The construction of ecological civilization is an important national strategy in China, and the Qinling Mountains play a strategic position in the construction of ecological civilization in China. To clearly understand the existing problems and paths of ecological civilization construction in the Qinling-Daba Mountains, nine well-known researchers from different fields were invited in an interview on cutting-edge research topics in the Qinling Mountains. The interview covered such topics as ecological patterns and geographic processes, scientific investigations, rural revitalization, and water resources protection. The results of the interview show that: to gain a better understanding of the important value of the study area and to carry out the ecological protection and sustainable development in the New Era, it is necessary to understand the ecological and environmental effects of the North-South Transitional Zone of China, reveal the ecosystem service functions, emphasize the pivotal role in maintaining national ecological security, and conduct research on ecological protection and restoration of the Qinling Mountains. It is significant to continuously monitor the ecological functions, build an intelligent monitoring system integrating "Space-Air-Ground", continue to carry out comprehensive scientific investigations, pay attention to major scientific propositions, discover the unique geographical phenomena and laws of the Qinling Mountains, and form a scientific data sharing mechanism and platform to support regional scientific research and decision support. Under the new mobility paradigm, we should look at the resettlement project from a dynamic perspective, focus on the livelihoods of different groups and types of immigrants, and solve immigration problems through a diversified security system. In the context of climate change, it is necessary to attach importance to the response of the Qinling Mountains to climate change and human activities, strengthen the construction of regional transportation infrastructure, find out the law of evolution and changing trend of Qinling Mountains' water resources, and to carry out systematic management to ensure long-term and safe supply of water resources, and promote sustainable social and economic development.
This paper summarizes the research process of rural tourism in China through systematic literature review, which contains three stages: primary application research (1992-2005), diversified expansion research (2006-2015), and integration deepening research (2016-), as well as analyzes the background and research value orientation of each stage. Based on the analysis of knowledge map by CiteSpace, it reveals the changing process and characteristics of research topics. Combining the rural revitalization strategy and tourism development needs in the New Era, the research expounds the basic characteristics of rural tourism, constructs the research framework of rural tourism in the New Era, puts forward the main scientific issues, and proposes the research trends and academic innovations of rural tourism research. Moreover, the research emphasizes that rurality and recreation constitute the fundamental characteristics of rural tourism. Future research should focus on the national strategy and high-quality development requirements of the New Era, as well as keeping up with the international academic frontiers. Meanwhile, based on the local practice of rural tourism research in China, relevant research should concentrate on the "five-sphere integrated plan" basic framework for rural tourism, taking industry, ecology, culture, governance, and livelihood as the core elements. Under this research framework, it is essential to focus on the rural area system with its complexity and key tourism scientific issues, to strengthen research platforms and professional talents, to integrate multidisciplinary theories and technology methods, as well as to reinforce the ideas of data-driven and science-technology energization. It is also necessary to reveal the process, patten, mechanism, and rule of rural revitalization pushed by rural tourism in a deep-going way, to explore the development model and path of rural tourism revitalization with distinct Chinese characteristics, to continuously promote the deepening of theoretical research, practical application innovation and the development of rural tourism discipline, besides, to improve the academic research, innovation ability, service value, and internalization level of rural tourism.
The scientific evaluation of urban-rural integration is the core content of urban-rural integration, and it is the foundation for establishing and improving the institutional mechanism of urban-rural integration. Based on the logical line of "connotation identification-theoretical analysis-system reconstruction", this paper carries out the review of urban-rural integration evaluation including concept connotation, theoretical basis, evaluation index, evaluation method, evaluation scale, spatio-temporal differentiation, and mechanism analysis. At present, the academic understanding of the connotation of urban-rural integration is basically the same. The evaluation index selection of urban-rural integration shows multidimensional and multi-attribute characteristics, but the index system construction has not broken through the static characteristics. Quantitative evaluation method is relatively simple. Generally, current research still remains at the macro scale, but lacks quantitative research from a micro perspective and comparative studies of different fusion modes. The spatial and temporal differentiation pattern and its mechanism of urban-rural integration need to be further deepened. Finally, this paper puts forward five prospects: (1) strengthening the construction of basic theory system and perfecting system research framework; (2) optimizing the multidimensional evaluation index system and identifying the development model of urban-rural integration; (3) deepening the flow mechanism of urban and rural elements and promoting the balanced development of urban and rural space; (4) strengthening the exploration of micro-scale details and improving the promoting mechanism of urban-rural integration; (5) strengthening the empowering role of the digital economy and innovating the development mechanism of high-quality urban-rural integration.
The Qinghai-Tibet Plateau is sensitive to climate change. At present, relevant researches mostly focus on the dynamic changes of ice and snow in the Qinghai-Tibet Plateau, and seldom pay attention to the dynamic changes of the rocky desert left by the melting ice and snow. Through the earth-atmosphere interaction, rocky desert may change the regional heterogeneity of climate at a large scale. This paper sorted out the extraction methods of remote sensing monitoring of ice and snow melting and rocky desert dynamic changes in the Qinghai-Tibet Plateau, and analyzed the advantages, disadvantages and applicability of various remote sensing data and extraction methods. We also summarized the data and research methods of the dynamic monitoring of ice and snow and the dynamic changes of the rocky desert in the Qinghai-Tibet Plateau. At present, the remote sensing monitoring data of the snow and ice dynamic changes in the Qinghai-Tibet Plateau are diverse and the research methods are mature. However, the remote sensing monitoring of the rocky desert dynamic changes left by the melting ice and snow has not yet formed a systematic study. Besides, under the condition of insignificant human disturbance, the dynamic changes of the rocky desert in the ice and snow melting area can also be used as a supplement to remote sensing monitoring of ice and snow dynamic changes.
With the rapid growth of remote sensing data, greater challenges arise in raster data efficient processing and value mining. Traditional map services focus on content sharing and visualization, but lacking real-time image analysis and processing functions. In this study, the real-time analysis and processing capabilities of raster tile data are realized in the form of map service. The cloud optimized GeoTIFF (Cloud Optimized GeoTIFF, COG) is used as the data organization method. The distributed collaborative prefetching strategy is designed to realize the raster tile loading in a cold or hot way, which optimizes the efficiency of reading image data from the cloud. Based on the efficient raster tile data loading, an expression-based raster tile processing model is proposed. By converting the expression into a calculation workflow, the raster tile is processed in the request of the map service in real time. The massive remote sensing data stored in the cloud is quickly analyzed to realize the direct visual conversion from raw data to products. For scenarios where full data are involved, use appropriate resampling data to simplify calculations to meet the real-time performance of map services. Three types of different complexity models, NDVI, ground object classification, and fractional vegetation cover, are used to perform real-time calculation and analysis on Landsat 8 images in the map service. Experimental results show that the processing model can effectively analyze raster tiles, and can be extended in a distributed manner. It can provide stable map service capabilities in high-concurrency scenarios, adapt to calculations at various levels and scales, and contribute a new idea to the future development of map service.
This paper explored the characteristics of intercity human mobility and the 'negative effects' of massive intercity population movement in China by using mobile internet positioning big data. Two travel periods of Baidu Migration data were selected involving Spring Festival and usual travel time. Based on two mobility indicators, i.e., movement scale and movement scope, the spatial characteristics of intercity population movement were measured by local spatial autocorrelation. With a vital public health emergency, linear regression models were used to measure the differences in the negative effects of the national intercity population movement on different cities and urban agglomerations in China. It is found that three major urban agglomerations, namely, the Yangtze River Delta, the Pearl River Delta, and Beijing-Tianjin-Hebei, are the most significant high-value clustering area of mobility in China. Urban agglomerations and megacities are accompanied by higher risks of negative effects for their super mobility. First, the megacity-centered urban agglomeration will have a more significant negative consequence when it is affected by the negative effects of intercity mobility. Second, the megacity-centered urban agglomeration will significantly spread the negative effects through intercity mobility. It is proposed that the security of urban agglomeration should firstly guarantee the security of mobility. The security of urban agglomerations should be reflected in the resilience of intercity mobility networks. In the process of new urbanization, the development strategy of urban agglomerations needs to focus on the mobility and security of urban agglomerations from the perspective of territory spatial security.
Propagation simulation is an important way to recognize the resilience of network structure from a dynamic perspective. Exploring the relationship between the difference in network structure and the state of network propagation is of great significance to the improvement of network structure resilience and the optimization of territory development space. This paper constructs four typical urban network models: nearest neighbor network, small world network, scale-free network and random network. Using complex network theory and SIS virus propagation model, MATLAB and Gephi are used to simulate infectious diseases, and the four types of networks are analyzed. The variation characteristics of infection quantity and infection time under the difference of network shape, node scale and degree value, and the influence mechanism are discussed. The results showed that: (1) From the perspective of overall characteristics, the difference in network structure affects the strength of network propagation. The heterogeneity value distribution, highly local clustering, and short path length of irregular network will expand the scale of infection and shorten the time of infection. (2) From the perspective of decomposition characteristics, scale is not the core factor affecting network communication. High degree of urban network with power law distribution is the risk of regional and urban suppression of negative transmission. (3) From the perspective of spatio-temporal characteristics, heterogeneous network and regular network have the dual characteristics of robustness and fragility. The advantages of heterogeneous network in peacetime and the advantages of regular network in epidemic time should be fully developed through network switching. Based on this, the resilience optimization strategy of land development space network structure is proposed from the regional and urban levels.
Unmanned aerial vehicle (UAV) is in an important period of rapid technological breakthrough and application growth, which will vigorously promote the low-altitude economy development. The low-altitude Internet of Intelligences (IoI) is the cornerstone of the UAV industry development and an important infrastructure to realize the "human-UVA-physical objects" fusion and AIoT (All in Internet of Thing) in low-altitude airspace. The construction of low-altitude IoI aims to realize the transition from the traditional Internet to the AIoT by the space-air-ground-sea network infrastructure, and to form a physical cyberspace for the digital and intelligent operation of low-altitude services. It can provide a digital, intelligent, and networked environment for the UAV industry, which is of great significance for promoting the development of low-altitude economy.
During the development of COVID-19 virus's global epidemic, the fundamental research and various applications of crowd dynamics-oriented observation theories have attracted much attention from many researchers and people all over the world within some related disciplines, such as public health, clinical medicine, geography, public management, etc. Researchers conducted many interdisciplinary explorations in theories and methods of monitoring epidemic dynamics scientifically, preventing and controlling spatial transmission precisely, predicting accurately, and responding effectively. However, no crowd dynamics-oriented observation theories have been proposed in literature so far. This paper revisits the concept and introduces a theory framework of crowd dynamics-oriented observation, which tries to include the core theories of observation from geospatial big data and to support diverse potential developments. Firstly, this article introduces the research background of crowd dynamics-oriented observation, and then summarizes its three core questions (how to observe its change, how to analyze its change, and how to control its change). From the inter-discipline view of geographic information science, surveying and mapping science, this paper explains the research significance and disciplinary value of crowd dynamics-oriented observation theories. Secondly, this paper introduces a framework of crowd dynamics-oriented observation and its spatiotemporal application, and then elaborates on the bottleneck problems of the key observation theories of crowd dynamics, such as fundamental space-time framework theory, space-time quantification and comprehensive observation theory, spatiotemporal process optimization theory, etc. Thirdly, this paper preliminarily introduces some changes of crowd dynamics-oriented observation theories, for example, refined observation driven by the application needs of digital society governance and public safety/health emergency, personal privacy protection and personalized observations by balancing the public interest and personal privacies, the development of integrated observation theories for human-oriented observation and earth-oriented observation, and the theory of crowd dynamics-oriented observation for high-level management and service. Finally, this article points out the potential directions of crowd dynamics-oriented observation theory and methods, such as, the development of big data-driven crowd perception, multi-space refined crowd dynamics observation, and human-land systematical interaction modeling, so as to realize some differentiated, integrated, and hierarchical crowd dynamics-oriented observations. All potential theories are helpful to the scientific decision-making of public management and public service. The crowd dynamics-oriented observation theory should focus on the fundamental research questions related to studying, analyzing, and servicing human beings, which has become a research frontier in geospatial information science, and could play very important roles in supporting national development strategies, such as "New urbanization", "beautiful China", "artificial intelligence", and "new infrastructure", so as to contribute to a green, efficient, smart, and sustainable regional and urban development.
In order to avoid crowd trampling, it is very important to accurately obtain information on the number of crowds from surveillance images. Early crowd counting studies used a feature engineering approach, in which human-designed feature extraction algorithms were used to obtain features that represented the number of people to be counted. However, the counting accuracy of such methods is not sufficient to meet the practical requirements when facing heavily occluded counting scenes with large changes in scene scale. In recent years, with the development of neural network, breakthroughs have been made in image classifications, object detections, and other fields. Neural network methods have also advanced the accuracy and robustness of dense crowd counting. In view of the difficulty of counting dense crowds, small crowd targets, and large changes in scene scale, this paper proposes a new neural network structure named: VGG-ResNeXt. The features extracted by VGG-16 are used as general-purpose visual description features. ResNet has more hidden layers, more activation functions and has more powerful feature extraction capabilities to extract more features from crowd images. Improved residual structure ResNeXt expands on the base of ResNet to further enhance feature extraction capabilities while maintaining the same computing power requirements and number of parameters. Therefore, in this paper, the first 10 layers of VGG-16 are used as the coarse-grained feature extractor, and the improved residual neural network ResNeXt is used as the fine-grained feature extractor. With the improved residual neural network feature of "multi-channel, co-activation", the single-column crowd counting neural network obtains the advantages of the multicolumn crowd counting network (i.e., extracting more features from dense crowd images with small targets and multiple scales), while avoiding the disadvantages of the multicolumn crowd counting network, such as the difficulty of training and structural redundancy. The experimental results show that our model achieves the highest accuracy in the UCF-CC-50 dataset with a very large number of people per image, the ShangHaiTech PartB dataset with a sparse crowd, and the UCF-QNRF dataset with the largest number of images currently included. Our model outperforms other models in the same period by 7.5%, 18.8%, and 2.4%, respectively, in MAE in the above three datasets, demonstrating the effectiveness of the model in improving counting accuracy in dense crowds. The results of this research can effectively help city management, relieve the pressure on public security, and protect people's lives and property.
Good Health and Human Well-being is one of The Sustainable Development Goals proposed by the United Nations, and increasing the life expectancy is a significant step towards this goal. Due to differences in the natural environment and social development of Chinese cities, understanding the factors that affect life expectancy in different regions is the key to formulate urban public health policy. Based on the data of 286 cities in China in 2015, this paper used exploratory regression, ordinary least squares, and geographically weighted regression to screen out the most relevant influencing factors to life expectancy and explore their spatial differences. Then, the two-step cluster analysis was used to make targeted policy recommendations for each type of cities. The results show that: (1) Economic development, educational conditions, and medical facilities had a significant positive impact on life expectancy, while average altitude and environmental pollution had a negative impact; (2) Compared with other regions, economic development in the southeast region had a greater impact on local life expectancy; medical facilities in the northeast and southwest regions had a higher degree of promotion of life expectancy for its residents; education conditions in the northern region had a higher impact on the life expectancy of local residents; average altitude had the greatest impact on the life expectancy of residents in the West region; The life expectancy of residents in the northwest region was more susceptible to the negative impact of environmental pollution than in other regions; (3) Cities were divided into three categories based on spatial differences, and the key factors affecting the life expectancy are economic development and environmental pollution, educational conditions, and medical facilities in order. City managers in each category of cities should pay attention to different factors to increase their life expectancy.
With the increase of indoor space application and the development of indoor positioning technology, the integration and application of indoor location information has become one of the hot spots in indoor GIS research. Emergency rescue and navigation for indoor space, such as large venues, has become a research hotspot of indoor GIS application. The construction of indoor network is the key technology to realize the indoor emergency navigation service. In this paper, aiming at the problem of indoor navigation routing, we proposed and constructed Indoor Cognitive Hierarchical Coding Method (ICHCM) based on indoor space perception and hierarchical cognition. The main contents are as follows: (1) Based on the law of indoor space perception and the way of hierarchical cognition, the indoor road network was simplified into four levels: street-building level, building-floor level, floor-block level, and block-room level. Thus a tree network of multi-level expression was formed; (2) In order to meet the needs of semantic analysis and path finding, the "virtual room" unit was introduced to divide the indoor closed unit and associated unit into room unit based on the analysis of the indoor unit function. The partition strategy of horizontal and vertical connection space was also provided; (3) Based on the cognitive hierarchical model of interior architecture and the results of indoor unit division, the indoor units were coded successively from high level to low level. This indoor unit encoding method is of great significance to semantic relations, spatial queries, topological relations, and path finding in indoor space. In order to verify the feasibility and effectiveness of the proposed road network construction and coding method, a commercial center was selected as study area, four levels of indoor road network were constructed. The number of nodes and arcs of every level of the network was reduced by layered and partitioned processing while the ICHCM network was effectively simplified and the efficiency of calculation was improved. The time used in path-finding was less than those of traditional network models. The same floor routing time was -55 millisecond while the cross floor routing time was -100 millisecond. The results showed that ICHCM model fits the way of the cognition of science for people. ICHCM can describe the characteristics of the network of different levels, enable the integrated path-finding of indoor space, and meet the demand of the precision and efficiency of path-finding. Results from this study provide important basis for indoor navigation.
The modern international and domestic science advancements have brought forward new opportunities as well as higher requirements to the development of geographic science in China. In planning the disciplinary structure of geographic science in the "Development Strategy of Discipline and Frontier Research in China (2021-2035)", we propose a modified disciplinary structure for the geographic science in the new era. The geographic science in China can be categorized into four secondary disciplines, i.e., integrated geography, physical geography, human geography, and information geography, considering the current situation and development outlook of geographic science. The tertiary disciplines under each secondary discipline are nearly fully developed, and a few quaternary disciplines under tertiary disciplines have already been widely accepted and used. We hope this new disciplinary structure can play a breakthrough role for improving the branches of geographic science, promoting the development of emerging disciplines under the framework of geographic science, and better serving the international and domestic development needs in the new era.
Resident food consumption is affected by factors such as the natural geographic environment and urbanization. At the same time, food consumption will affect regional food security and the development of agriculture and animal husbandry through market mechanisms. Taking the Yarlung Zangbo River and its two tributaries of Tibet (also known as Three-Rivers Region) as a typical case, this paper obtained the food consumption data of 262 rural residents by field surveys based on stratified sampling, and then analyzed the food consumption structure of the rural residents and its influencing factors in the Tibetan Plateau. The results indicated that: (1) The consumption of plant foods of the residents in the sample is 3.19 times that of animal foods, with vegetable and grain as the main plant food and meat and milk as the main animal food. And highland barley and highland barley liquor are important in the diet of Tibetans. (2) The scale and structure of food consumption of residents are closely related to the index of food self-sufficiency, and the characteristics of self-sufficient food consumption are significant. (3) Among different regions, family sizes, scales of migrant worker, income levels and family ages, the food consumption structure of residents varies, and the differences in the consumption of flour and fruits between different families are the most significant. (4) Regional differences, family sizes and migrant worker scales are the main factors that affect the comprehensive difference of food consumption in the sample rural areas. The research results of the paper can provide scientific basis and guidance suggestions for the improvement of food consumption structure, promotion of dietary nutrition and transformation and development of agriculture and animal husbandry in the Tibetan Plateau.
Understanding the relationships between ecosystem services supplies and demands is of vital importance for sustainably utilizing natural capital and coordinating ecosystem services supplies and demands. According to the previous research on ecosystem services at home and abroad, the research framework of the relationships among ecosystem services supplies and demands was put forward in this study. Within this framework, the formation mechanisms and representations of the relationships between ecosystem services supplies and demands were explained, the basic characteristics of the relationships between ecosystem services supplies and demands were summarized, and the potential research focuses were proposed, which could provide a guidance for the studies on the ecosystem services and the governance of ecosystem services. In general, there were two non-exclusive mechanisms that formed the relationships between ecosystem services supplies and demands. On the basis of these formation mechanisms, the representations of the relationships between ecosystem services supplies and demands included bundles, trade-offs, synergies and no-effect relationships. In terms of the characteristics, the relationships between ecosystem services supplies and demands could be spatially heterogeneous, temporally variable and scale dependent. The construction and evaluation of indexes, statistical analysis of indicators, development and simulation of scenarios, and spatial mappings and analysis were the four main methods to study the relationships between ecosystem services supplies and demands.
Food consumption is the primary way to get access to the basically-needed energy and nutrition for human being. Our investigation was conducted in Zhengzhou city, one of the provincial cities in central China, by a 3-consecutive-day household weighting survey. We gained a first-hand dataset consisting of 309 urban households in Zhengzhou and their food consumption data. Our research reveals that: (1) Urban households in the study city held a 372.32 g of food consumption for each meal per capita, which was dominated by plant-based foods (277.12 g). The ratio between plant-based foods and animal foods was 3∶1. (2) Among the three urban districts, Huiji consumed more sea food and fruits compared with Erqi and Jinshui. The per capita consumption of staple foods and vegetables for households in the city tended to decrease as annual per capita income rose, while that of fruits, seafood and dairy increased. Households with a smaller population consumed more food per capita compared with those with a larger population. (3) Furthermore, the comparison of research results and the general dietary guidelines indicated that the dietary pattern of urban households in Zhengzhou need to be further adjusted. Briefly, their meats consumption far exceeded the recommended upper threshold, while the consumption of dairy products and fruits did not reach the recommended anount. In the following application of "Health China" and other relevant national strategies, we should continue to highlight the urban household food consumption, promote and diversify the content and form of nutrition & health education in communities and families. The excessive meat consumption needs to be reduced in a reasonable range, and the high-nutrition foods should be expanded and encouraged.
With the increasing economic interaction between cities, capital flow across regions has gradually become a key factor affecting the regional economic disparities. Cross-regional enterprise investment is regarded as the micro embodiment of capital flows. It is of great significance to explore the characteristics of cross-regional enterprise investment for reducing regional economic disparities. Thus, this study examined the cross-regional investment network using the cross-regional investment data of Chinese listed companies in 1998-2018, and analyzed the characteristics of the spatial evolution of China's cross-regional investment network and its influencing factors at the national and regional levels. The results show that: the spatial agglomeration trend of node centrality in China's cross-regional investment network at the national and regional levels is obvious and the cities with high node centrality are mainly concentrated in the five major urban agglomerations. There are obvious hierarchical structure, spatial heterogeneity, and path dependence of the cross-regional investment network; the net investment inflows and outflows are mainly in the eastern region, and the investment activities tend to develop toward the central and western regions; the influence of city economic development level, industrial structure, and financial environment varies across regions and types of cities with different population scales.
Through various exploration and practice of poverty alleviation, China has embarked on a path of poverty alleviation with Chinese characteristics, which has greatly reduced the number of rural poor people and significantly improved the living standard in poverty-stricken areas. For a long time, the monitoring of socioeconomic and environmental conditions in poverty-stricken areas is based on all kinds of statistical data, reports, paper files, etc., based on administrative units, lacking effective and accurate spatial location information. With the rapid development of geo-information science such as Remote Sensing (RS) and Geographic Information System (GIS), the real-time and efficient capture and calculation ability of spatial information greatly improves the efficiency and decision support level of poverty alleviation. This paper expounds the contributions of geo-information science on China's poverty alleviation from the following aspects:① monitoring and evaluation of natural resources and environment in poverty-stricken areas based on multi-source geospatial data; ② monitoring, early warning, and management of natural disasters in poverty-stricken areas; ③ analysis of poverty causing factors and poverty prediction; ④ decision support system for targeted poverty alleviation based on the mechanism of targeted poverty alleviation. China aims to eradicate absolute poverty in 2020, so the application of geo-information science in poverty alleviation will mainly focus on the establishment of monitoring and assistance mechanism to prevent poverty returning and alleviate the relative poverty. Moreover, under the background of rural revitalization, using geo-information science and technology to promote rural infrastructure information construction will be the focus of the next step.
The application of natural resources big data and its processing technology can provide basic support for the research and management of natural resources, especially for revealing the elements, structure, and correlation of natural resources system, and provide new ideas, new methods, and new technologies for the development of resources science. This paper attempts to clarify the concept, main characteristics, and development trend of natural resources big data, and analyzes the practical significance of natural resources big data for national economic and social development. The construction of natural resources big data is not only an important part of natural resources informatization, but also a new way to improve the efficiency of natural resources industry and the whole social economy, and the governance structure of natural resources and the modernization of natural resources governance capacity. In this paper, the knowledge framework of natural resources big data application research is constructed under the earth system science system, based on the structure of "one map, one network, and one platform", this paper proposes to establish a large database of natural resources integrating space, aviation and ground observations and an application framework in terms of production, residential and ecological spaces, and discusses the establishment of a structural system based on data collection, processing, and application of natural resources. The frontier progress and development trend of natural resources big data application research are also analyzed under this technical framework.
Global climate change is not only the most important environmental problem, but also one of the most complex challenges mankind faces in the 21st century. In the context of the increasing challenges of climate change and global governance, the assessment of CO2 emissions and costs has attracted increasing attention from academia and policy makers. At present, almost all global studies, including the assessment by the Intergovernmental Panel on Climate Change (IPCC), use global average CO2 concentration to drive the climate models. However, there are many controversies on the impact assessment based on the global average distribution of CO2 in academia. To formulate countermeasures to deal with carbon emissions and reduction and enhance China’s international discourse on dealing with climate change, it is of great importance to explore the mutual feedback mechanism between the inhomogeneity of atmospheric CO2 concentration and geophysical processes (e.g. surface temperature rise), and explore the impact mechanism of the inhomogeneous distribution of atmospheric CO2 concentration on global climate change. This paper reviews the research progress of non-uniform distribution of atmospheric CO2 concentration and its effects on surface warming. Firstly, this paper reviews the evidence of non-uniform distribution of atmospheric CO2 concentration from three aspects, ground-based measurement, numerical simulation, and remote sensing. It summarizes the advantages of these three methods and analyzes the discovery process of non-uniform distribution of global atmospheric CO2 concentration. Secondly, this paper explores the mutual feedback between the non-uniform distribution of global atmospheric CO2 concentration and surface temperature rise. The non-uniform distribution of atmospheric CO2 concentration directly affects the radiative forcing or indirectly affects the regional warming through affecting the photosynthesis. Regional warming has a direct or indirect impact on the ability of the ocean and vegetation to absorb CO2, which ultimately affects the non-uniform distribution of global atmospheric CO2 concentration. Finally, this paper reviews the problems of existing studies on non-uniform distribution of atmospheric CO2 and discusses the prospect of future development trends. This study provides a scientific basis for understanding the current situation of global/regional carbon emissions and climate change impacts, and further explores the feedback mechanism among atmospheric CO2 non-uniform distribution, surface temperature rise, and socio-economic system.
It is very important to summarize the research, understand the development process and direction of industrial geography in China scientifically under the context of the development of international industrial geography. Based on 154 papers on industrial geography published in Acta Geographica Sinica from 1934-2019, this paper reviewed the development process of industrial geography in China and the progress of research in major fields. This paper showed that China's industrial geography is a unique theoretical system based on the integration of Western industrial geography theory and Soviet-style industrial geography theory, under the tasks of theory development and practices. Going through exploration, growth, perspective changing and deepening, industrial geography is gradually brought into line with the international researches on the content and paradigm. The development of discipline needs to meet the national strategic demand, raise theoretical innovation capacity, strengthen the application of new methods and techniques, and develop theories of industrial geography with the Chinese institutional context.
It is disputable that global large-scale urbanization and climate change has become an outstanding issue, which requires the common concern of mankind. However, it is not yet clear what is the complex relationship between urbanization and climate change and how to scientifically deal with climate change in the process of urbanization. Further exploration from science and management to practice are needed in order to achieve global and regional sustainable development. This paper first displayed the basic facts of mass urbanization and climate change and summarized interactions and possible mechanisms of urbanization and climate change. Urbanization leads to heat island effect, uneven precipitation distribution and extreme weather, together with local-regional-global multi-scale superposition effect, which aggravates global climate change. The impact of climate change on urbanization is mainly manifested in the aspects such as changes of energy consumption, mortality and the spread of infectious diseases, sea level rise, extreme weather damage to infrastructure and water shortage. This paper also briefly reviewed relevant international research and joint actions, and put forward an analysis framework of multidimensional sustainable urbanization adapting to and mitigating climate change, from the perspective of key dimensions of urbanization, namely, population, land use, economy and society. We call on to strengthen the interdisciplinary research of science and humanities, take urbanization and other human activities into consideration of the land - atmosphere system, and explore the human-land-atmosphere coupling process. The adaptation and mitigation from the perspective of human activities represented by urbanization might be the most critical and realistic way to deal with climate change.
Improving urban residents’ quality of life is an important goal and concrete embodiment of achieving high-quality development in the Yellow River Basin.This article constructs an evaluation index system of urban residents of quality of life from 4 aspects (residents’ life, infrastructure, public service and ecological environment), and measures the level of urban residents’ quality of life in the Yellow River Basin in 2004-2018. The kernel density estimation, ESDA and Dagum Gini coefficient are used to analyze the spatial and temporal pattern of residents’quality of life and measured the spatial difference. The obstacle factor diagnosis model is used to analyse the obstacle factors of residents’ quality of life. The conclusions are as follows: 1) From 2004 to 2018, the areas with high quality of life of urban residents in the Yellow River basin gradually transferred from the lower reaches to the middle and upper reaches; 2) The H-H agglomeration areas of urban residents’quality of life in the Yellow River Basin are mainly in Inner Mongolia Autonomous Region, and the L-L agglomeration areas are mainly in Henan Province, Shandong Province and Shanxi Province; 3) The spatial difference of the quality of life of urban residents in the Yellow River Basin is mainly the contribution of the net value difference between regions from the upper, middle and lower scales, and the contribution of the regional difference from the left and right bank scales; 4) The obstacles to urban residents’ quality of life in the Yellow River Basin are mainly the amount of water resources per capita, the number of mobile phone users at the end of the year, the area of parks and green space per 10 000 persons, the proportion of education expenditure in fiscal expenditure, the road area per 10 000 persons, and the per capita disposable income, etc. Therefore, we must pay attention to the ecological environment protection, especially the rational utilization of water resources, improvement of urban infrastructure and public service levels in the future high-quality development.
Innovation is one of the important ways to promote the high-quality development of the Yellow River Basin. Using the panel data of 79 cities above prefecture level in the Yellow River Basin from 2006 to 2018, this article first constructs an index system to analyze the level of technological innovation and green development of each city, and then deeply explores the mechanism of technological innovation on regional green development through panel econometric model. The results are as follows: 1) From 2006 to 2018, the level of urban technological innovation and green development in the Yellow River Basin has been greatly improved, but the spatial difference is significant, and the overall trend is “downstream > midstream > upstream”. 2) On the whole, technological innovation has no influence on urban green development in the Yellow River Basin, but after adding the quadratic term of technological innovation, there is a obvious positive “U-shaped” nonlinear relationship between them, which also shows the existence of “rebound effect”. 3) The impact of technological innovation on urban green development in the Yellow River basin can be reflected by both direct and indirect effects, but the two effects are just the opposite. That is to say, the promotion of a city’s technological innovation level has a significant “U-shaped” relationship with the urban green development, but it has an inverted “U-shaped” relationship with its neighboring cities. According to the research conclusions, this article puts forward the corresponding policy implications from the direct and indirect effects of urban technological innovation on green development. First of all, it is particularly important for the middle and upper reaches of the Yellow River basin to enhance the ability of technological innovation and strengthen the innovation-driven effect on urban green development; Then, cities in the Yellow River Basin should break the “beggar thy neighbor” phenomenon, so as to strengthen the coordinated development in the Yellow River Basin and give play to the positive spillover effect among cities.
Carbon emission control is the main problem and measure of ecological protection and high-quality development in the Yellow River Basin. Carbon emission at county level research can provide more accurate theoretical support for collaborative governance and sustainable development of the Yellow River Basin. Spatial panel model, spatial autocorrelation analysis and spatial Markov chain with regional background and nearest neighbor as spatial lags were used to analyze the spatiotemporal pattern and spatial effect of carbon emissions in counties of the Yellow River Basin from 2000 to 2017, the results showed that: 1) the carbon emission in the Yellow River basin has increased dramatically since 2000; the high carbon emissions areas, Shandong province and the boundary between Shaanxi, Gansu, Ningxia and Inner Mongolia, expands to the outer circle layer and the axial direction, forming the spatial pattern of high in the east and low in the west; 2) there is a phenomenon of “club convergence”; the high carbon emission counties converge in Shandong province and the boundary between Shaanxi, Gansu, Ningxia and Inner Mongolia; the low carbon emission counties converge in the southwest; the comparison between 2000 and 2017 shows that county carbon emission type has strong stability; counties which tranfered from higher carbon emission type to lower carbon emission type are concentrated in the southeast region, while counties that change in the opposite direction are concentrated in Inner Mongolia. 3) high carbon spillover effect and low carbon locking effect are important forces to shape the spatiotemporal pattern and the former is stronger; the regional background enhances “club convergence” and the convergence of surrounded outliers and its acting force was stronger than the nearest neighbor; the probability of carbon emission type transition in insignificant regions increased; 4) the spatial panel model shows that increase of carbon emissions and its spatial effect are promoted by young population structure, large economy, industrial structure dominated by the secondary industry, high living standard and high public expenditure; economy and industrial structure are important driving factors.
With the accelerating process of urbanization and industrialization in China, the coexistence of excessive non-agricultural farmland and low efficiency of urban land use is becoming increasingly serious. So taking the Yellow River Basin as the research object, it is of great theoretical and practical significance to analyze the spatial pattern of urban land economic density in the Yellow River Basin from the provincial, municipal and county level. Taking 8 provinces and regions (Gansu, Qinghai, Shaanxi, Shanxi, Henan, Inner Mongolia, Ningxia and Shandong) in the Yellow River Basin as the research objects, based on the multi-temporal and high-resolution global urban boundary interpretation data in 2018, the urban land economic density of the Yellow River Basin was calculated from the provincial, municipal and county-level scales. The spatial pattern of urban land economic density in the Yellow River Basin was discussed by using the methods of Theil index, global and local spatial autocorrelation analysis. With the help of geographical detector, the influencing factors of urban land economic density were analyzed. The results show that: 1) The economic density of urban land in the Yellow River Basin is generally not high. At the county scale, 68.3% of the counties are lower than the average level; At the municipal level, 57.5% of cities are below the average. 2) There is a significant spatial positive correlation of urban land economic density in the Yellow River Basin. The high value agglomeration areas (HH) are concentrated in the Central Plains urban agglomeration and Shandong Peninsula urban agglomeration, the low value agglomeration areas (LL) are concentrated in the western China such as Shaanxi, Gansu and Ningxia. And the low-quality heterogeneous area is inlaid around the Central Plains urban agglomeration and Shandong Peninsula urban agglomeration. 3) In the whole Yellow River Basin, per capita GDP, population size, local financial investment in science, technology and education, labor density of secondary and tertiary industries and location quality index have a great impact on the economic density of urban land. There are some differences in the upper, middle and lower reaches of the Yellow River Basin. Generally speaking, capital investment intensity, per capita GDP and location quality index have high explanatory powers for the economic density of urban land in the upper, middle and lower reaches.
As a typical cultural phenomenon throughout the progress and development of modern and contemporary Chinese society, the writing, construction, inheritance and other topics of red memory at the macro level have been widely concerned and discussed. However, the research on red memory on the individual level is relatively deficient and requires to be promoted. Therefore, this paper takes Yan'an urban core area, which is rich in red resources, as a case study. With the help of generation research method, through in-depth interviews with 36 local residents, this paper interprets the red memory differences among three generations of Yan'an urban residents, and explores the "macro-micro" construction path and results of red memory. The results show that the macro level of memory elements mining, narrative expression and resource activation construct the coding, selection and consolidation process of residents' red memory, promote the local residents to generate red memory content with characteristics of the times, and finally construct the authoritative, functional and reflective red memory system of the old, middle and young generations. The results reflect the significance of the social forces of memory construction and the changing times in shaping the content of individual memory, and provide a theoretical reference for standardizing the practice of red memory and promoting the inheritance of red memory.
Taking Jinggang Mountain Scenic Area as a case, this study collected and analyzed the travel notes of this scenic area from Mafengwo.com. We adopt big data analysis and qualitative text analysis methods and introduce the theory of value co-creation to explore the value co-creation mechanism of red tourism development from three dimensions (resources, practices and values). The results show that the value co-creation resources of red tourism scenic spots include historical and cultural heritages, natural landscape resources and iconic landscape symbols. Through practical activities including red culture experience, learning and training activities, and interpretation service experience, tourists gain knowledge of red history and culture, build an emotional connection with red culture and form the values of patriotism and identification with the country. This verifies the realization of the educational function of red tourism. On the other hand, the existing value co-creation practice of red tourist attractions is still limited. The value co-creation mechanism of red tourism development constructed in this study integrates the demand of tourists, the support service of scenic spots, and the possible value co-creation practice, which has practical significance for improving the participation of tourists and realizing the value co-creation of red tourist attractions.
The Chinese government has curbed the outbreak of COVID-19 through a population flow control rarely seen in history. The COVID-19 pandemic has greatly impacted the recreation industry. Using mobile location data, this study quantitatively analyzed the impact of the COVID-19 pandemic on population heat map in the leisure areas within the Third Ring Road of Beijing City on the Qingming Festival and Labor Day. The results showed that: 1) The COVID-19 pandemic significantly impacted population heat map in leisure areas in Beijing on holidays, and the population heat map values of the three types of leisure areas investigated in this study declined by 54.2% and 53.0% on the Qingming Festival and Labor Day in 2020 as compared to the 2019 values, respectively. To be specific, the population heat map values of famous scenery, shopping services, and hotel accommodation decreased by 53.6%, 57.5%, and 52.9% on the Qingming Festival, and by 48.5%, 52.0%, and 55.6% on Labor Day, respectively. 2) There were differences in the degree of the impact on population heat map in different types of areas in famous scenery. The impact on the three major segments of famous scenery can be ranked in ascending order as follows: temples and churches (41.7%, 50.3%), parks and squares (53.1%, 47.1%), and scenic spots (61.1%, 51.2%). Wilcoxon rank sum test showed that the hourly variation of population heat map in temples and churches was smaller, and the overall demand can be ranked in ascending order as follows: sightseeing, daily leisure, and religious activities. 3) The 2020 population heat map of the leisure areas within the Third Ring Road of Beijing City was significantly negatively and positively correlated with the population heat map before the pandemic and area of these leisure areas, respectively. This can be attributed to the risk perception of the leisure crowds and the spatial and environmental factors of the disease prevention and control measures. This study provides a scientific basis for assessing the impact of the COVID-19 pandemic on leisure forms in big cities of China.