Based on the analysis of its basic characteristics, this article investigated the disparities of Chinese service industry among the three regions （the eastern China, the western China and the middle China） and inter...Based on the analysis of its basic characteristics, this article investigated the disparities of Chinese service industry among the three regions （the eastern China, the western China and the middle China） and inter-provincial disparities of that in the three regions by Theil coefficient and cluster analysis. Then, major factors influencing its spatial disparity were explored by correlation analysis and regression analysis. The conclusions could be drawn as follows. 1） The development of Chinese service industry experienced three phases since the 1980s： rapid growth period, slow growth period, and recovery period. From the proportion of value-added and employment, its development was obviously on the low level. From the composition of industrial structure, traditional service sectors were dominant, but modem service sectors were lagged. Moreover, its spatial disparity was distinct. 2） The level of Chinese service industry was divided into five basic regional ranks： well-developed, developed, relatively-developed, underdeveloped and undeveloped regions, As a whole, the overall structure of spatial disparity was steady in 1990-2005. But there was notable gradient disparity in the interior structure of service industry among different provinces. Furthermore, the overall disparity expanded rapidly in 1990-2005. The inter-provincial disparity of service industry in the three regions, especially in the eastern China, was bigger than the disparity among the three regions. And 3） the level of economic development, the level of urban development, the scale of market capacity, the level of transportation and telecommunication, and the abundance of human resources were major factors influencing the development of Chinese service industry.展开更多
In this study, a number of typical precursory anomalies recorded by stations in Qinghai, Gansu, Sichuan, Xinjiang, Ningxia, Hebei and Shaanxi provinces and autonomous regions before the Ms8.1 earthquake in the west of...In this study, a number of typical precursory anomalies recorded by stations in Qinghai, Gansu, Sichuan, Xinjiang, Ningxia, Hebei and Shaanxi provinces and autonomous regions before the Ms8.1 earthquake in the west of Kunlun Mountains Pass are collected and checked. According to the standards of earthquake cases in China, the criteria of the precursory anomalies are determined, and 53 distinguished. The characteristics of these anomalies before the Ms S. 1 earthquake are analyzed, with results showing a very large earthquake affected area. The precursory anomalies recorded by instruments were 2900 km away from the epicenter, and according to the study in this paper, reached 2100 km away. The results also show that the anomalies present characteristics of long duration, multi-measurement items and large-amplitude variation. The authors believe that in large earthquake monitoring, attention should be paid to the variation of data over a large area, ranging up to thousands kilometers, with much denser earthquake observation networks.展开更多
Despite the rapid development of flower-viewing tourism in China in recent years,there is almost no systematic research on it.Therefore,this study analyzes the spatial and temporal distribution characteristics of flow...Despite the rapid development of flower-viewing tourism in China in recent years,there is almost no systematic research on it.Therefore,this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method.The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip,the flower observation data from China Phenological Observation Network,Chinese network news,and Weibo,and the statistical data from yearbooks.The results are as follows:1)The spatial attribution type of flower-viewing tourism in China is aggregated into areas,including two high-density aggregated areas,three medium-density aggregated areas,and one general-density aggregated area.Furthermore,five major types of flower-viewing tourist attractions have formed several aggregated areas.2)The time of flower viewing in China starts from about February and lasts about eight months till October each year.Florescence and flowering time of different ornamental flowers in different regions are different.3)The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology,spatial distribution characteristics of flower-viewing resources,regional permanent population size,youth population size,female population size,regional GDP,and added value of the tertiary sector.These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China.They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.展开更多
基金Under the auspices of National Natural Science Foundation of China (No 40871069)Megaproject of Science and Technology Research for the 11th Five-Year Plan of China (No 2006BAJ05A06)Natural Science Foundation of Beijing City (No 9072002)
文摘Based on the analysis of its basic characteristics, this article investigated the disparities of Chinese service industry among the three regions （the eastern China, the western China and the middle China） and inter-provincial disparities of that in the three regions by Theil coefficient and cluster analysis. Then, major factors influencing its spatial disparity were explored by correlation analysis and regression analysis. The conclusions could be drawn as follows. 1） The development of Chinese service industry experienced three phases since the 1980s： rapid growth period, slow growth period, and recovery period. From the proportion of value-added and employment, its development was obviously on the low level. From the composition of industrial structure, traditional service sectors were dominant, but modem service sectors were lagged. Moreover, its spatial disparity was distinct. 2） The level of Chinese service industry was divided into five basic regional ranks： well-developed, developed, relatively-developed, underdeveloped and undeveloped regions, As a whole, the overall structure of spatial disparity was steady in 1990-2005. But there was notable gradient disparity in the interior structure of service industry among different provinces. Furthermore, the overall disparity expanded rapidly in 1990-2005. The inter-provincial disparity of service industry in the three regions, especially in the eastern China, was bigger than the disparity among the three regions. And 3） the level of economic development, the level of urban development, the scale of market capacity, the level of transportation and telecommunication, and the abundance of human resources were major factors influencing the development of Chinese service industry.
基金funded by National Joint Foundation of Earthquake of China under Grant No.106086
文摘In this study, a number of typical precursory anomalies recorded by stations in Qinghai, Gansu, Sichuan, Xinjiang, Ningxia, Hebei and Shaanxi provinces and autonomous regions before the Ms8.1 earthquake in the west of Kunlun Mountains Pass are collected and checked. According to the standards of earthquake cases in China, the criteria of the precursory anomalies are determined, and 53 distinguished. The characteristics of these anomalies before the Ms S. 1 earthquake are analyzed, with results showing a very large earthquake affected area. The precursory anomalies recorded by instruments were 2900 km away from the epicenter, and according to the study in this paper, reached 2100 km away. The results also show that the anomalies present characteristics of long duration, multi-measurement items and large-amplitude variation. The authors believe that in large earthquake monitoring, attention should be paid to the variation of data over a large area, ranging up to thousands kilometers, with much denser earthquake observation networks.
基金The National Key Research and Development Program of China(2019YFB1405600)The General Project of Scientific Research Program of Beijing Municipal Education Commission(SM202110031002)+1 种基金The Humanities and Social Sciences Foundation of the Ministry of Education in China(18YJA630102)The Youth Academic Talents Project of Beijing International Studies University(21110010005).
文摘Despite the rapid development of flower-viewing tourism in China in recent years,there is almost no systematic research on it.Therefore,this study analyzes the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China using the spatial statistical analysis methods and the geographic detector method.The study uses the Point-of-Interest data of flower-viewing tourist attractions from networks such as Qunar and Ctrip,the flower observation data from China Phenological Observation Network,Chinese network news,and Weibo,and the statistical data from yearbooks.The results are as follows:1)The spatial attribution type of flower-viewing tourism in China is aggregated into areas,including two high-density aggregated areas,three medium-density aggregated areas,and one general-density aggregated area.Furthermore,five major types of flower-viewing tourist attractions have formed several aggregated areas.2)The time of flower viewing in China starts from about February and lasts about eight months till October each year.Florescence and flowering time of different ornamental flowers in different regions are different.3)The spatial and temporal distribution characteristics of flower-viewing tourism in China are mainly affected by ornamental flower phenology,spatial distribution characteristics of flower-viewing resources,regional permanent population size,youth population size,female population size,regional GDP,and added value of the tertiary sector.These conclusions clarify the spatial and temporal distribution characteristics of flower-viewing tourism and its influencing factors in China.They could provide a scientific basis and useful reference for the coordination and sustainable development of regional flower-viewing tourism in China.
