The rural decline which emerged in the process of human development and transformation has become a global trend, and rural revitalization is urgently needed. It is the only way to realize rural revitalization and sustainable development by scientifically and systematically grasping the development and evolution of rural regional systems, revealing the interaction mode of rural system and external development environment, as well as improving the rural resilience to resist and adapt to changes in the external environment. The article analyzes the development and evolution of rural regional systems and rural revitalization from the perspective of rural resilience. The study found that: (1) Rural resilience includes the resilience, adaptability and transformation ability of the rural system to the impact of external disturbances. (2) Rural development evolution differentiation is a comprehensive representation of the interaction between rural regional systems and the dominant factors of external development. In this process, the resilience of rural systems in different regions to resist external development disturbances has been improved or declined. (3) Creating multi-functional villages, implementing rural rectification projects, and cultivating rural social capital play an important role in promoting the construction of rural resilience. The article emphasizes that the rural regional system should be scientifically identified and differentiated implementation plans are formulated to cultivate and enhance rural resilience to achieve balanced function, structure and operation of rural system.

The agricultural regional function is an important scientific problem in agricultural geography research, and it is also the important practical issue related to the national food security and sustainable development of regional agriculture. Taking the Bohai Rim region of China as an example, this paper identified the agricultural regional function as four types including agricultural products supplying function (APF), labor employment and social security function (LEF), ecological conservation function (ECF), and cultural heritage and recreational function (CRF) and their spatial pattern and evolution process were explored. The study also identified the agricultural regional type and the impact factors affecting the four functions using cluster analysis method and spatial econometric model. The results indicate that: Firstly, the degrees of spatial concentration of the APF, LEF and CRF were low, while that of the ECF was high. The spatial distributions of the four functions presented obvious regularity. Secondly, the APF enhanced largely, its center of gravity was further concentrated in plain agricultural areas. The high value areas of the LEF shifted from inland to coastal areas. The ECF of hilly areas further highlighted. Advantage areas of the CRF were concentrating in the municipal districts and their surrounding counties. Thirdly, the leading counties of the APF were distributed in central and southern plains of Hebei province, the impact plain of northwest Shandong, the Jiaolai plain and the west of Liaohe plain. The leading counties of LEF were distributed in piedmont plain of Yanshan and coastal plain of Hebei province, Jiaodong Peninsula and the Yellow River Delta region. The leading counties of the ECF were distributed in Bashang plateau, mountainous region of Yanshan, hilly area of eastern and western Liaoning province, and the surrounding areas of Beijing-Tianjin-Hebei urban agglomeration. The leading counties of the CRF were distributed in the surrounding areas of central-south Liaoning urban agglomerations, Beijing-Tianjin-Hebei metropolitan region and Jinan metropolitan area. Comprehensive counties were distributed in the Huang-Huai plain and hilly areas of central-south of Shandong province. Fourthly, natural factors possessed a significant impact on the formation of the three functions including APF, LEF and ECF, while social and economic factors on the impact of the four functions were quite different. The study reveals the regularity and influence mechanism of the evolution of agricultural regional function, which can provide theoretical basis for scientific guidance of regional division of labor, strengthening of leading function, highlighting regional value and promoting regional coordinated development.

Green development is pivotal to resolving natural environmental constraints, solving national economic transition, and supporting and realizing the United Nations sustainable development goals. It is gradually growing into a crucial guideline for China's ecological civilization construction, "Beautiful China" development, and global economic transition and restructure. Based on a thorough review of the concept of green development, this paper accurately depicts a full picture of China's spatio-temporal patterns of urban green development efficiency (UGDE) in 2005-2015 by using SBM-Undesirable, the Theil index and the Spatial Markov Chain methods. Moreover, the influencing mechanism has been further discussed based on a quantitative analysis of both natural and human factors. Our results demonstrate that: (1) UGDE increased steadily by 10% from 0.475 in 2005 to 0.523 in 2015. And temporally, it shows a pattern of "W"-shaped fluctuated growth. (2) Spatially, UGDE decreased from eastern to central China, and further to western China. Besides, there is an inverted pyramid pattern of "national level > regional level > local level" urban agglomeration in UDGE growth. Moreover, there is a steady urban scale structure from super city to small city in UDGE. (3) There is an evident concentration of cities with high-level and low-level UDGE, indicating a significant influence of path dependence. (4) Quantitatively speaking, compared to natural factors, human factors such as economy size, industry structure, and openness level play a more important role in influencing the UDGE.

Agglomeration externality is an important mechanism for reducing industrial pollution emission. Different agglomeration patterns correspond to different pollution emission behaviors and effects. Based on the theory of agglomeration economies and the industrial data from 285 China's prefecture-level cities, this paper differentiates the agglomeration patterns into different types such as agglomeration density, geographical proximity, specialization, diversity, related diversity, and unrelated diversity from the spatial and organizational perspectives, and investigates the spatial patterns of industrial SO₂ pollution intensity and industrial agglomeration levels, and examines the effects of different agglomeration types on industrial SO₂ emissions by building econometric models. The main conclusions are as follows: (1) There exists the asymmetric spatial distribution between the industrial SO₂ pollution intensity and the industrial agglomeration levels. The pollution intensity is higher in the west, but lower in the east. The levels of agglomeration density, geographic proximity, diversity, related diversity and unrelated diversity are higher in the eastern and central regions, but lower in the western. (2) There is the spatial spillover effect of industrial agglomeration on industrial SO₂ pollution. The geographical agglomeration, diversity, and related diversity in neighboring regions have a negative impact on industrial pollution, while specialization has a positive effect. (3) Raising the agglomeration scale and guiding enterprises concentrated in industrial parks can help to reduce industrial SO₂ emissions, and promoting the diverse and related industrial agglomeration is conducive to pollution reduction, while unrelated industries agglomeration will increase pollution emissions. (4) The impact of industrial agglomeration on industrial SO₂ emissions has a notable spatial heterogeneity. Agglomeration density, geographic proximity, diversity and related diversity play a more significant role in pollution reduction in the central and western regions, while specialization and unrelated diversity are not conducive to pollution reduction in the eastern and central regions; Increasing agglomeration density and reducing diversity and unrelated diversity level are more beneficial to the small cities; Improving the geographic proximity, industrial diversity and related diversity levels are more helpful to the medium- and small-sized cites, but the reduction effect for the large cities goes obviously down because of the crowding effect. (5) To further reduce the intensity of industrial SO₂ emissions, it is necessary to take the road of agglomeration, persist on increasing agglomeration density, guide enterprises' centralized layout, improve the level of industrial diversity based on technology association, strengthen the joint prevention and control among neighboring regions, and focus on the industrial linkage and environmental protection cooperation between regions.

Methods for the evaluation of sustainable development capability are important and highly sought after tools for identifying the synergistic relationship between humans and the environment and guiding scientific decision-making for the implementation of ecological and environmental protection measures. Compared to traditional methods such as ecological footprint, environmental sustainability index, and human development index, emergy analysis and exergy analysis result in smaller errors and are more objective. These two methods can directly convert materials and services into energy units, without evaluation indicators and weight settings, and do not require raw dimensionless data. Exploring the coupling of emergy analysis and exergy analysis can provide a new perspective on and method for the analysis of regional sustainable development capabilities. Based on a literature review, a theoretical analysis framework was constructed. This study proposes an emergy and exergy coupling model for the analysis of sustainable development capability based on a thermodynamic theory. This analytical model has three indices, namely, self-organizing capability index (SO), ecological pressure index (EP), and sustainable development capability index (SC). The emergy and exergy input and output values of 17 typical developed countries in 1985 were screened via meta-analysis to calculate the SO and EP thresholds of the model, based on which sustainable development capability was divided into four stages. The model was tested via a comparative analysis of the sustainable development capability of China and the USA in 1985-2015. The results show that China was in the low self-organizing capacity and low ecological pressure stage before 2005. After 2005, it entered the low self-organizing capability and high ecological pressure stage. It has had low eco-efficiency and scale expansion driving characteristics. The USA is always in the high self-organizing capacity and high ecological pressure stage, and is characterized by high ecological efficiency, and economic and ecological decoupling. These results are consistent with the findings of the World Ecological Footprint Network and World Wildlife Fund, indicating that the proposed model is adaptive and reliable. In addition, the study results indicate that this model can express the ecological efficiency of an economic and social system in terms of "total annual exergy amount used/annual emergy input amount". Moreover, it can express the ecological pressure as "annual exergy loss of an economic and social system/annual eco-exergy produced by an ecosystem." This model connects the entropy path of an economic and social system to the ecosystem. Furthermore, it can identify sustainable development stage and analyze changes in sustainable development level and factors driving these changes. From an anthropological and ecological perspective, the model expresses the ecological efficiency of an economic and social system, evaluates the proportion of ecological space occupied, and can combine macroscopic scale with microscopic efficiency analysis, which is an improvement over conventional methods.

It is of great significance to enhance disaster prevention and response capacity to reveal the post-disaster economic development and recovery process, and to formulate the control policies and recovery methods for post-disaster economic reconstruction according to the economic resilience. Based on the long-term socio-economic data and ARIMA model, this paper calculated the economic resilience index of severely affected area of Wenchuan earthquake, and adopted the improved Variable Return to Scale (VRS) DEA model and Malmquist productivity index to analyze the efficiency and effect of annual post-disaster recovery. The results show that: (1) The economic resilience index of earthquake severely affected area is 0.877. The earthquake caused a short-term economic recession in the affected areas, but the economy returned to its pre-quake state within two years. In addition, the industrial economy is less resilient than agriculture and service industries. (2) The comprehensive economic recovery efficiency of the disaster-stricken area in the year after the disaster is 0.603. The comprehensive efficiency, pure technical efficiency and scale efficiency of the plain hilly area are significantly higher than those of the plateau mountain area. (3) The annual fluctuation of total factor productivity after the disaster was strong, and the economic recovery efficiency declined significantly, resulting in a short-term economic recession. The TFP index returned to steady state after a decline of 33.7% and 15.2% in the two years after the disaster. (4) The significant decline in the post-disaster recovery efficiency is mainly caused by technological changes, and the renewal of production system is the leading factor in determining the economic resilience after the disaster. With the decline in the scale of economic recovery, the long-term economic recovery in the study areas mainly depends on pure technical efficiency, and the improvement of pure technical efficiency is the driving force to maintain the long-term growth of post-disaster economy. Therefore, in view of the differences between the reconstruction of natural conditions and the stage of economic development, the disaster-stricken areas need to change and readjust their economic structures actively. Meanwhile, we should pay attention to updating production system to enhance the level of technological progress, and give full play to the scale effect of large-scale capital, facilities, manpower and other factors investment, so as to enhance the response to the disaster impact of economic resilience and recovery efficiency.

Interurban technology transfer becomes an essential channel for regions or cities to obtain external knowledge. Based on patent transaction data among cities during 2005-2015, this study investigates the interurban technology transfer network of Northeast China, aiming to explore spatial evolution of technology transfer network in this region from national to local perspectives based on social network analysis (SNA). A negative binomial regression analysis further reveals the factors of interurban technology transfer network. The results of the study are as follows: (1) From the national perspective, the interurban technology transfer network of Northeast China presents a core-periphery structure. The spatial pattern of "divergence in the northeast region" and "convergence in the coastal areas" has been formed. (2) From the local perspective, the technology transfer network of Northeast China shows a centripetal contraction situation, and its four hubs, namely, Harbin, Changchun, Shenyang and Dalian, play the role of technology gatekeeper. The interurban technology transfer flows present the characteristic of strengthening nationalization and weakening localization, which are more likely to emerge between the Northeast-Southeast China rather than among the Northeast China. (3) Both path-dependence and path-creation exist in the spatial dynamics of intercity technology flows in Northeast China. From the national perspective, technology flows from Northeast China to the Beijing-Tianjin-Hebei, Yangtze River Delta and Pearl River Delta urban agglomerations with Beijing, Shanghai and Shenzhen as the core respectively, while the local intercity technology transfer in Northeast China presents a mixed diffusing mode including hierarchical, contagious and jump diffusions. In addition, the local network mainly focuses on intra-provincial technology flows which centered on Haibin, Changchun, Shenyang and Dalian. (4) Some drivers, such as geographical proximity, the similarity of industrial structure, economic differences, the similarity of innovation capability, technology absorptive capacity, foreign direct investment, are evidenced to play a significant or determining role in interurban technology transfer of Northeast China.

The development of development geography stems from the study of underdeve-lopment and poverty. On the basis of combing the development process, basic theories, analytical models and methods of development geography, and combined with China's academic exploration of regional overall poverty alleviation and localization and poverty reduction of sustainable development, this paper constructs an analytical framework of development geography of poverty in underdeveloped areas, and establishes the "five-in-one" geographical capital index system composed of economic geographical capital, social geographic capital, cultural geographic capital, ecological geographic capital and political geographic capital. The integration method and technical flow of data processing are put forward to analyze the local differentiation of poverty in underdeveloped areas. The results show that: (1) Geographical detection determined the leading geographic capital that plays a role in poverty, and the determinative force of each leading geographic capital on the poverty incidence L_A,P ≥ 0.15; (2) Under the action of different dominant geographical capitals, the five single-dimensional geographic capital indexes and their synthetic regional geographic capital indices have obvious local differentiation, and have the characteristics of barrier and time delay; (3) The poor local differentiation can be divided into four types: economic geographical capital constraint, economic-social geographical capital constraint, economic-social-ecological geographical capital constraint, and economic-social-cultural-ecological geographical capital constraint; (4) Based on the characteristics of development, we tap the local dynamics and put forward the targeted countermeasures and models of different types to alleviate local poverty. Under the background of rural vitalization and the 2020 poverty alleviation shift, it is necessary to focus on the comprehensive research on spatial differentiation, spatial diffusion and spatial integration of poverty in less developed areas, so as to provide development geographical solutions for localization and poverty reduction of sustainable development.

Sponge city construction (SCC) is regarded as one of the effective ways to solve the urbanization problems in China, such as waterlogging, water pollution, water shortage and heat island. Since 2015, a total of 30 pilot cities had been set up as sponge cities for providing the models of a nationwide SCC in the future. Nevertheless, the studies about the SCC mainly concentrated on its concept, planning and goal in some pilot cities, few are known about the changes of the ecological effects under the SCC. As the first city in China to accept the sponge city concept and put it into practice, the Changde city, Hunan province, with the Chuanzi River catchment as the study area, provides the ideal area to evaluate the ecological effects under the SCC in China due to a longer SCC history over the period of 2004-2019. In this study, the ecological effects under the SCC in this catchment were analyzed based on field investigation and the comparsion of the measured data of hydrology, vegetation, and temperature before and after the SCC. The results showed that the SCC effectively alleviated the waterlogging in the Changde city, but some waterlogging sites still presented at the different areas in the catchment under the rainstorm. Meanwhile, the water quality in the Chuanzi River had been generally improved from bad Ⅴ to Ⅲ grade, but there was periodically deterioration due to the pollutants enrichment in the water during the winter seasons, which were the results from both closed water system and low temperature environment. In addition, the biodiversity in the catchment had significantly increased, but it also showed some existing problems at the same time including single plant species, few plants with environmental purification functions, incomplete ecosystem and poor management. Besides, the SCC had alleviated the heat islands in summer in the Changde city to some extents. As a result, the SCC over the period of 2004-2019 in the Changde city has significantly improved the ecological effects at the Chuanzi River catchment, which provides an important ecological basis for the socio-economic development and the improvement of the living environment in this area, and provides the reference for the reasonable evaluation on the SCC effects in other pilot cities in China.