization development level, to determine the level of urbanization development and conduct a comprehensive analysis and evaluation.

Looking at the changes in the time difference of each dimension of the high-quality development of urbanization in various provinces, it can be seen that the development index of the five dimensions of most provinces showed a significant turn in 2019, showing a trend of first falling and then rising in the three dimensions of coordination, innovation and green, and a trend of first rising and then falling in the two dimensions of openness and sharing. In 2020, the innovation, green, coordinated and shared development index of most provinces is in an upward trend. Except for Henan, Shaanxi and Shandong, the open development index of the other six provinces is in a downward trend. This development trend is mainly caused by the changes in national policies and the outbreak of the epidemic. The proposal of the ecological protection and high-quality development strategy of the Yellow River Basin in 2019 urges the provinces in the Yellow River Basin to take into account the economic growth rate and the quality of economic development and promote the high-quality development of urbanization from the five dimensions of innovation, coordination, green, openness and sharing. Therefore, the development trend in the five dimensions is as follows: concentrate on developing innovation capacity, increase the opening up and promote the sharing of resources. However, due to the teething period of high-quality urbanization development, the provinces are in the exploratory stage of green and coordinated development, resulting in the reduction of the green and coordinated development index of most provinces and cities. The outbreak of the pandemic in 2020 is both a challenge and an opportunity for the high-quality development of urbanization. The continuous spread of the epidemic in the world and the entry control have restricted the opening-up and development of the provinces, resulting in the decline in the opening-up and development index of the provinces in 2020. Under the severe situation of the epidemic, the high demand of the country for scientific and technological innovation and the emphasis on science and technology and education are the main reasons for the rise in the innovation development index of all provinces in 2020. The restriction of the epidemic on human activities has led to the reduction in the per capita emission of major pollutants in the exhaust gas and the improvement in the comprehensive utilization rate of general solid wastes; thus, achieving the increase in the green development index of each province in 2020. The epidemic prevention and control has reduced the flow of people, and the number of permanent residents in all provinces has decreased, leading to the increase in the indicators of the sharing dimension; thus, achieving the growth of the sharing development index in 2020. The epidemic has affected residents’ employment, income and consumption, and has had a greater negative impact on urban residents, indirectly promoting the growth of the coordinated development index in 2020. Under the background of normalized epidemic prevention and control, provinces should innovate various investment models to attract foreign capital, give full play to the advantages of digital finance and provide contactless financial services. On the basis of responding to the national epidemic prevention and control, we will achieve innovative, coordinated, green, open and sharing balanced development and high-quality urbanization.

The theoretical contribution of this paper has two points. The first of these is the construction of a reasonable and feasible urbanization quality development evaluation index system. This paper took the five development concepts as the primary indicators and constructed 31 secondary indicators to determine the final score to demonstrate the development level of urbanization. By comparing the level of urbanization development each year, the weaknesses and deficiencies in the process of urbanization development can be identified, and in response to the weaknesses and deficiencies, the development plan can be adjusted in time to ensure the high level and quality of urbanization development, and the sustainability of high-quality urbanization development, in compliance with the national strategy of high-quality economic development. Second, it built a reasonable overall framework for evaluating high-quality urbanization development. This paper compared the development of urbanization in each province from 2010 to 2018 and used spatial correlation analysis and cluster analysis to analyze the high-quality development of urbanization from both time and space perspectives to understand the development status of urbanization. The article studied the level of urbanization development and the time and space pattern in the Yellow River Basin and drew out the development of urbanization in each province of the Yellow River Basin, prompting urbanization development to adapt to economic and social development, which is significant for promoting the coordinated development of urbanization and the high-quality development of urbanization in the Yellow River Basin. The index system and high-quality evaluation framework constructed in this paper can give a reference for the evaluation of high-quality development in other river basins, other provinces and cities.

It is essential to recognize that the high-quality development of urbanization is not just a certain aspect of urbanization but also comprehensive development with innovation, coordination, green, open and sharing as indispensable. However, based on striving for balanced development, each province should face up to its strengths and weaknesses in the light of local conditions, and build on its strengths and avoid its weaknesses. Shandong Province should make the most of its coastal advantages to promote the transformation and upgrading of the industrial structure, strengthen the development of scientific and technological innovation and protect the ecological environment. Shanxi is a resource-based province, and it is important to avoid a single economic structure and reduce damage to the natural environment while using coal resources for development. Henan, as a large agricultural province, should vigorously promote agricultural modernization to turn agriculture from a disadvantage into a regional advantage. Shanxi and Henan, as provinces in the midstream areas of the Yellow River Basin, should seize the national regional development strategy of promoting the rise of the central area and promote the high-quality development of urbanization. Inner Mongolia should continue to promote the development of the energy and heavy industry sectors and improve the regional economic development system, while at the same time promoting scientific and technological progress, increasing investment in innovation, and vigorously cultivating innovative talents. Shaanxi, Gansu, Ningxia, Qinghai and Sichuan, as the upstream areas of the Yellow River Basin, should face the regional disadvantages, pay attention to environmental protection in the pursuit of development, take advantage of the “One Belt One Road” strategic concept, make use of the new round of western development strategy and the national strategy of ecological conservation and high-quality development of the Yellow River Basin and increase market development. Additionally, it should improve the level of openness on the basis of meeting the epidemic prevention requirements, attract foreign investment and promote the upgrading of the economic structure of the western region. Secondly, the concept of a new type of urbanization with coordinated economic, ecological and social development should be actively established, and urbanization development strategies should be scientifically formulated following the current stage of urbanization development in each province, to further transform urban development patterns, optimize industrial structures, improve green development capabilities and solve the problem of urban environmental degradation. After realizing the gap between the upstream and midstream areas of the Yellow River Basin and the downstream areas, we should focus on building and developing the upper and middle reaches, while the downstream areas should play a good engine and driving role while vigorously developing urbanization, and try our best to reduce the gap between the development of each province in the Yellow River Basin and finally embark on a healthy road of urbanization development after achieving regional coordinated development. Third, actively respond to the impact of COVID-19 on society, economy and people’s lives. All provinces should deeply understand the impact of COVID-19 on their own high-quality urbanization development, identify weak links, take precise measures, and explore new paths for high-quality urbanization development under the background of normalization of epidemic prevention.