Structural and institutional factors such as lagging industrial transformation and upgrading, inadequate reforming of state-owned enterprise, un-development of private economy, and insufficient scientific and technological innovation capacity are the main limits for the revitalization of the Northeast region of China. At the same time, the complexity and spatial differences of problems facing the comprehensive revitalization of the Northeast China require to formulate revitalization paths and policies for key regional issues and problem areas. Hence, it is necessary to assess the socio-economic support capacity of the comprehensive revitalization of the Northeast region to clear where the place with strong stronger potential for rapid revitalization is, and where the place with weaker capabilities is and which should be focused on. Based on the comprehensive understanding of supporting capacity and the characteristics of the Northeast China, this paper establishes an evaluation index system of the social and economic support capacity of the comprehensive revitalization of three provinces of Northeast China on the prefectural cities-level in the perspective of ‘Five-concepts’, such as innovation, coordination, greenness, openness and sharing.It found that the social and economic support capabilities of different cities are significantly different. The core cities with strong economic and social development bases, such as Dalian, Shenyang, Changchun and Harbin, had higher scores on capabilities of each item. They not only have strong sharing capability, but also have stable social and economic development conditions and innovation. Furthermore, the relatively advanced state-owned enterprise reform and opening up process made them had strong capability on coordination and openness, which is good to attract foreign investment and local cultivation. On the other side, some resource-based cities, such as Chaoyang, Qitaihe, Suihua, Huludao, Tieling, Shuangyashan and Hegang, have weaker sub-sector and total support capability limited by vicious development model of ‘resource depletion-industrial depression-development mode solidification-insecure social security-poor investment and poor innovation-industrial depression’. So, it is important to apply different policies to different regions and different issues according to their spatial characteristics of revitalization supporting capabilities. In terms of innovation, greenness, and openness, it need to focus on key breakthroughs regions and guiding talents and innovative industries to concentrate on core cities such as Shenyang, Dalian, Changchun, and Harbin to improve urban innovation capabilities and external radiation capabilities. As for cities with better ecological environment located on west and east wings of Northeast China, it should vigorously develop ecological and organic industries in order to cultivate local economic growth pole. As for cities on the border areas, it should pay attention to population agglomeration with developing of special agriculture products processing industries, tourism, cross-border industrial cooperation and international trade. In terms of institutional and mechanism reforming and sharing capabilities, it should focus on increasing the scale of policy coverage. The reforms of administrative management mechanism and state-owned enterprises should be deepened with the forwarding of counter cooperation between Northeast cities and Eastern cities. Also, the construction of equalization of basic public services should be emphasized. Especially central government should pay more attention on the social security capacity building of cities in the northern Heilongjiang and the west-wing of Liaoning Province and Jilin Province.
From the perspective of innovation network of urban agglomerations, using the relevant data of innovation of urban agglomerations in the Guangdong-Hong Kong-Macao Greater Bay Area, and based on the principal component analysis, geographical gravity model and social network analysis, this paper studies the innovation level and division of urban innovation in the Guangdong-Hong Kong-Macao Greater Bay Area. The results show that from the perspective of innovation division of labor, innovation research and development are concentrated in nine cities in the Pearl River Delta, and innovation transformation is concentrated in Hong Kong and Macao. Further analysis of innovation and R & D cooperation shows that Shenzhen focuses on enterprise application-oriented innovation, while Guangzhou focuses on basic innovation, and they are in the center of innovation network in the bay area, driving four urban subgroups of interactive innovation, and forming three areas of innovation division in space. The Guangdong-Hong Kong-Macao Greater Bay Area has initially formed an innovative cluster development pattern, which provides a strong support for the economic growth of the bay area and becomes an important space carrier for the high-quality development of China's economy.
The ecological function of major urbanized areas in China was evaluated and analyzed at county scale, the correlation between ecological function index and three-level index was analyzed, and suggestions were put forward for areas with obvious ecological function decline. The results show that from 2009 to 2015, the proportion of districts and counties with high level ecological function of the ‘two horizontal and three vertical’ urbanization strategic pattern decreased from 78.68% to 68.13%. The proportion of districts and counties with high level ecological function of the optimized development zones decreased from 53.85% to 37.28%. Counties with obviously degradation in ecological function are mainly distributed in the southeast of Beijing-Tianjin-Hebei region and the Bohai coastal region. The proportion of districts and counties with high level ecological function index of the key development zones decreased from 73.78% to 69.21%. Counties with obviously degradation in ecological function are mainly distributed in the central Henan urban agglomeration and northeast region. Urban areas with ecological degradation are accompanied by different degrees of habitat quality index reduction, ecological space reduction, development intensity and population density increases. The order of the correlation between eco-function index and three-level index are as follows: Proportion of ecological space, habitat quality index, development intensity and population density. It is suggested to emphasize development control, strengthen ecological protection, implement classification control, and improve the long-term mechanism of differentiated coordinated development of different major functional areas.
Scientific and technological innovation is an emerging driving force for the development of the marine industry, which is essential for improving the quality of development. In this article, the SBM super-efficiency method is used to measure the marine scientific and technological industry innovation efficiency in the coastal provinces and cities of China from 2006 to 2014. The study areas include 11 coastal provinces and cities: Liaoning, Hebei, Tianjin, Shandong, Jiangsu, Shanghai, Zhejiang, Fujian, Guangdong, Guangxi, Hainan (limitation to data, not including Hong Kong, Taiwan and Macao). Combined with the nuclear density estimation, the spatial and temporal differentiation characteristics are analyzed. Then, from the 2 dimensions of investment scale and innovation efficiency, the marine scientific and technological innovation development type area is divided. The results are obtained as follows. Firstly, from the perspective of efficiency change in 2006?2014, there was a small increase in the efficiency of marine scientific and technological innovation in coastal areas, but the overall efficiency was low. The difference in efficiency among regions is first reduced and then expanded, presenting multiple levels of division, and the marine industry innovation activities completed the core transformation of development, and the core position is more prominent than ever. Secondly, from the perspective of the 2 dimensions of innovation investment scale and marine scientific and technological innovation, 7 types of innovative input-efficiency type zones can be identified in 11 coastal provinces and cities. On this basis, the regional development background and development momentum are comprehensively considered, and 4 types are further divided. Innovative development type zones: leading areas, catching areas, breakthrough areas and backward areas. The leading areas include Guangdong, Shanghai and Liaoning, which have a good marine industrial environment and the most advanced innovative technologies in the country, and are the core areas of marine scientific and technological innovation and development in coastal areas. The catching area is Guangxi, and the traditional marine industry is weak, but high-level marine industry innovation technology level and resource management capabilities have driven the rapid development of marine scientific and technological innovation activities. The breakthrough areas include Tianjin, Shandong, Fujian, Jiangsu, and Zhejiang, which have an excellent development of traditional marine economy and high level of innovation scale. However, low-level innovation technology has hindered the development of regional marine scientific and technological innovation activities. The backward areas are Hebei and Hainan. The traditional marine economy is backward, and there is no good innovation scale economy. Coupled with the poor ability of innovative technologies, the marine scientific and technological innovation and development activities lag behind other regions.
Compared with the mainstream indicators of GDP economic development level, the night lighting data has the advantages of high objectivity, time series stability and comprehensiveness. So, we use the NPP/VIIRS nighttime light data to characterize the economic development level, the spatial pattern of the county economy in Hunan-Hubei-Jiangxi border regions is visualized by the ESDA method, and the spatial heterogeneity of the factors affecting the economic development is studied by using the GWR model. The results show that: There is insufficient imbalance in the county economy in the Hunan-Hubei-Jiangxi border regions. With the decline of economic development level, the number of counties (cities) has increased significantly, and there is a clear ‘Pyramid’ type of hierarchical characteristics, and the low level county (city) is closer to the provincial border line than other regions, and the border effect shows obvious shielding characteristics; Spatial agglomeration is still at a low level, and the economic links among the counties need to be strengthened urgently. Moreover, this agglomeration is due to the low level similarity and shows the characteristics of ‘continuous poverty’; most of the hot spots are located in the periphery of the border area, the cold point area is located in the vast inner abdomen area. The imbalance between internal cooling and external heat has not been effectively resolved. From the results of spatial heterogeneity of economic effects of related factors, the labor, capital and government function all have positive effects. The high value of the return coefficient of labor input and capital input is in the hot area, and the low value is concentrated in the cold point area. On the one hand, the effect of government action decreases with the increase of distance from the region to the central city, on the other hand, it shows the difference between provinces. The impact of transportation level and education development level on economic development difference will show positive and negative polarization characteristics. From the perspective of spatial pattern analysis, it is necessary to deepen regional cooperation and fully improve the mechanism of coordinated development. From the analysis of influencing factors, it is necessary to improve the efficiency of labor transfer and the quality of labor employment; activate the potential of capital factors; enhance the educational supply capacity and education level; consolidate the construction of transportation infrastructure and actively enlarge the capacity of external traffic corridors in the Hunan-Hubei-Jiangxi border regions; and actively play the role of government guidance to mobilize the enthusiasm of local governments for economic development.
Based on the theory of living state, this article aims to build an index system of the living state of traditional villages according to material heritage system, intangible heritage system and village residents system. The author obtained these data through literature review, field survey, questionnaire survey and local interview and other methods to quantitatively evaluate the living state of three different types of traditional villages in Xiangxi, Hunan Province. The results shows that: First, the problem of inactivation is relatively common among these villages, and Dongshan village has the worst living state, then Xiaoshi village, and Disun Miao village has the best living state. Second, from the perspective of the system level, material heritage is the most important factor affecting the living state of traditional villages; and from the perspective of the element level, demographic structure, historical buildings and pattern texture are the main factors that affect the living state of traditional villages. Third, from the perspective of system level, intangible heritage is the main factor that leads to the inactivation of traditional villages in Xiangxi area; from the perspective of elements level, population, traditional skills, and natural ecological environment are the main factors that lead to the inactivation of traditional villages. In general, the living state of tourism traditional villages is better than that of urbanized villages and traditional villages. However, there still has some differences between active contribution factors and inactivation factors in different types of villages.
Population aging is becoming a prominent problem restricting the revitalization and development of Northeast China. This paper analyzes the evolution characteristics of the spatial pattern of population aging at the county in the three provinces of Northeast China from 2000 to 2010, and classifies the types of population aging by using static indicators (aging coefficient, the ratio of the aged and the young), dynamic indicators (age structure change, the number change of the elderly population and the non-elderly population, the growth rate of the elderly population), spatial autocorrelation and other measurement indicators and methods. The main conclusions are as follows: 1) In terms of static indicators, the aging coefficient and the ratio of the aged and the young all show an overall upward trend from 2000 to 2010, with more prominent regional differences, and the spatial distribution changed from ‘homogeneous’ to ‘polarized’. Urban agglomeration, resource-based urban districts and some border cities and counties in central and southern Liaoning Province have become the concentrated distribution areas of aging population and low birth rate. 2) In terms of dynamic indicators, during the study period, there are significant differences in age structure change, number change of the elderly population, non-elderly population and growth rate of the elderly population among the municipal districts of the four core cities, surrounding cities and counties of core cities, resource-based urban districts and border cities and counties. 3) Using static and dynamic indicators, the aging types in the three northeastern provinces are divided into five types, named aging with dilution, residual aging, aging in place, potential aging and non-aging. This paper summarizes the characteristics of each type of aging, and puts forward targeted policy recommendations for typical regions.
Online shopping has now become an important channel for residents to shop. To clarify the influencing factors of online shopping behavior is helpful to the formulation of e-commerce development strategy and the layout planning of physical business. Based on 1 156 online shopping behavior questionnaires of Guangzhou residents on November 2015 and March 2016 and the data of Point of Interest (POI) in 2016, this article explores the influence of 4 factors including 17 indicators on the online shopping frequency: personal socio- economic attributes, commodity characteristics, spatial environment and logistics express delivery, by using ordinal logistic regression model from whole city and different locations of Guangzhou. The results show that: 1) There are differences in the number, intensity and direction of influencing factors in different spatial scales and locations. The number of influencing factors is the largest in the whole city and the least in the outer suburbs. The effect of each factor is strong in the inner suburb and the whole city, but weakest in the outer suburb. The importance of return service plays an opposite role in the inner suburb and the central area. 2) Some spatial environmental indicators have an impact on the online shopping frequency. Urbanization level and accessibility of commercial centers have an impact on the whole city. Residents in higher urbanization level region and closer to the commercial center have higher online shopping frequency, which supports innovation diffusion hypothesis. The number of express delivery points has an impact on the central area. Residents with more express delivery points in residential areas have higher online shopping frequency. Other spatial environmental factors have no significant impact. 3) Personal socio-economic attributes have greater impact on the online shopping frequency than spatial environmental factors. Gender and age are the most important indicators, followed by education, occupation and monthly income. Women, young people, highly educated, upper-middle income residents have higher online shopping frequency. Commodity characteristics and express logistics indicators have a greater impact on the online shopping frequency in different regions. Residents who pay more attention to commodity characteristics have higher online shopping frequency. Residents with higher acceptance of the proportion of freight to transaction and express time have higher online shopping frequency.
The flows of passengers, goods and information are important expressions of interaction between regions, and it is a new attempt to analyze the differences of urban network structure in the space of various flows. Based on the actual big data, such as mobile phone call detail records and highway toll data, the various flows between the county-level administrative areas of Guizhou Province are measured. This study comprehensively analyzes the control structure, hierarchical structure and core-periphery structure of urban network in Guizhou Province, through the methods of C-value and T-value analysis, dominant flow analysis and network centrality analysis. Then, the key factors influencing various flows between cities (counties) were identified, and the results show that: 1) The control structure of Guizhou Province in the space of information and material flows are similar, but there are differences in control nodes. 2) In the space of information and material flows, Guizhou Province has formed a hierarchical network structure of provincial city-prefecture-county. 3) Compared with the space of material flow, the degree of centralization of the spatial network structure of Guizhou Province in the space of information flow has been further strengthened, and the gaps between cities (counties) have been further expanded. 4) The material and information flows between regions will decrease significantly as distance increases, and the geographical, cultural, industrial and organizational distances have a greater hindrance to the material flows between regions than the information flows. The regional attributes, such as economic development level, infrastructure level and population size also have significant impacts on the various flows between cities (counties).
All-for-one tourism is an idea which centers on tourism to boost industrial development, improvement of the urban and rural, residents' well-being, and environmental protection. As a novel concept and pattern of synthesized development within a specific region, all-for-one tourism highlights the match of tourism with economy, society, and ecosystem. Therefore, how to manage the match is an important question for local governments and academia. The research on the tourism-economy-society-ecology system coordination helps evaluate the infrastructure to promote all-for-one tourism in China, enrich the literature on all-for-one tourism, and achieve a balance between tourism, economy, society, and ecosystem. Jilin Province has the most (i.e., 15) exemplars of all-for-one tourist attractions on the list consisting of 262 all-for-one tourism attractions recognized by the Ministry of Culture and Tourism of the People's Republic of China. The great number indicates the hope of Chinese government on tourism industry of Jilin Province. Meantime, Jilin Province showcases great determinations to develop all-for-one tourism and formulates the policy of ‘All-for-one tourism navigates all-for-one Jilin’. Because of both external and internal factors, local government and stakeholders in Jilin have paid plenty of attention to all-for-one tourism. Therefore, Jilin is an appropriate and representative setting to investigate all-for-one tourism. This study takes a lens of all-for-one tourism and applies contrastive analysis to identify status of tourism-economy-society-ecology system of Jilin Province in the entire China. In addition, the present study uses obstacle diagnosis method to examine the system and determinants of all-for-one tourism. The results show that the infrastructure of all-for-one tourism in China is insufficient, and the degree of coordination of tourism-economy-society-ecology system varies significantly across provinces. Specifically, the degree of coordination decreases gradually from the southeast to the northwest. The economical development, societal development, and the tourism system of Jilin is below the national average, and the ecosystem is slightly above the national average. More importantly, the coordination of tourism-economy-society-ecology system is below the national average. Moreover, our results show that the tourism and economic system significantly hinder the coordination of tourism-economy-society-ecology system, and ecosystem is the slightest hinderance. Other hinderances include growth rate of population and GDP, domestic tourism revenue, total tourism revenue, and the number of A-star tourist attractions.
By constructing transportation superiority degree index and two sub-indices (traffic network connectivity, traffic external accessibility). This essay aims at evaluating the transportation superiority degree of the first level administration region in Kenya by using exploratory spatial data analysis method to find out the current spatial differentiation pattern of transportation superiority degree in Kenya from multi-dimensions, the influencing factors are also discussed. The conclusions are as follows: 1) Transportation superiority degree between different first level administrative regions shows significant spatial differences. Nairobi and Mombasa have the highest level of transportation superiority degree; Relatively high and medium transportation superiority degree of the first level administrative regions are roughly along the axis of Kenya railway in spatial distribution; Low and relatively low transportation superiority degree of the first level administrative regions are mainly located in the central inland and border areas. In terms of traffic network connectivity and traffic external accessibility, the first level administrative regions along the Kenya railway is stronger than the other first level administrative regions. 2) On the whole, the spatial pattern of transportation superiority degree in Kenya shows strong non-equilibrium. The specific manifestation is that the transportation superiority degree is bounded by the Equator, whereby the transportation superiority degree of the first level administrative regions south of the Equator is better than that of the north of the Equator. In addition, in the south of the Equator, the transportation superiority degree of the first level administrative regions along railway lines is better than that of other first level administrative regions. 3) The two sub-indices of transportation superiority degree in Kenya show significant spatial differentiation characteristics. Traffic network connectivity generally presents a spatial differentiation pattern with Nairobi as the core and Kenya railway as the axle belt, which decreases in a circle-layered manner to the surrounding areas, while traffic external accessibility roughly presents a spatial differentiation pattern from the southeast coast to the northwest inland and from south to north. 4) Topography, climate, hydrology, population density and economic development level have significant impacts on the spatial differentiation pattern of transportation superiority degree in Kenya. Kenya should firmly grasp the historical opportunity brought by 'The Belt and Road' initiatives, optimize and adjust the spatial distribution of transportation infrastructure, meanwhile, actively guiding the rational layout of economic space on this basis to promote faster and better economic development. Besides that, Kenya should attach importance to the planning and construction of road networks in border areas, actively promote the docking of railway and road networks in East African Community countries, and enhance its transportation links with surrounding countries. In order to promote the free flow of capital, labor, resources and products in East African Community countries, so as to achieve rapid economic development in Kenya and East Africa.
Accommodation industry is the major energy-consuming sectors of the tourism industry. Carbon emission of accommodation industry has become an important part of the countermeasures to global climate change, and is increasingly getting attentions from all of the governments and the academia. In this article, Xihai Hotel is taken as a case hotel of mountainous hotel in Huangshan scenic area. Energy consumption and account method and carbon footprint method was used to circumstantially analyze sample data. And energy consumption and carbon emission of the case hotel were studied in recently 5 years. The results showed that water and electricity were major energy consumption in the case hotel, electricity energy consumption was the highest, and about mean 98%, among total energy consumption. However, water energy consumption was the lowest, and only about 1%, among total energy consumption. Total energy consumption was 500 t standard coal equivalent (tce), the annual total carbon emission was 3 695.46 t carbon dioxide, and it was an increase trends year by year. Energy consumption of hotel main department of guest room and catering room was not the highest. The energy consumption of hotel auxiliary department of landscape greening and public was the highest, among total energy consumption in the case hotel from 2014 to 2018. Water energy consumption of other department was about from 39% to 58%, and electricity energy consumption of other department was about from 59.41% to 66.68%, among total energy consumption. Mean energy intensity was about 0.06 tce consumption per ten thousand yuan (RMB) output value, energy consumption of hotel guests was 1 kgtce per capita per day. Carbon emission was from 217.17 to 257.84 kgCO2/m2, the annual average carbon emission was 236.79 kgCO2/m2 in the case hotel. It was positive correlation between carbon emission and total energy consumption intensity, and total carbon emission would be increased when energy intensity was increased in the case hotel. The research has provided a scientific basis for energy-saving and emission-reduction in accommodation industry of mountain scenic area in the future.
This article uses the Boston matrix to introduce the competitive model of the tourism market, and analyzes the inbound tourism statistics of Jilin Province from 2009 to 2018. The results show that: The thin dog market and the young child market alternate and maintain, the bull market is shrinking, and the star market is blank. The conclusions can be drawn: 1) pay attention to the 4 major inbound tourist markets of South Korea, Russia, Hong Kong of China and Japan, and highlight the status of Korea’s leading source market; 2) develop new demand to enable South Korea to jump into the star market and prevent Hong Kong of China from retreating into the thin dog market; 3) revitalize Japan back to the young child market; 4) nurture Australia and the UK as the main market, and cultivate the French market as a star market; 5) develop markets in Canada, Germany, Singapore and the United States in a timely manner; 6) appropriately abandon the markets of Macao of China, the Philippines and Thailand; and 7) abandon the Taiwanese of China and Malaysia source markets.
Urban agglomeration is the main form of promoting urbanization, and inter-regional horizontal ecological compensation is an important measure for the ecological co-construction and sharing of urban agglomerations. Based on the input-output method, this article establishes an inter-regional ecological contribution measurement index system reflecting urban ecological input and ecological consumption, and uses the super-efficient SBM-DEA model to conduct an empirical analysis of inter-regional ecological compensation for urban agglomerations in the Beijing-Tianjin-Hebei region, the Yangtze River Delta and the Chengdu-Chongqing regions, to explore the inter-regional ecological compensation logic, standard and implementation path of urban agglomerations. The results show that, according to the input-output thinking, we can use the theoretical logic of ecological input and ecological consumption to reflect the interregional ecological relations, and establish the index system of ecological contribution and the input-output model to determine the role of ecological compensation and to consider the basis of compensation standards. The long-term mechanism of inter-regional ecological compensation in urban agglomeration based on ecological contribution is clear and feasible. We should speed up the improvement of the inter-regional ecological compensation mechanism, expand the measurement index of ecological contribution based on the unified registration management and regular monitoring bulletins of natural resource elements. The regional GDP, public finances, territorial spatial planning, coordinated regional development should taken into account, in order to calculate ecological compensation quota and establish a green benefit mechanism for regional ecological construction and sharing in the urban agglomeration system.
Southern Rare Earth Mine is the world's main production base for ionic rare earth mines, Which has brought immeasurable economic value to local and even China. However, while pursuing the economic benefits of rare earth mining, due to the lack of mining technology, a series of environmental problems have arisen, which seriously threatened the ecological safety of the mining area. In this study, taking rare earth mining area of Lingbei in south of Jiangxi Province as an example. Based on the landscape ecological security pattern theory and the method of minimum cumulative resistance model (Minimum Cumulative Resistance Model, MCR), and Identify and analyze the ecological source areas, ecological corridors, and ecological nodes of the mining area, to constructed the landscape ecological security pattern of the mining area in 2009, 2013 and 2018. The results show: 1) In the years of 2009 and 2013, the plaque area of the ecological source of the rare earth mining area was small, mainly concentrated on the east and west sides of the mining area; In 2018, the area of the ecological source gradually increased, and the location of the ecological source moved toward the direction of high resistance slowly. 2) During year has been selected, the area of the ecological source area and the number of the ecological corridors, radiation channels and ecological nodes are constantly increasing in the rare earth mining area. It shows that during these 9 years, the landscape ecological security situation of rare earth mining area has been improved to a certain extent, the ecological pattern began to rationalize. However, relevant departments still need to further plan and optimize the ecological security pattern of rare earth mining areas.
Hand, foot and mouth disease (HFMD) has become a major national infectious disease in recent years, and the incidence rate of HFMD in Hubei is the most serious in Central China. The study of HFMD in Hubei mainly focus on epidemiology, however, spatial and temporal characteristics and influencing factors have not been analyzed, and the spatial and temporal scales of the study are relatively rough. In this paper, the methods of geospatial analysis and statistics analysis are used. We aim to reveal the spatial-temporal characteristics and influencing factors of HFMD in Hubei from 2009 to 2016. Based on the case and incidence rate of HFMD and 11 indicators both in natural and economic factors, the matrix of 11 times 103 was built. The population distribution and seasonal variation of HFMD were collected by statistical methods. Then the correlation between incidence rate of HFMD and all kinds of influencing factors was analyzed. Then Moran index was used to identify the overall distribution of HFMD, and GETIS-ord index was used to measure the cold and hot spots of HFMD in Hubei. The spatial differentiation of HFMD incidence were explored by geodetector and geographically weighted regression model (GWR). The Results are as follows: 1) HFMD mainly primarily affects children under the age of 5 years, especially for 1 year old. While the incidence of HFMD in males is generally higher than that in females; the incidence of HFMD in women over 25 years old are higher than men of the same age. 2) The first incidence peak occurred from April to July, the second incidence peak occurred in November. The incidence is highest in May and the lowest in February. 3) HFMD is more prevalent in urban areas than in rural areas, and it is mainly distributed along the A-shaped urban skeleton. 4) The main meteorological factors like humidity, precipitation, temperature mainly affect the seasonal variation of HFMD, while the main socioeconomic factors like the number of beds per thousand and urbanization rate affect the inter-annual variation and spatial differentiation of HFMD. The prevalence of HFMD in underdeveloped areas is much more affected by economic factors. The incidence rate of HFMD is higher in Hubei province. Using mathematical statistics and geographical spatial analysis, this article analyzed the population characteristics, spatiotemporal characteristics and influencing factors of HFMD epidemic in Hubei from 2009 to 2016. The results showed the population characteristics with two peak ages of 0?5 and 25?30, and spatiotemporal distribution characteristics with ‘hot spots’ and ‘cold spots’. Because the OLS regression analysis has not considered spatial heterogeneity, combined with geodetector and geographical weighted regression, the regional disparity of incidence rate of HFMD can be analyzed in counties of Hubei. It can provide policy suggestions for the surveillance and control of HFMD in Hubei.
Pollen analysis is one of the best and possible approaches for the quantitative reconstruction of paleobotany, paleoclimate, and palaeoenvironment. Pollen is affected by many factors such as its own morphological structure, pollen production, sedimentation, transmission, preservation, and external environment, making the relationship between it and vegetation not a simple linear relationship. Therefore, it is very important to study the relationship between topsoil pollen and modern vegetation. In this article, we reveal the relationships between surface pollen spectra and modern vegetation from the Torreya forests, mixed broadleaf-conifer forests, tea garden and bamboo forests along the Xibai Mountain, Shengzhou City, Zhejiang Province. The pollen analysis results of surface soil samples show that: 1) 50 pollen taxa (genera or family) were identified, with the arboreal pollen percentages are 71.5%-92.9%, where Torreya grandis and Pinus massoniana are dominant pollen assemblages, the herbaceous pollen with 5.3%-24.7%, and then fern spores with only 1.5%-7.2%. In general, pollen assemblages are consistent with vegetation composition, though some differences also exist in different vegetation types. 2) The PCA results indicate that both Torreya grandis and the Torreya forests can be distinguished from the surface pollen samples. 3) The results indicate that the percentage of Torreya grandis pollen may reach 41.1% within the pure Torreya forests, but decreased abruptly when outside the forests (with only 5.2%-9.8%), indicating a poor dispersal ability. Therefore, we suggested that the ancient Torreya forests should exist locally when Torreya grandis pollen values exceed 10%.
Ecological compensation standard accounting is the core issue of regional ecological compensation practice, and the accurate measurement of ecosystem service value is the key to scientifically determine the ecological compensation standard. Taking the grassland of Ningxia Yanchi County as the research area, and integrating grassland vegetation and soil survey, grassland information extraction, remote sensing inversion, spatial analysis and other technical methods, three key ecosystem service types, including carbon storage, soil conservation and water conservation were selected and accurately evaluated based on the InVEST model before and after grazing ban (2000, 2015). On this basis, grassland ecosystem services value were estimated by using market value method, and the variation of grassland ecosystem services value before and after grazing ban were measured, that of the ecological compensation standard. Furthermore, using the methods of the hotspots and three-dimensional trend analyses to identify the ecological compensation standards at different scales. The results showed that: 1) Since the grazing prohibition, the grassland ecosystem service in Yanchi County has been significantly enhanced, including carbon storage increased by 456 600 tons, and its intensity increased by 0.42 t/hm2, water conservation increased by 93.51×106 t, and intensity increased by 211.14 t/hm2, soil conservation increased by 20.91×106 t, and the intensity increased by 44.93 t/hm2; 2) Grassland ecological compensation standard was 309.21 yuan/hm2 in Yanchi County, compensation standard on the township scale was between 7.25 and 1 146.36 yuan/hm2, while that on the village level was between 3.04 and 2 074.56 yuan/hm2, and the village-level compensation standard can better reflect the ecological contribution of grassland; 3) From the perspective of space, the three-dimensional trend of compensation standard on the village level was gradually improved from west to east and appeared with a U-shaped differentiation from north to south. And the hotspots of compensation standard on the village level were concentrated in the southeast and northeast of Yanchi County. The research can provide method support for regional ecological compensation standard accounting, and provide reference for grassland resource management and ecological compensation practice.
Northwest China is one of the regions with severe drought in China. Based on the monthly MODIS NDVI data from 2001 to 2018, the normal difference vegetation index NDVI and the vegetation condition index VCI were used as indicators of vegetation growth status, combined with the SPEI values calculated from the monthly precipitation and monthly mean temperature data from 2001 to 2018. Using the univariate linear regression trend analysis method and Pearson correlation coefficient to analyze the variation trend and spatial distribution characteristics of vegetation condition and meteorological drought in Northwest China, as well as the response of vegetation to meteorological drought in multiple time scales. The results showed that the growth of vegetation in Northwest China showed a trend of improvement in the period from 2001 to 2018, but the spatial distribution was significantly different. The improvement of vegetation in the eastern region was higher than that in the central and western regions. The average SPEI of the five different time scales in Northwest China all showed an overall increase trend in the past 18 years, indicating that the degree of drought decreased. In space, the overall trend of aridification was higher in the central and western regions and lower in the east. The vegetation growth status was positively correlated with SPEI in most areas. The overall performance showed that the vegetation in the eastern part of the Northwest China had the highest response to meteorological drought, followed by the western part and the middle part. Among the different vegetation types, the sensitivity of grassland to SPEI-12 was the strongest, followed by arable land, while the response of forest land was slower; the response of each vegetation type to SPEI-3 and SPEI-12 was generally higher in most months of the growing season.
