Industrial added value of China has been the largest in the world, and industrial sectors consumed a lot of energy and resources, which led to the destruction of the ecological environment. Thus, improving the industrial eco-efficiency is the important measure to realize the sustainable development. Eco-efficiency was first applied to measuring the environment performance of economic activities. The core connotation of eco-efficiency is to maximize economic benefits while minimizing environmental pollution and resources consumption, and the ultimate goal is to achieve sustainable development. Ecological efficiency has become an important tool for analyzing the impact of economic activities on the environment. This article takes different province as the research object and measures the industrial eco-efficiency with the aid of data envelopment analysis. Different spatial weight matrixes were constructed, and then the spatial evolution was analyzed by spatial autocorrelation analysis. On the basis of the optimal spatial weight matrix, spatial Durbin model was used to analyze the direct effect, space spillover effect, total effect of different influencing factors. Some conclusions were drawn as follows. The average value of the industrial eco-efficiency showed an obvious fluctuation trend during 2000-2015, and the absolute difference showed the similar trend, and the relative difference presented an “N” type change trend. The spatial distribution of the industrial eco-efficiency was characterized by “high in the southeast and low in the northwest”. The mean industrial eco-efficiency of Beijing and Shanghai was the highest, while the mean industrial eco-efficiency of Ningxia was the lowest. The spatial correlation feature of the industrial ecological efficiency was more accurately reflected under the comprehensive weight matrix combining geography and economy. The phenomenon of high and low clustering space club was also obvious. The overall effect of economic development, scientific and technological innovation and fiscal decentralization was positive, and showed that these 3 factors were the important driving force for promoting the improvement of overall regional industrial eco-efficiency, while the opening up had a negative impact on the improvement of industrial eco-efficiency. The direct effect value of fiscal decentralization was the highest, and opening to the outside world and fixed assets were the main factors to restrain the improvement of regional industrial eco-efficiency. Scientific and technological innovation and fiscal decentralization had positive spillover effect. Industrial agglomeration and opening to the outside world have negative spillover effects. On the basis of our study, we can find that industrial ecological efficiency had a spatial spillover effect, which was not only affected by various influencing factors in its region, but also affected by other regional influencing factors. Therefore, when formulating relevant countermeasures and suggestions, not only the regional influencing factors should be reasonably planned, but also the influence of different influencing factors in other regions should be taken into account.
The carbon emission efficiency of China's tourism industry presents complex spatial correlation characteristics for the interaction of multiple factors. It is of great significance for energy saving and emission reduction of tourism industry to clarify the comprehensive structure scenario of carbon emission efficiency in China's tourism industry. Based on panel data of 30 provinces in mainland China from 2001 to 2016, this article uses the SBM model to measure the carbon emission efficiency of tourism industry. Then, the method of social network analysis and the modified gravity model are applied to examine the characteristics of spatial network and its effects on carbon emission efficiency in China's tourism industry. The results show that: 1) The network relationship number and network density of tourism carbon emission efficiency fluctuate upwards. While the network grade and network efficiency decline gradually. The spatial correlation of carbon emission efficiency in China's tourism industry has been significantly strengthened. The network structure tends to be mature, but there is still much space for improvement from the ideal state. 2) From the analysis results of network centrality, the diversity of network centrality indicators in various provinces gradually decreases. Shanghai, Beijing, Jiangsu and other provinces rank steadily in the forefront, Chongqing, Fujian, Inner Mongolia etc. present a fluctuant rising trend, Ningxia, Qinghai, Shanxi and others rank relatively backward. 3) According to the analysis results of core-periphery structure, the network as a whole shows the trend of core districts expansion from eastern coastal areas to central and southwestern China, while the scope of the periphery shrinks gradually. 4) The network density is positively proportional to the tourism carbon emission efficiency and negatively correlated with the difference of tourism carbon emission efficiency. While the network grade and network efficiency are contrary to network density. The promotion of individual centrality indicators including degree, closeness and betweenness can significantly enhance the carbon emission efficiency of tourism industry. In order to promote regional cooperative emission reduction in tourism industry, targeted policies should be formulated according to the effects of network structure.
Within region, accessibility refers to the degree of convenience which a particular transportation system can be used to reach other cities or regions. Railway passenger transport is an important part of China's long-distance passenger transport system. The opening and operation of the high-speed railway has shortened the travel time between cities along the line, and has a profound impact on regional spatial organization. Temporal distance has been widely applied to the evaluation of railway accessibility. Based on the railway passenger transport flow, this paper captures the shortest time between 315 cities in China (excluding Hong Kong, Macau and Taiwan) by using the network data of www.12306.cn. And this paper explores the spatial pattern of urban time accessibility and the spatial connections and hierarchical characteristics of the inter-city time accessibility through the network analysis and the spatial analysis of GIS. According to the result of time accessibility, it analyzes the isochronous rings and daily-communication-area of 31 central cities. The research indicates: 1) At present, China has 315 prefecture-level administrative units with railway passenger train stops. According to the natural discontinuity classification method, the time accessibility level is categorized into seven degrees,present a core-periphery sphere structure. The central area extends axially along the main railway line and high-speed railway line, which shows the strong influence of the ‘corridor’. The urban time accessibility of the eastern and central regions is better than the western region. 2) The city pairs with time accessibility less than 2 hours constitute a ‘Five vertical and five horizontal’ zonation pattern connected by Beijing-Guangzhou HSR, Beijing-Shanghai HSR, Beijing-Harbin HSR, Beijing-Fuzhou HSR, Hangzhou-Shenzhen HSR, Qingdao-Taiyuan HSR, Xuzhou-Lanzhou HSR, Shanghai-Wuhan-Chengdu HSR, Shanghai-Kunming HSR and Guangzhou-Kunming HSR lines. Cities with time accessibility less than 10 hours cover most of the southeast region of the ‘Hu Huanyong Line’ and the urban belt is transformed into the urban network. Cities with time accessibility longer than 10 hours are mainly connected to the eastern and western regions with a long spatial distance. 3) Daily-communication-area of central cities expand axially. And the corridor effect is obvious. It is divided into four degrees according to the number of cities included in the daily-communication-area. The daily-communication-area covers 227 cities which mainly distribute in the southeast of the ‘Hu Huanyong Line’. This paper divides 19 urban agglomerations and Lhasa city circle based on the daily-communication-area of 31 cities. Compared with the urban agglomeration development plan approved by the State Council, the scope of the urban agglomeration is highly consistent, which provides a reference for the division of urban agglomerations.
Nitrogen Oxides (NOx) is one of major contributors to degrading the environmental quality in China. Moreover, it notably leads to haze and fog events. Hence, it is of great significance to study what determines NOx emissions. The existing literature on NOx emissions in China has been conducted mainly based on bottom-up method with the data from statistical yearbooks, which might suffer from statistical bias. Unlike these empirical studies, we obtained a data set of NOx emissions of 26 Chinese provinces from 2007 to 2016 estimated from satellite observations. In the first stage, this research analyzed the spatio-temporal characteristics of NOx emissions at provincial levels over China. Then, in the second stage it applied spatial econometric panel data models to discover the socio-economic driving factors of NOx emissions. The findings are the following. 1) High NOx emissions are basically concentrated on the industry-dominated or heavy-industry-dominated provinces, for example, Hebei province, Shanxi Province, Shandong Province, Henan Province, Inner Mongolia autonomous region, and on economically developed eastern provinces, such as Jiangsu Province and Guangdong province. 2) The results of Moran tests illustrated that provincial NOx emissions exhibited a significant spatial autocorrelation in space, implying spatial clusters. 3) From the results of spatial lag panel data models, the spatial autoregressive coefficient is significant and positive, indicating positive spatial spillovers. Besides, we observed that increases in provincial GDP, the share of the secondary industry, and coal consumption led to the rise of NOx emissions in China. On the other hand, technological progress and foreign direct investment have negative effects on NOx emissions, indicating that advanced technologies may be a best solution to reducing NOx emissions and improving the environmental quality. Finally, policy implications based on the main findings of the research were discussed.
From the perspective of cultural economic geography, industry development and the transformation of place are interacted. As for local industry, its development is rooted in local social and cultural system. Meanwhile, it is connected to regional or global production networks. The interaction between place and structure plays a key role in local industry development, and it provides a proper approach to discuss the transformation of place from the perspective of cultural economic geography. Taking a village specialized in jadeware processing and trade, the Yangmei Village in Jieyang, Guangdong as an example, using the qualitative research methods such as non-participating observation and in-depth interviews, this article analyzes the interaction between the development of local industry and the reconstruction of place, especially how place is embedded in and reconstructed by the development of local industry. Based on a research framework which focuses on the interaction among place, local actions and structure, the study finds that, local jadeware production has generated with the drive and help of different dimensions of local characteristics such as location and historic culture and grown with the changes of multi-scale political and economic patterns and the response of the local actors. In this process, placeness is the initial condition for local industry to come into being and establish external functional contact, and it is also the basis for the strategic choice and local marketing made by local subjects. But meanwhile, local practices such as production behavior of villagers, local social interaction and religious activities have been given the function and significance related to jadeware production. Changes in local activity have been reflected in the reconstruction of rural landscape such as the shape and structure of living space and traditional public space. This has also put impacts on the perception and identity of local villagers. The development of jadeware industry has provided local inhabitants with far more and better employment opportunities than ever before. Local villagers are satisfied with and proud of being in this place, which promotes their place dependence and attachment.
Based on the framework of multi-scale and multi mechanism analysis, using the methods of difference measure index, scale decomposition index, ESDA correlation analysis and panel data model, this article analyzed the spatial-temporal characteristics and driving mechanism of the economic differences in the three provinces of Northeast China from 2003 to 2016 based on three spatial scales-province, prefecture and county. The results show that: 1) The absolute and relative differences of regional economy in the three different spatial scales were obvious, and its had been expressed the scale pattern of county level > prefecture level > provincial level; the regional economic disparity showed a downward trend in general, and the difference of each scale and its contribution rate to the total disparity showed inter-city disparity > intra-city disparity > inter-provincial disparity. 2) There were significant features of spatial cluster for regional economic development in the three different spatial scales, spatial correlation and significant spatial correlation were positive and the concentration of Low and Low (LL) clusters, and the smaller the spatial scale, the greater the spatial dependence and heterogeneity. 3) The regional economic development showed a pattern of ‘Two Cores Two Belts’ in space, that was, taking the central and southern Liaoning and the great wall city group of Harbin as the core, taking the Harbin Dalian axis and the eastern border axis as the development axis belt. 4) The geographical location and factor endowment, strategic policy and financial support, administrative division and hierarchy, open drive and spatial optimization, and so forth, were the main influencing factors contributing to evolve the spatial-temporal pattern of regional economic differences.
Based on 5 937 logistics enterprises in Chongqing, the ecological niche model of logistics enterprises and counting model are adopted to identify the advantageous location and influencing factors of logistics enterprises from multiple scales. The following conclusions are drawn in the article. 1) At the district and county scales, there are 8, 8 and 22 districts and counties with a niche breadth in the high, medium and low levels, and a spatial structure of “one main gathering center and one sub-concentrating center” is presented around the main urban area and Wanzhou District; 2) On the street scale, 29 streets’ logistics enterprises density are on the first three floors, but among these 29 streets, only one street’s logistics enterprises state is on the first three floors; and 413 streets’ logistics enterprises density are on the last three floors, but among these 413 streets, 29 streets’ logistics enterprises state is on the first three floors; There are not coordinated in spatial distribution between logistics enterprises state and logistics enterprises density, and the outstanding problem is that logistics enterprises density in some streets is higher, but logistics enterprises state is lower; 3) From the perspective of influencing factors, trading volume in commodity exchange market and the presence of logistics nodes are highly positively correlated with the number of logistics enterprises, which are not affected by the scale. After weighting the scale of logistics enterprises, industrial output value is replaced by whether there is a factor of port layout.
China’s floating population is the biggest mobile population in the world. Most of its members are not able to settle down and be fully integrated into the destination cities, need to circulate between the places of origin and destination, and adopt multi-locational livelihood strategies. The bi-local or even multi-local housing arrangement is an important part of the floating population’s multi-locational livelihood strategies, and a growing body of literature has been devoted to understanding their housing conditions and their determinants in the destination cities in such a context. Nevertheless, within this growing body of literature, far less attention has been given to understanding the housing investment and its determinants of the floating population in the places of origin. Using data from a survey of the floating population in Fujian Province in 2015, this article intends to fill this gap by examining two forms of the floating population’s housing investment in their places of origin, namely village home renovation and housing purchase. The article estimates two binary logistic regression models to examine the underlying factors affecting the decision and location selection of the floating population’s housing investment in their places of origin, and the main conclusions are as follows: 1) Housing investment in the places of origin is quite common among members of the floating population, with village home renovation being more widespread than housing purchase as the form of housing investment. 2) The floating population’s housing investment at their places of origin has been significantly affected by the periods of the investment and the life course of the investors, resulting from the interaction among China's macroeconomic situation, relevant government policies, and life events of individual members of the floating population. 3) Life courses of individual members of the floating population, their multi-locational livelihoods strategies, and community characteristics of their places of origin jointly determine both the decision and location selection of the floating population’s housing investment in their places of origin. The individual life course is the direct force determining floating population’s housing investment in their places of origin, and the community environment in the places of origin is the external driving force for such investment. The average annual amount of remittances and the times of returning home of the floating population play important and positive roles in promoting the housing investment of floating population in the places of origin, but the familization of the floating population’s migration and participation in the transfer of land use rights have a negative effect on the floating population’s housing investment in their places of origin.
It is the precondition to achieve targeted poverty alleviation to find out the reason why people fall into poverty. Taking a remote minority-inhabited county, Wangqing, Jilin Province, China, as a study area, this article analyses the influencing factors of the annual net income of poor household at two levels: household-level and village-level by using multilevel analysis in HLM 6.8. In addition, the spatial heterogeneity of village-level characteristics is analyzed as part of understanding the geography of poverty. And the spatial heterogeneity of the village-level variables is checked by GWR. The results indicate that: 1) Internal household attributes and external environmental characteristics determine household poverty simultaneously, but internal factors dominate. 87.02% of the difference in annual net income of poor household is caused by the differences in characteristics at household-level. The remaining 12.98% is due to the differences in village-level environmental characteristics. However, the chi-square test of the estimated between-village variance component is proved to be highly significant, so the impact of environmental variables cannot be ignored. 2) Excluding the influence from village-level variables, excepting for the age, ethnicity and disability status of household heads, the gender, education level, disease status, labor capacity of household heads and the household size, dependency ratio, education burden, social relief and off-farm work at household-level are significantly associated with the annual net income of poor household. Female-headed households have lower income than male-headed households.And with the improvement of education level of household heads, income increases. The relationship between physical status of household heads and income is evident. As their health deteriorates, their incomes decrease. The disability status of household heads is also negative with income, but the results of t-tests are not significant. Labor capacity of household heads plays an important role in income, and the results show that household heads with normal abilities to work can get more income than household heads without normal abilities to work. In the study, household size, social relief and off-farm working increases the income of poor households. However, both dependency ratio and education burden decrease the income of poor households significantly. 3) Village-level variables can explain the difference of influence effect of household-level variables to different extent. The variance effect of ethnicity of household head is most affected by village-level variables. And the variance effects of the dependency ratio, disability status, gender and household size can also be highly explained by village-level variables. 4) The results of GWR show that there is spatial heterogeneity in the impacts of arable land, distance to county and average altitude from village-level. And the influencing direction and intensity of these 3 variables are different at different units. Based on the results, we suggest: Firstly the government of Wangqing county should formulate and implement poverty reduction strategies, adhere to the principle of "implementing policies for each household" in, and give attentio to "implementing policies for each village". Secondly, the government should improve the construction level of village-level education and medical service facilities, and reduce the threshold and cost of using public service facilities for poor households. More local employment opportunities should be provided by improving the employment environment. Lastly, the government should strengthen the regional coordination in spatial poverty governance, especially for the provincial-level border areas of non-centralized poverty-stricken areas.
The construction of characteristic towns is an important way to promote the agglomeration of regional spatial resources,optimize regional industrial structure, improve supply-side structural reform, and promote the sustainable and high-quality development of China's economy and resources protection. Based on the data of the first and second batches of national characteristic towns in China, with the help of GIS spatial analysis tools, methods such as Kernel Density Analysis, Neighborhood Analysis and Buffer Analysis are applied to analyze the spatial distribution characteristics and influencing factors of national characteristic towns in China. The results show that: 1) National characteristic towns are distributed in an agglomeration pattern in space, which are mainly concentrated in coastal areas, central regions, especially in the Yangtze River Delta with an uneven distribution in north and south. In the 3 zones, the distribution of national characteristic towns in the eastern and western regions shows a trend of decreasing gradient from east to west. In the eight partitions, the number of national characteristic towns gradually decreases from the eastern coast and the southern coast to the middle reaches of the Yellow River and the northwest of China. 2) The first batch of national characteristic towns with high-density core areas are located in the Yangtze River Delta region of China, and the micro-core areas are in Tibet and Xinjiang, showing a gradual decline from the coast to the interior, which is coupled with the spatial distribution of the three major economic zones in eastern and western China. While the second batch of national characteristic towns with high-density core areas are still located in the Yangtze River Delta region. The secondary core areas appear in Beijing-Tianjin-Hebei and the junction of Sichuan, Guizhou and Chongqing Provinces. 3) From the perspective of natural factors, national characteristic towns are concentrated in subtropical and warm temperate regions with small slope and topographic relief, low elevation and relatively flat terrain. From the perspective of social and economic factors, national characteristic towns are mainly distributed in the regions with good economic foundation, high-developed market and well-developed cultural industry.
The scale of China's online business has exceeded the order of ten trillion, and online business has developed into China's largest business group, with tens of millions of practitioners. Taobao (www.taobao.com) has become China's largest e-commerce trading platform, and it has become an important way for urban and rural residents to consume. Based on Taobao's five most common types of crown and gold crown shop data, a Taobao stores service quality evaluation index system was constructed, using entropy-TOPSIS, gravity models, and geographic detectors to analyze the overall service quality space of Taobao in China and the five major categories differentiation characteristics and influencing factors. The results show that: 1) Taobao stores in municipalities, capital cities, and economically developed cities have higher overall service quality than major less-developed cities. Household Taobao stores and electronic Taobao stores have a higher concentration of high-quality service areas than clothing Taobao stores, beauty Taobao shops, and food Taobao stores; 2) The service quality of the entire Yangtze River Delta and the Pearl River Delta regions and all major types of stores are network-shaped, and the service quality of the two cities interacts strongly; Beijing, Wuhan, Zhengzhou and other cities have a ‘central-peripheral’ radiation pattern; Two or two other cities are weakly connected. Spatial connection of service quality of beauty and food Taobao stores is more complicated than that of electronics, clothing, and home furnishings, and the strength of urban connection is better than the latter three categories. 3) The total retail sales of consumer goods plays a decisive role in the service quality of Taobao stores. In addition, the total amount of regional freight, the number of broadband Internet access households, the level of urban administration, and the number of ordinary colleges and universities play a supporting role. The influence factors of Taobao store service quality in the eastern region are highly interrelated, mainly multi-factor superimposed effects; the central region has a certain level of influence, and the influence of each factor is obvious; the western region is similar to the central region. However, the influence of each factor is weaker than that of the central region; there are relatively few influential factors in the northeast region, and each factor individually affects the service quality of Taobao stores.
It’s of great significance to identify the hotspot and its mechanisms of the urban tourism and leisure industry for efficient allocation of tourism leisure elements and optimization of the urban functional structure. Based on the data of industry interest points (POI), the spatial analysis methods such as Getis-Ord G* index are used in this article to explore the hotspots’ characteristics and their form mechanisms of the urban tourism and leisure industry in Xi'an city. The results show that for the comprehensive industry there are three tourism and leisure hotspots in Xi'an, namely, the Bell Tower hotspot in the center of the city, the Qujiang-Xiaozhai hotspot in the southeast of the city and the Electronic City hotspot in the southwest of the city. Meanwhile, there are inherent differences in the industrial agglomeration grade, scale and structure system of each hotspot. Similar to the distribution of the comprehensive industrial hotspots, hotspots of the subdivided industry are mainly concentrated in the urban core areas such as the Bell Tower, Qujiang-Xiaozhai and the city street named Electronic City. Essentially, the formation of urban tourism and leisure hotspots is determined by the orientation of urban development, that is to say, under the guidance of service transformation, urban space, as a geographical factor, exerts its influence on the humanistic factor, the urban tourism leisure industry, through the process of old city reconstruction and new district construction so as to make the tourism and leisure industry centralized in the urban core areas. By scientifically and reasonably guiding the agglomeration development of the tourism and leisure industry, the growth vitality of old urban areas can be rebuilt, and the spatial quality of new urban areas can be optimized effectively.
Household energy consumption has been a major contributor to the increase in global energy demand and carbon emission, and the household sector has also become one of the most crucial factors shaping the management of developments towards sustainability. Rural energy consumption not only affects the national economy significantly but also affects the living conditions of rural residents. Research of household-scale energy consumption patterns is important basic work. A comprehensive survey of households in the rural area of Qinghai Province was conducted from 2017-2018 to identify energy consumption characteristics. In particular, in this article, 3 typical household energy flow models were established. The following conclusions are drawn: coal, fuelwood, and straw are the major energy source for heating and cooking in the agricultural areas of Qinghai Province. Coal constitutes the largest portion of household energy consumption. However, the use rate of clean energy is quite low, and energy poverty is more prominent. The low-income households account for a large proportion of fuelwood and straw consumption. Households of different cultural backgrounds have different energy consumption patterns. The results of this survey will not only help decision-makers and scholars discover the possibility of energy conservation but also more effectively assess energy policies. According to the economic and geographical characteristics of Qinghai, the energy policies are put forward. For example, renewable energy is not only a solution to the energy shortage problem in rural areas, but also helps conserve fossil resources and protect the environment. The environmental problems have emerged with the change of household energy consumption patterns, making it necessary to conduct systematic planning on household energy construction.
Loess gully cross-sections carry greatly important information on evolution of loess landforms, gully erosion and sediment yield. However, systematically quantifying morphological characteristics of loess gully remains been poorly understood. The objectives of this study are to: 1) Analyze the characteristics of gully cross-section indexes (including basic gully cross-section indexes and compounded gully cross-section indexes) for different ranks of gully in the same sub-watershed, and for the same rank of gully in different sub-watersheds. 2) Reveal the relation of gully cross-section and loess landforms in different evolution stage. In this study, we choose Loess Broken Tableland (Yijun Watershed), Loess Ridge (Yan’an Watershed) and Loess Hill (Suide Watershed) as the study test sites, and classify the three watersheds into 5 ranks according to Strahler’s method. Our original studied data are 5 m-resolution Digital Elevation Models (DEMs) and the matched Digital Orthophoto Maps (DOMs) with 1 m-resolution. The DEMs and DOMs met the national standards of China; the DOM data was conducted by using of 5 m-resolution DEM. Based on 5 m DEM, we measured 19 indexes for 1 831 loess gully cross-sections in Yijun, Yan’an and Suide using GIS platform. Futher, we applied the principal component analysis method (PCA) to obtain 7 key indexes: namely, depth, width, cross-section eroded area, the ratio of width/depth, erosion degree, asymmetry ratio of side width and asymmetry ratio of side area of loess gully. The results demonstrate that: 1) The principle component analysis test showed that the cumulative contribution rate of depth, width, cross-section eroded area, the ratio of width/depth, erosion degree, asymmetry ratio of side width and asymmetry ratio of side area of loess gully already reaches to 95.02%. These indexes act as key indexes for characterizing loess gully cross-section. 2) With the increase of loess gully-rank, obvious increasing trends were detected in width, cross-section area, width/depth ratio, erosion degree of loess gullies. Besides, the trends of width/depth ratio and gully depth indexes indicate that low-ranks loess gullies present obvious downward erosion, whereas high-ranks loess gullies present lateral erosion accompanying with shoulder-lines retreating. 3) With the increase of loess gully-rank, the depth presents a trend of increasing firstly and then decreasing, and the turning points occur at intermediate-levels gully. The trend confirms the fact that intermediate-levels gullies have started to incise into bedrock.
Extreme temperature is an important indicator of climate change and an important reference for rational arrangement of agricultural production. Based on the daily maximum and minimum temperature of the Weihe River Basin during 1960-2017, and 16 indices of extreme temperature were computed to reveal the trend of extreme temperature in weihe river basin and its response to global warming. This article analyzed the variation trends of extreme temperature and its response on regional warming in different climate zones of basin. The results are as follows: The extreme cold index (ice days, frost days, cool nights, cool days and cold speel duration index) showed a downward trend of the Weihe River Basin during 1960-2017, while the extreme hot index (summer days, tropical nights, warm days, warm nights and warm speel duration index) had an upward trend, especially after the 1980s, the upward trend accelerated. The response of the extreme temperature index on regional warming in semi-arid regions was more sensitive and the response was mainly reflected in the increase of daytime temperature and the significant reduction of freezing and frosting days, while in semi-humid regions, the warming was obvious at night and in the extension of crop growth. Comparing with 1960-2004, the average temperature of basin increased by 1.62℃ during 2005-2017, warm nights and summer days increased by 8.33 and 7.28 days, and ice and frost days decreased by 8.68 and 2.58 days. Topographic condition was the important influencing factor of spatial variations of extreme temperature in this basin. In semi-arid regions of basin, the rapid reduction of ice and frost days are conducive to the growth of crops. However, in the semi-humid area with relatively high humidity, high-temperature heat wave events are more harmful with the increase of continuous hot weather in summer.
Based on the 270 soil profile data of the second soil investigation of Guangxi, the digitized soil type map (1∶500 000), the map of land use types, and the meteorological monitoring data of Guangxi, geostatistical methods and stepwise regression analysis were applied to analyze the spatial variation of soil organic matter and its influencing factors in Guangxi, China. Results showed that the soil organic matter in Guangxi was higher in the north but lower in the south, with an average of 3.11±2.19% and a coefficient of variation of 70.72%. Spatial distribution of soil organic matter is affected by both natural and anthropogenic factors. The comprehensive interpretation ability of six environmental factors to the variation of soil organic matter content is 47.9%. Soil type is the main influencing factor, which can explain 36.0% of the variation, independently. Altitude and soil parent material can explain 28.5% and 15.8%, respectively. Caused by that the effect of temperature on soil organic matter is greater than that of precipitation in Guangxi, spatial distribution of soil organic matter is displayed a trend of lower in the south but higher in the north of Guangxi. At the same time, sensitivity of soil organic matter to temperature was restricted by precipitation. In addition, there were also factors, such as agricultural farming management, which lead to the increase of soil organic matter in the study area.
Variations in glaciers in response to climate change in the whole Himalayas, which is located in the central southwestern part of the Tibetan Plateau, were investigated using Landsat Thematic Mapper (TM), Enhanced TM Plus (ETM+), Operational Land Imager (OLI), and meteorological data collected over the past 25 years. The results suggest that there were approximately 12 211 glaciers covering an area of 23 229.27 km2 in 1990. The total ice cover retreated by approximately 10.99%, with an annual percentage of area change (APAC) of nearly 0.44%/a during the period of 1990-2015. Based on the analysis of meteorological data, glacier shrinkage in the Himalayas can probably be attributed to the increase in air temperature and reduce in precipitation and the glaciers will continue to rapidly shrink in the next several years. The maximum area shrinkage occurred in 2.0-5.0 km2 in the Himalayas, with the overall number of glaciers was reduced in the period of 1990-2015, whereas glacier in the size class <0.2 km2 increased in area and the total number of glaciers increased significantly over 25 years; The largest glaciers in the area show a maximum elevation of about 5 200-5 600 m in 1990, 2000, 2010 and 2015. All glaciers, regardless of their orientation, have shrunk, but south facing retreated faster than those facing others directions, which indicated that glaciers on this aspect were more sensitive to climate changes in the Himalayas.
