1. Introduction
Green development is an inevitable choice for human development. It is a deep-seated exploration of the harmonious coexistence mode between humans and nature in response to global resources and environmental problems [
1]. Green development is a new development model combining the economy, society, and ecology and has important guiding significance for social policy adjustment and development focus correction. As one of the fastest growing emerging industrialized countries, China’s gross domestic product (GDP) increased from CNY 367.9 billion in 1978 to CNY 11400 billion in 2021. China’s rapid development depends on the rapid growth of its industrial level, but the traditional extensive manufacturing mode has caused great pressure on China’s resource supply and environment. There is an urgent need to adjust the corresponding green development strategy to achieve efficient, balanced, and harmonious development [
2,
3,
4]. At present, the research on China’s green development is mostly based on the first-tier, second-tier cities, or township areas with obvious particularity [
5,
6,
7,
8], lacking universal research on the existing large number of small and unobvious county characteristics [
9]. Therefore, in order to cope with the environmental pollution and resource depletion caused by the gradual expansion of the county’s economy, it is urgent to put forward corresponding countermeasures for the county’s green development.
Hunan Province is located in south-central China, rich in natural resources and humanistic color. It puts forward the goal of ‘promoting ecological civilization and building a beautiful Hunan’, and its green development policy is gradually improving. Based on the good local natural resources, various regions of Hunan Province have formed green development forms with local characteristics [
10]. With the rapid development of agriculture and industry in recent decades, problems such as a shortage of resources, environmental damage, and ecological degradation have led to a reduction in the environmental capacity in Hunan Province, thus affecting the green development of the region. Agriculture is the main industry in the northeastern part of Hunan Province, and the disturbance of the environment by human activities is more serious. Therefore, the green development index in Hunan Province showed a downward trend from 2005 to 2020, and the index in the northeast was the lowest. It is urgent to formulate new policies to achieve green development.
Research on the evaluation of urban green development evaluation can be divided into the evaluation index selection [
11,
12,
13,
14], the index weight setting [
15,
16,
17,
18,
19,
20,
21,
22,
23,
24], the green development framework’s construction and model evaluation [
25,
26,
27,
28,
29,
30,
31], and the spatial-temporal change and driving mechanism of green development [
32,
33,
34,
35,
36]. The evaluation index selection is a key factor affecting the conclusion of urban green development evaluation. The United Nations Commission on Sustainable Development (UNCSD) has designed a system for sustainable development covering 134 indicators in the economic, social, and environmental fields [
37]. The World Bank takes national wealth as the basis for measuring sustainable development and builds a sustainable development index system composed of natural capital, artificial capital, human capital, and social capital. In addition, countries have actively explored and practiced sustainable development index systems at different scales [
38,
39,
40,
41], such as the European urban sustainable development index system, the Manuka New Zealand sustainable development index system, and the United States Seattle community sustainable development index system, etc. [
42]. Therefore, the three-pillar model combining social systems, economic systems, and environmental systems is widely used because of its simple and comprehensive characteristics [
11,
12,
13]. Chinese scholars believe that social systems, economic systems, and environmental systems are the three elements of urban green development. Yuan, Li et al. constructed a sustainable development index system including the economy, society, and the environment to evaluate the sustainable development capacity of municipalities and provincial capitals in China [
43,
44]. In addition, some researchers choose green GDP [
45,
46], green economic efficiency [
47,
48,
49], or green economic indicators [
50,
51] as indicators of urban green development. However, most studies focus on national provinces and municipalities, and few studies exist on green development evaluations from a county perspective [
52,
53]. Wei et al. applied resources and environmental carrying capacities (RECC) to explore the relationship between regional economic development and environmental carrying capacity, analyzed the specific characteristics of each functional area in the county, and provided a reference for optimizing the spatial pattern of land and further deepening green development [
54]. She et al. studied the constraints of infrastructure sustainability to effectively improve the sustainability effect and provide a reference for the long-term green development of counties [
55]. In addition, Cheshmehzangi et al. realized a dual-carbon management plan through comprehensive evaluations such as SWOT analysis and fluid dynamics (CFD) simulation, providing a reference for the county’s low-carbon transition and sustainable energy planning [
56].
The index weight setting is also an important part of urban green development evaluation, which can be divided into subjective weighting methods [
15], objective weighting methods [
16,
17], and combined weighting methods [
18,
19,
20]. Subjective weighting methods, such as the Delphi method [
21], the Analytic Hierarchy Process (AHP) method [
22], etc., reflect the subjective judgment and intuition of the evaluators. The Delphi method was used to determine the index entropy to evaluate the green economy differences in different provinces and cities in China [
25]. However, the objectivity and reproducibility of these methods are relatively poor. Objective weighting methods, such as the entropy weight method [
23], deviation maximization method [
24], etc., adopt relatively perfect mathematical theories and methods but do not consider the subjective information of the evaluator. Gang et al. used multiple linear regression analysis to analyze the development of the green economy in 30 provinces in China and found that the overall development was good, but the regional polarization was severe [
57]. Yin et al. used the entropy weight method to study the green economy level of 30 provinces in China in 2015 and found significant regional differences [
58]. Although these methods can comprehensively elucidate the development of a regional green economy, they cannot fully reveal the internal development constraints. In order to embody the advantages of the above two methods at the same time, a combined weighting method is proposed and widely used.
Various mature analysis frameworks and measurement methods have been formed for the construction and evaluations of green development frameworks. Kim et al. conducted a cross-country comparison of green growth in 30 countries by using the OECD assessment framework [
26]. Based on the Green Growth Knowledge Platform, Lyytimäki et al. constructed a series of key green growth indicators for Finland [
27]. Xu et al. used SEA technology to improve the efficiency of municipal solid waste treatment and ensure the sustainable development of urban economic, social, and environmental coordination [
59]. LI et al. developed the Full Permutation Polygon Synthetic Indicator method (FPPSI) to comprehensively evaluate and give recommendations for different stages of urban development [
60]. Zhou et al. improved the urban sustainability evaluation system and further improved the accuracy and pertinence of their conclusions by incorporating the attitude indicators of decision makers [
61]. Zhu et al. established an object–subject–process framework system and analyzed the global green development practice and policy effect evaluation model [
29]. Wu et al. used the DPSIR model to evaluate urban green development in Beijing, taking into account resource depletion, environmental damage, and ecological benefits [
30]. Guo et al. used the Urban Development Index (CDI) framework to evaluate the sustainable development of China’s municipalities from five dimensions: infrastructure, waste treatment, health, education, and urban output [
28,
30,
31]. Na and Martin et al. used SEB, DEA-BCC, and other models to analyze the green economic efficiency of Chinese cities in different years, and found that technological progress is the main driving force restricting the development efficiency of the urban green economy [
48,
49].
The spatial-temporal change and driving mechanism of green development have been concerned with the spatial heterogeneity of specific research objects. Similarly, the study of green development is bound to explore the occurrence, change, and impact of differences in green development. Zhang and Chen et al. used panel data to analyze regional green development levels, spatial relationships, and their heterogeneity characteristics in China [
33,
34]. Hasan et al. used the LMDI model to analyze the economic scale, industrial structure, and technological progress of German green development [
35]. Cheng et al. used the projection pursuit evaluation model and the methods of Gini coefficient, coefficient of variation, spatial autocorrelation, and spatial measurement to analyze the temporal and spatial evolution trajectory and impact mechanism of green development in 30 provinces and cities in China [
32,
36].
In general, China’s green development evaluation is still in its infancy, and the statistics department has not systematically conducted statistics on the relevant indicators of green development evaluation. The existing research results are quite different in the structural design of the index system. Therefore, it is urgent to establish a hierarchical index system reflecting the coupling of natural, economic, and social systems to reveal the continuous operation mechanism of the complex and giant system of regional development. At the same time, this method should be relatively easy to calculate, and the results are intuitive and easy for decision makers to understand and apply. Therefore, this paper takes 88 counties in Hunan Province, as the research object and uses principal component analysis, analytic hierarchy process, and ArcGIS spatial visualization to scientifically and objectively explore the spatio-temporal changes and limiting factors of green development in Hunan counties. The DPSIR model is used to construct a green development evaluation index system, define the connotation of green development, and reveal the constraints affecting regional green development.
4. Discussion
In this paper, the interaction factors of each link are considered, and green development indicators are set based on the DPSIR model. In addition, combining PCA and AHP to determine the index weights avoids the uncertainty of subjective weighting methods such as the Delphi method [
21]. At the same time, with the support of ArcGIS and Geoda software, spatial visualization analysis is carried out. The results show the spatial differences in green development in the counties of Hunan Province and some factors that cause these differences. There are still differences in the green development models among the counties in Hunan Province, which still need to learn from each other to improve. The level of green development in the coastal areas of China is relatively high, while the level of green development in the northwest region is relatively lagging [
57,
58,
62]. The research conclusions of Deng et al. [
10] are similar to the evaluation results of this paper, both concluding that stable ecosystem development is needed in Hunan Province. It can be seen that the development trend of the green development index in Hunan Province is almost the same as that in China’s inland provinces. However, there is variability in the results for the spatial distribution of development levels. Starting from a micro perspective, this paper takes each county as the unit of research and identifies problems such as the slowing down of green development and large regional differences in development in Hunan Province. The reasons for this may be related to policy development, industrial restructuring, and pollutant treatment levels in each county. This phenomenon verifies the hypothesis in the introduction. Due to the rapid development of agriculture and industry in the past two decades, Hunan Province has neglected the protection of environmental resources and ecology, so the green development index has shown a downward trend, especially in the northeastern region dominated by agriculture, which is greatly affected by human interference, and has the lowest green development index.
The contradiction between economic development and environmental protection has existed for a long time. Therefore, while promoting economic development and social progress, it is also necessary to always pay attention to resource conservation and environmental protection. It is very important to seek a balance between economic growth and the harmonious development of the environment. The green development mode is a deep exploration of the harmonious coexistence model between human beings and nature when dealing with today’s global resource and environmental problems [
45,
46,
47,
48,
49,
50,
51]. In addition, green development is not a stylized model but needs to be comprehensively judged according to the social, economic, and environmental conditions of different regions and explored from multiple perspectives and in-depth levels to discover the inhibitory factors that affect the harmonious development of cities [
54,
55,
56]. It is not difficult to find that the improvement in the level of green development requires coordination and improvement in various factors. The government should play an active role in macro-control, such as increasing R&D investment in energy conservation, emission reduction, and resource utilization; reasonably formulating relevant laws and regulations; further strengthening the control of pollutant discharge and resource waste; encouraging the development of emerging green industries; advocating for the optimization and improvement of industrial structure and provide corresponding subsidies and technical support for farmers; and reducing damage to cultivated land, forest land, and rivers. In addition, enterprises should introduce relevant environmental protection technologies to improve production efficiency and reduce the waste of resources in the production process. Finally, residents need to raise awareness of environmental protection and promote the concept of green development. Only through multi-party coordination can the level of green development be comprehensively improved.
On the whole, it is necessary to correctly understand regional differences and apply local advantageous conditions to formulate relevant green development methods. In addition, there are also significant differences in the level of green development in different regions of China. Therefore, it is necessary to strengthen exchanges and cooperation between provinces and cities and introduce advanced management experience and technical means. It is also necessary to speed up the transformation of old industries in the northwest region and increase production capacity, to reduce pollution emissions and speed up economic development. At the same time, it is also necessary to strengthen the urban infrastructure construction, maintain the balance between economic development and environmental protection, and improve the overall level of green development.
5. Conclusions
The results show that the counties in Hunan Province have achieved good results in the early stage of green development, and show a trend of steady improvement. However, in recent years, the level of green development has declined significantly. Although it has eased in 2020, the proportion of highly competitive green development regions is still insignificant, indicating that counties in Hunan Province urgently need to change their green development models. From 2005 to 2020, the county green development index showed an agglomeration distribution (HH and LL). The overall ranking of the green development index was in the order of eastern counties > central counties > northeast counties > southwest counties, and the difference between western counties and northwest counties is not obvious. In addition, from 2005 to 2020, the green development level of each county has obvious spatial differentiation characteristics. It is worth mentioning that the D and P systems have a significant role in promoting the green development of the county, while the S and I systems have a certain role in promoting the green development of the county. Based on the evolution mechanism of green development in Hunan Province, this paper studied the new green development evaluation system and put forward three suggestions for green development in Hunan Province as follows:
- (1)
According to the comprehensive judgment of the social, economic and environmental conditions in Hunan Province, investigate in-depth from multiple angles and levels to discover the restrictive factors of green development and implement ecological compensation or industrial transformation measures to reduce the restrictive effect.
- (2)
The government could increase investment in energy conservation, emission reduction, and resource utilization; strengthen the control of pollutant discharge and resource waste; and encourage the development of emerging green industries.
- (3)
Strengthen exchanges and cooperation between provinces and cities and introduce advanced management experience and technical means. Strengthen urban infrastructure construction, increase industrial production capacity, reduce pollution emissions, and ensure a balance between economic development and environmental protection.
This study couples the SD and DPSIR models, and establishes a green development index model from the five aspects of driving force, pressure, state, impact, and response, combining resources, the ecological environment, and socioeconomic indicators. However, the selection of evaluation indicators is subject to a certain degree of subjectivity, and this study fails to accurately predict the future green development of Hunan Province. Future research should adopt scenario simulation to predict green development as the research direction.