The urban built-up area boundary is important basic information for urban studies, and is also the premise of the implementation of urban function space layout, the implementation of boundaries control. Accurate extract urban built-up area for urban construction, management and research has important guiding significance, but also reflects the city's comprehensive economic strength and the level of urbanization, one of the important indicators.The DMSP/OLS night light data has been widely used in the extraction of urban built-up areas. But due to the effects of saturated, diffuse, and low resolution problems, it is still a huge challenge to rely on the DMSP/OLS NTL mapping the urban built-up areas. In order to overcome the limitations of the data source itself, In this study, the application of hierarchical expert knowledge analysis, multi-source data extraction of the thematic information layer by layer into the extraction process, the construction of urban built-up area for the level of expert knowledge model to achieve the city built-area refinement extraction. The urban index （VANUI） was constructed by combining 250 m MODIS NDVI data with 1 km DMSP/OLS data. Based on the administrative boundary, the statistical area of the area is divided into the administrative boundary of each prefecture-level city, and the optimal segmentation threshold of each administrative unit VANUI feature image is calculated according to the regional segmentation method, so as to obtain 250 m urban boundary space information range. Meanwhile, Due to the low spatial resolution of the DMSP/OLS luminous data and the narrow range of light and light values, there is still a large gap between the optimal segmentation threshold and the built-up area. Therefore, this study proposed the maximum autocorrelation double threshold extraction method. The 30m Landsat 5 NDVI data were fused to obtain the maximum autocorrelation quadratic NDVI threshold in each 30m seed region by multi-scale segmentation of the regional threshold segmentation. According to the maximum autocorrelation threshold of each potential built-up area, each potential built-up area is revised one by one, and finally 30m urban built-up area is obtained. This paper takes the Beijing-Tianjin-Hebei region as the research area, the experimental results show that the total precision of extracting urban built-up area by multi-source remote sensing cooperative method is 92.9%, and it has higher validity and reliability in spatial distribution and statistical data. The results show that the results of the urban built-up area extracted by this method are not only the overall accuracy, but also the spatial extent of the visual interpretation, and the relative error of the statistical area in each prefecture-level city is small, which verifies the reliability and validity of the method in spatial distribution and statistical data, and avoids the error caused by subjective threshold selection. DMSP/OLS data can be used not only for urban area extraction, but also for the intensity and scope of human activities. Therefore, in the follow-up study, based on the identification of urban built-up area boundary, combined with the quantitative analysis of luminous data and evaluation of urban development area outside the expansion trend and internal dynamic changes for the DMSP/OLS luminous data to give full play to its effectiveness, Economic and historical values play a positive role in promoting.

Earth is always changing. Knowledge about where changes happened is the first step for us to understand how these changes affect our lives. In this paper, we use a long-term leaf area index data (LAI) to identify where changes happened and where has experienced the strongest change around the globe during 1981–2006. Results show that, over the past 26 years, LAI has generally increased at a rate of 0.0013 per year around the globe. The strongest increasing trend is around 0.0032 per year in the middle and northern high latitudes (north of 30°N). LAI has prominently increased in Europe, Siberia, Indian Peninsula, America and south Canada, South region of Sahara, southwest corner of Australia and Kgalagadi Basin; while noticeably decreased in Southeast Asia, southeastern China, central Africa, central and southern South America and arctic areas in North America.

The existing finite element numerical simulation method of groundwater flow has some defects in the three-dimensional visual spatial analysis and the expression of numerical calculation process and simulation results. In order to solve this issue, the key steps of the finite element analysis process including the conceptual model construction, spatial discretization, hydrogeological parameters extraction and initial condition assignment are taken into consideration respectively. Based on the finite element method and 3D GIS platform, the method and technique framework of the groundwater finite element numerical simulation under 3D GIS are proposed with the supports of GIS spatial analysis algorithms and computer graphics theory. In addition to describe the technique framework, the core algorithms’ implementation details are given and the complete process of 3D GIS groundwater flow simulation is presented. The groundwater simulation example demonstrates that the proposed method and technique framework are capable of simplifying the finite element analysis process and improving the calculation efficiency of the model. The whole technique framework can be integrated into 3D GIS platform, and furthermore the visualization of simulation process and calculation results can be achieved eventually.

The mountainous regions of Southwest China, where Chongqing Municipality is located, has typical regional environmental characteristics such as cloudy fog and less sunshine. In order to realize the spatial simulation of temperature in this geographical environment, this study proposes a model for local regression considering terrain correction factor for solar radiation. In this model, the terrain correction factor is derived indirectly by fitting the spatial distribution of global solar radiation under undulating terrain. The model combines the Geographically Weighted Regression model, the Solar Analyst model, the improved Angtrom-Prescott equation, and the multiple linear regression method. Based on temperature, relative humidity, sunshine percentage, and global solar radiation of the meteorological stations, combined with DEM data with a resolution of 100 m×100 m, this model realizes the spatial simulation of temperature under the mountainous terrain. The model has good fitting accuracy and stability. The simulation accuracy of local regression term is much higher than Inverse Distance Weighting (IDW) interpolation and Kriging interpolation. It is also better than the traditional Multivariate Llinear Regression model based on latitude, longitude, altitude, sunshine percentage, and relative humidity. Further, 55 regional meteorological stations are used to verify the summer temperature simulation accuracy of a single year. The average absolute error is 0.59°C, and the errors of 38 meteorological stations are reduced after considering the terrain correction factor. The model performs well in spatial and temporal simulation of air temperature, which can reflect the influence of local terrain factors such as slope, aspect, and topographic occlusion on temperature, and has clear physical meaning. Based on the available observation data of meteorological stations, DEM, and the commercial software ArcGIS, this model is convenient to apply, especially suitable for cloudy, sunless areas like Chongqing and its surrounding mountainous regions.

Heatwave has become an extreme meteorological disaster which occurred frequently during the summer. Moreover, heatwave could evidently affect the healthy conditions of residents. Thus, study the spatial pattern of heatwave health risk would be helpful for us to prevent from and respond to the impacts of heatwaves. Using the historically meteorological datum of Xiamen, this study built a database of heatwave cases and analyzed the basic characteristics of heatwaves in Xiamen. Taking a heatwave event occurred in 2010 as a case, we analyzed the spatial pattern of heatwave health risk by using both the remote sensing data and the demographic data. It is concluded as the following statements. (1) The intensity of heatwaves in Xiamen is quite low, but its frequency is rather high. An intensive heatwave occurred occasionally. (2) The regions with high health risk are located in Xiamen Island, lying from the northeast toward the southwest. The regions with the highest healthy risk are located in the northern and southeastern Jiangtou sub-district, Huli district, and the most area of Xiagang sub-district and Siming district. (3) The human health risk pattern of Heatwave is associated with the spatial distribution of environmental and demographic factors. Generally, this study promotes and extends the scientific knowledge on the health risk of heatwaves.

Utilizing Landsat TM/ETM+/OLI imagery and digital elevation model (DEM) data, this study extracted the boundaries of glaciers and glacial lakes in Poiqu Basin, Xigaze City, Xizang Autonomous Region, China from 1990 to 2020 through the ratio threshold method and visual interpretation. The distribution and variation of glaciers and glacial lakes over three decades were analyzed, alongside the exploration of their co-evolution and response to climate change within the basin. The findings revealed: (1) A notable acceleration in glacier shrinkage within the Poiqu Basin over the last decade, with glaciers primarily situated between 5500 m and 6100 m. While the count of large-scale glaciers (≥10 km²) remained constant, small-scale glaciers (≤0.5 km²) exhibited an upward trend. (2) Both the number and area of glacial lakes witnessed a significant increase, with an expansion rate of 74.24%. Predominantly located between 4900 m and 5300 m, the expansion was more pronounced in larger glacial lakes (≥0.07 km²), whereas smaller lakes (≤0.03 km²) also saw a marked rise in numbers. (3) Glacial lakes connected to their parent glaciers emerged as the most significant type contributing to glacial lake expansion, registering a 72.08% increase. (4) The past 30 years have experienced a gradual temperature rise and a minor decline in precipitation. These climatic shifts, particularly the temperature increase and precipitation decrease, have been crucial in glacier retreat, while meltwater from glaciers has facilitated the expansion of glacial lakes. Through examining the distribution, changes, and interrelation of glaciers and glacial lakes in Poiqu Basin, this study aims to provide valuable data support for understanding glacier area dynamics and aiding in the prediction and mitigation of glacial lake outburst floods.

Based on the two dimensions of overall prosperity and achievement sharing,this paper constructs a common prosperity index system and applies the entropy method to measure the level of common prosperity in China at the provincial level from 2007 to 2020. This paper analyzes the spatial differences of common prosperity level using the Dagum Gini coefficient and portrays the dynamic evolution of its distribution using kernel density estimation. Moreover,it uses the Kaya identity and LMDI factor decomposition method to identify the driving effects of its dynamics. Conclusions are as follows: 1) The common prosperity level increased significantly on the whole and in three regions,which showed a distribution pattern of "decreasing from the east of China to the west of China". 2) The overall differences,intra-regional differences and inter-regional differences of China's common prosperity are narrowing,and the inter-regional differences are the main source of overall differences. 3) The level of common prosperity in three regions is characterized by strong unimodal aggregation,while the overall shows a trend of polarization. 4) The economic effect and equilibrium effect have significant positive driving effects on the improvement of China's common prosperity,the driving forces of social effect and efficiency effect are developing in a good direction.

The transformation and development of urban waterfront space is the key way to promote the optimization of urban space and the adjustment of industrial structure, which has become the main part of the current international urban renewal and redevelopment efforts, and a large number of relevant studies have emerged. Therefore, it is necessary to summarize the existing studies. Taking the relevant publications in the Web of Science and Science Direct databases from 1988 to 2020 as the analysis object, this study systematically examined the research results of the transformation and development of urban waterfront space abroad, summarized and analyzed the research contents and main conclusions from the aspects of the transformation process, mode, motivation and mechanism, and effect. The results show that international studies on the transformation and development of waterfront space mostly used qualitative methods to carry out descriptive analysis of cases, the research themes have shifted from paying attention to practical needs to exploring underlying academic issues and gradually diversified, and the research perspective increasingly emphasizes humanism and the concept of equality. Finally, considering the international research experience and domestic reality, this study proposed that in the future, China should change the research perspective and research object, pay attention to the comparative study of multiple cases in different regions, reveal the transformation process of urban waterfront space, simulate the transformation mechanism of urban waterfront space, and comprehensively evaluate the transformation effect of urban waterfront space, so as to optimize and improve the research system of urban waterfront space in China.

An artificial Masson pinus forest has been chosen to measure the precipitation inside and outside of the forest, as well as stemflow.

目前水温预报的降水资料严重不足，特别是无资料地区将很大可能利用卫星遥感反演获取降水信息，丹遥感资料提供的降水时间尺度往往较长，难以满足水文预报需求。论文提出了一种基于统计，针对独立降水事件，将长时段降水聚解为短时间尺度降水的方法。研究将此方法应用于史灌河七邻雨量站，分别聚解了七邻6h、3h、2h、1h降水为10min降水。研究表明，该方法计算简单，能保证模拟的总量同实际的完全一致，雨强同实际的基本一致，具有较好的区域适应性。图6表6参8

The characteristics of wetland landscape structure in watershed in the Naoli River the Sanjiang Plain are exhibited in three aspects. The first one is wetland landscape gradient characteristic in the longitudinal landscape structure of the watershed from the sources area of rivers to the lower reaches, which shows that wetland landscape types were differently distributed according to the topographic gradient and hydrological gradient and formed a wide riparian landscape corridor in the watershed; the second is wetland landscape gradient characteristic in the transverse structure of watershed with perpendicularity rivers in the watershed, which also shows that wetland landscape types are differently distributed in a topographic gradient and hydrological gradient and formed an extensively distributed wetland area in watershed's flood plain; the third is wetland landscape internal structure, which shows that many small mosaics or patches were distributed in the microscopic geomorphic units in the extensive wetland landscapes. The driving forces leading to substantial changes of wetland landscape structure in the watershed were identified as: 1) land reclamation has led to more than 75% of wetlands loss in historical periods and 98% of the lost wetlands direct conversion to agricultural lands in the watershed, which is the major reason for watershed wetland landscape structure changes; 2) drainage ditches construction for agricultural development and dikes construction for flooding prevention after the 1980s has led to wetland loss and fragmentation and landscape structure changes in the watershed; 3) changes in wetland hydrological condition due to agricultural development have led to wetland ecosystem degradation, as a result, almost all the remaining marsh wetlands in the plain were degraded to meadow wetland at present state.

With Pukou District of Nanjing as an example, the article introduces SLEUTH cellular automaton model and adopts the Landsat TM/ETM+ remote sensing data in five study periods(the years of 1988, 1995, 2000, 2004 and 2008)to simulate the general situation of urban expansion of the study area with or without the planned cross-river channels.And the influence of the planned cross-river channels on the urban growth of riverside city is analyzed from the perspective of quantity increase of construction land as well as spatial growth.The research shows that:1) SLEUTH model, after adjusted and tested, could well simulate the quantity growth of construction land as well as its characteristics of spatial distribution in the study area, therefore, it could be fairly applicable to the research of urban expansion of the study area; 2) the construction of planning cross-river channel has a significant impact on accelerating the growth of riverside city, but its driving effect will gradually decline year by year.The newly increased construction land in the study area will rise by 48.05% and 62.33% in 2020 and 2030, and the contribution rate of planned cross-river channel is 20.67% and 17.50%, with a decreasing driven effect year by year, which is particularly significant in the street of Jiangpu, Dingshan and Yanjiang in "Pukou New Town".

South Africa is China's largest trading partner and investment destination in Africa, especially in infrastructure construction. Study of the spatial distribution of South Africa's population is of great significance to the cooperation of the two countries. Based on the census data from 1996 to 2011, this paper describes the spatial pattern and evolving trend of the diverse population of South Africa with time series and cross section data between 1996 and 2011 at county level, based on population density analysis, spatial autocorrelation analysis, population gravity center model, shift-share analysis, and unbalanced index. Using the software platform of ArcGIS and OpenGeoDa, conclusions are made as follows. (1) Population density of South Africa has "high on east and low on west" features, and also has multicore clustering characteristics in metropolitan areas and port cities. (2) Population density varies significantly in different regions. Metropolitan areas and coastal port cities have high population densities, while central and western regions have low population densities. (3) In terms of trend in population change, population distribution in South Africa became more and more imbalanced from 1996 to 2011. The gravity center of population moves to the northwest of South Africa since 1996. (4) Shift-share analysis shows population growth rate have undergone "high-low-high" stages for the last 15 years. At provincial level, Gauteng andWestern Cape have been always the places with dense populations.

After the adoption of the policy of reform and opening-up to the outside world,many changes in politics,society and economy have taken place in the Yangtze River Delta region and have resulted in rapid expansion of urban area.Using multi-temporal remote sensing images,we analysed the spatial and temporal urban dynamic change pattern of the Yangtze River Delta region in the past two decades.The results showed that from the end of the 1980s to the year 2000,the main land use change pattern is the rapid decrease of cultivable land and forest area and the fast expansion of urban area.Urban land use in the Yangtze River Delta presents a concentrated expansion,typically from vegetation landscape to a mixed urban and rural landscape,i.e.,95% from farmland 1.8% from forest land and 1.5% from grassland.Using remote sensing image to categorize land use,monitor land use change,and calculate land use change transfer matrix is a promising method to show distributed spatial pattern of land use and land use dynamic change.There exist different constitutional proportions relating to land use dynamic changes between the first decade and the second decade.The urban sprawl speed is lower in the second decade than the first one.The land use dynamic change affects the eco-environmental change in this region.For example,the urban expansion pattern directly affects the local climate change and the air quality of this region.Analyzing the correlation between the spatial pattern of urbanization and eco-environment in this region,we found that the urban sprawl pattern is one of the direct factors affecting the spatial distribution of regional urban heat islands and spatial pervasion of urban air pollution.By comparing the relationship between the land use change pattern and eco-environment,we can provide sustained decision-making strategy for improving eco-environment,developing local economy,and promoting the social progress.

Water stress is one of the main factors that affect the crop growth. Water stress can induce agricultural drought, and decrease the yield. Analysis on the water stress under rain-fed condition can reflect the influence of local climate and soil on the crop growth. It is very helpful for the agricultural drought management and improving the water use efficiency (WUE). This study simulated the growth of winter wheat under rain-fed condition using EPIC (Environmental Policy Integrated Climate Model) crop growth model. The temporal and spatial pattern of water stress was analyzed. It was found that the rainfall in this area could not afford the demand of the crop growth. The water stress in the later period of winter wheat growth season was very serious, especially in the third 10 days of May when the frequency of the severe water stress was up to 48.2%. Through the contrast between regions, the Hebei-Shandong-Henan low-lying plain and the agro-forestry hilly region in Shandong were worse than the other two regions in the study period.

The characteristics of precipitation diurnal variations in spring and summer are investigated based on the TRMM satellite data from 1998 to 2012. The South China Sea (SCS) and surrounding areas are divided into four main regions: the South China region, Indo-China peninsula region, Malaysia region, and the SCS region. The results show that: First, in low latitude regions of the two hemispheres, the precipitation has opposite variation phases in spring and summer. In spring, the precipitation mainly occurs in Malaysia region and its surrounding area. However, in summer, the precipitation is more distributed over the SCS region and its surrounding area while the precipitation over Malaysia region is small. The Philippine islands, Indo-China peninsula, and the South China region present land pattern of diurnal variation, which means the precipitation maximum occurs after noon. For Malaysia region, the precipitation maximum occurs at night. Second, the diurnal difference is related to land-sea difference. In general, the precipitation is larger at night than that in the daytime over land area while it is larger in the daytime than at night over sea area. Moreover, the diurnal difference is generally more significant over sea area than over land area. The diurnal difference is most significant over the SCS in both spring and summer. In summer, it is also significant over the South China region. From spring to summer, the diurnal difference reduces in Malaysia and the SCS regions while it ascends in the rest two regions. Third, in summer, the Indo-China peninsula and the Philippines present similar patterns of diurnal variations. Their precipitation maximums occur at around T 17:00-20:00 in both areas, which is earlier than in spring. Meanwhile, the high precipitation period of the SCS region occurs earlier in summer than in spring. In both seasons, the diurnal variation patterns of the four regions are similar. The diurnal variations over the South China region and the Indo-China peninsula region present single peak pattern. In Malaysia region, the diurnal variation is relatively gentle. Fourth, based on the data from 1998 to 2012, in spring, the interannual variations of the occurring time of precipitation minimums are not significant in the Indo-China peninsula and the SCS regions while the variation in Malaysia region is relatively large. The interannual variations of the occurring time of precipitation maximums are little in Indo-China peninsula region. For Malaysia region, the variation has become smaller since 2005 and stayed small from 2005 to 2012. From spring to summer, the interannual variations of the occurring time of precipitation maximum become more significant over the Indo-China peninsula region and less significant over the SCS region. The interannual variations of the occurring time of precipitation maximum are similar in both seasons. Last, the seasonal difference can well illustrate the precipitation variation from spring to summer. After the burst of summer monsoon over the SCS region, the precipitation variation decreases slightly around Malaysia and equator areas while increases over South China, SCS and Indo-China peninsula regions, especially over the Philippine islands. What is noteworthy is that in South China region, the Xisha Islands and their surrounding sea show a negative seasonal difference, which means its precipitation decreases after the burst of monsoon, while the major part of this region has positive seasonal difference.

China has been experiencing unprecedented urbanization process. In 2011, China's urban population reached 691 million with an urbanization rate of 51.27%. Urbanization level is expected to increase to 70% in China in 2030, reflecting the projection that nearly 300 million people would migrate from rural areas to urban areas over this period. At the same time, the natural growth rate of China's population is declining due to the combined effect of economic growth, improvement in education quality, and modern social consciousness. As a result, Chinese government has loosened its "one-child policy" gradually by allowing childbearing couples to have a second child if either of them is from a one-child family. An accurate prediction of the future spatial pattern of population and its evolution is critical for a variety of key policy-making processes in China, such as industrial development, ecological conservation, industrial upgrading and transfer, and environmental protection. In this paper, a top-down method was developed to project the spatial distribution of China's future population with considerations of both natural population growth at provincial level and the population migration between provinces from 2010 to 2050. The results suggested that the overall spatial pattern of Chinese population is unlikely to change significantly over the next four decades. Shanghai, Beijing, Tianjin and Jiangsu will remain the top 4 provinces in terms of population density in China, and Xinjiang, Qinghai and Tibet continue to have the lowest density of population. China's population is projected to continue to concentrate in eastern coastal provinces. Population densities of Shanghai, Beijing, Zhejiang will peak in 2030, while that of Guangdong will keep increasing until 2035. Due to the large amount of moving-out labors and gradually declining fertility rates, population densities for Central and Northeast China will decrease from 292 persons per km² in 2010 to 253 persons per km² in 2050, exhibiting a downward trend. The majority of the western provinces, including Shaanxi, Chongqing, Guizhou, Yunnan, Sichuan, Gansu, Ningxia, Qinghai, Xinjiang, Tibet, Guangxi and Inner Mongolia are likely to remain sparsely populated, with an averaged population density no more than 100 persons per km².

It is of significance to study the effect of land use change on ec osystem service values.This paper aimed to provide decision support for sustain able use of resources and protection of eco-environment by assessing land use change and its consequent changes in ecosystem service values of Jilin Province .We obtained land use data by interpreting remote sensing images.Based on dyna mic data of land use in Jinlin,this paper analyzed changes in land use and ecos ystem service values using the ecosystem service value coefficients put forward by Costanza et al.In addition,coefficients of sensitivity were introduced to test the rationality of ecological value coefficients.Results show that from1 980to2000,area of rangeland,water bodies and wetlands decreased and oth er categories of land use increased.Due to comparatively small valuation coeffi cients(VC)of cultivated land and comparatively big VC of wetland and water bod ies,the increment in cultivated land could not offset the total decrement in regional ecosystem service values because of decrease in area of wetlands and wa ter bodies.Meanwhile,city sprawl has also led to loss of ecological values.T he total ecosystem service values of the study area reduced dramatically,from U SD12365.14×10 6 to USD10700.38×10 6 in period1980-2000.There was a13.46%net decline in annual va lue of ecosystem services in study area(i.e.USD1664.76×10 6 net decline in total ecosystem service values)and a0.72%decline per ye ar.In recent five years,the degradation of woodland,wetland and rangeland sl owed down because of enhancement of eco-environment protection.There was an 0.54%decline per year in ecosystem service values from1995to2000,w hile there was an0.78decline per year from1980to1995,which shows t hat the decline in ecosystem service values has been lessened in recent five ye ars.

Hydropower development and outward transmission in Tibet play a vital role in optimization of energy resource configuration and reduction of CO₂ emission in China. The low-carbon effects of hydropower development in Tibet were assessed, and fossil fuel consumption reduction and CO₂ reduction achieved by hydropower development in Tibet were analyzed based on net coal consumption rate, CO₂ emission coefficient and its dynamic change of fossil-fired power generation in different power grids. The results show that: 1) The fossil fuel consumption reduction and the CO₂ reduction achieved by hydropower development in Tibet have significant variations. During the period from 2006 to 2012, the fossil fuel consumption reduction and the CO₂ reduction achieved by hydropower development in Tibet were the most in 2011. 2) The fossil fuel consumption reductions achieved by hydropower development in Tibet were different significantly with different net coal consumption rates of fossil-fired power generation. The fossil fuel consumption reduction achieved by hydropower development according to net coal consumption rate of fossil-fired power generation in Central China power grid (CCPG) was the most, the fossil fuel consumption reduction according to net coal consumption rate of fossil-fired power generation in Northwest China power grid (NCPG) and Tibet power grid (TPG) took the second and the third place respectively, and the fossil fuel consumption reduction according to net coal consumption rate of fossil-fired power generation in national power grid (NPG) was the least. 3) According to different CO₂ emission levels of fossil-fired power generation, the CO₂ reductions achieved by hydropower development in Tibet were also different. Among them, the CO₂ reduction achieved by hydropower development according to CO₂ emission level of fossil-fired power generation in TPG was the most, the CO₂ reduction of hydropower development according to CO₂ emission level of fossil-fired power generation in NCPG and CCPG took the second and the third place respectively. 4) The fossil fuel consumption reduction potential and the CO₂ reduction potential achieved by hydropower development in Tibet were outstanding. According to net coal consumption rates of fossil-fired power generation in NCPG, CCPG, TPG and NPG, the fossil fuel consumption reductions achieved by hydropower development in Tibet in 2030 would be more than 75% of total fossil fuel consumption (1.379×10⁸ tec) of fossil-fired power generation in NCPG in 2012. Among the CO₂ reduction potentials according to different CO₂ emission levels, the CO₂ reduction achieved by hydropower development in Tibet according to CO₂ emission level of fossil-fired power generation in CCPG would be the least, but more than the carbon dioxide emissions of fossil fuel consumption in Argentina, Pakistan, Vietnam and other countries in 2013.

The development strategy of "extending to east and opening up to south" which cancelled northern groups has scientific meaning of "eco-city" and landscape ecology control.Its scientific values are embodied by the function of Baiyun District, which is constructing ecologic supporting system of economic development of the metropolis and big scale background, embodying the practical meaning of eco-economy and the development idea of constructing landscape city for Guangzhou.However, the economic development of Baiyun District is weaker than that of other districts of Guangzhou, and its urbanization level is lower, which is not according with the status as and administrative area of Guangzhou.The change of development focus weakened the superiority of Baiyun District, and the production factors of talents, capitals, techniques etc.are flowing to southeast.So, Baiyun District confronts double challenges of controlling and development.According to the district characters, plight and function, this paper suggests to settle the conflict of controlling and development through constructing three blocks, forming industrial groups, building ecologic residential districts and corridors.

As a man-made spatial or geographic element, administrative boundaries, acting like an invisible barrier, influence the process of globalization and regional integration. According to the statistics of literature associated with border effect since the 1990s, the number of studies in this field has increased greatly. In 1995, the study of international trade between the United States and Canada by McCallum promoted the progress of research in border effect. Most studies in the field of economic geography that followed focus on the mechanism and effect in three categories: the puzzle of border effect, market segmentation, and the progress of integration. When studying the puzzle of border effect, researchers always focused on three questions: "what is the connotation of the border effect?"; "what factors may affect the border effect?"; and "how wide is the border?" With regard to the integration and market segmentation studies of the border effect, transnational trade was always the research hotspot. With the gradual deepening of the studies, researchers not only paid attention to border effect in the field of economic geography but also focused on transboundary differentiation in tourism geography, urban geography, and political geography. Gravity model, convergence analysis, and monopolistic competition model were chosen to construct the border effect model. Although based on different theories, the virtual variable "border" was added to the models in the same way. Social network and the principle of "homogeneous repel, heterogeneous attraction" also were applied to the study of border effect. Further research can be carried out in the following three areas: studying the puzzle of border effect in view of the nature of administrative boundary, developing the research field of border effect, and the optimization and innovation of research methods.

Poverty is still remaining as the most prominent "short-board" in the Chinese economic development. The hardest and heaviest part of building well-off society in an all-around way lies in the rural construction, especially in the poverty-stricken area. The poverty alleviation and development in China is at the most critical stage, which requires more accurate recognition for the spatial differentiation of the rural poverty and its influencing factors, to make sure the exact targeting of the poverty alleviation policies and measures. This paper picked Shanyang, a key county in the poverty alleviation and development project of China, to explore the spatial pattern and type of the rural poverty of this county through the spatial autocorrelation analysis and grouping analysis. The stepwise regression, geographically weighted regression and Geodetector models were used to analyze the influencing factors of the rural poverty in this county, followed with the discussion on the spatial heterogeneity and interaction of the influencing effects. The following findings were concluded from the research: (1) The incidence of rural poverty in Shanyang noticeably clustered in space, forming 6 hot spots and 4 cold spots. In terms of rural poverty degree and spatial connectivity, the county was divided into low poverty area, mid poverty area and high poverty area. The space distribution was based on the regional poverty degree to facilitate a proper implementation of the poverty alleviation policies. (2) The major influencing factors responsible for the rural poverty in Shanyang included water network density, the distance to the nearest highway, proportion of dilapidated buildings, disposable income per rural capita, proportion of migrant workers and the proportion of rural households participating in the agricultural cooperatives. The influencing effects of all factors featured the spatial heterogeneity. Water network density and rural disposable income per capita were negatively correlated with the incidence of poverty while the rest factors showed a positive correlation. (3) The influence of the interaction between two factors appeared to be larger than that of the single factor. The interaction modes between major factors included bi-factor enhancement and nonlinear enhancement. Due to the interaction enhancement effects between poverty factors, the poverty alleviation policies shall be comprehensively matched to realize the expected target, along with a powerful poverty alleviation security system to ensure the full implementation.

Rural household biogas uses human and livestock manure as raw materials and its main products include biogas and biogas fertilizer. Suitable air and soil temperature is the necessary condition for household biogas digesters to generate gas safely and run normally. The low temperature and the frozen soil in winter or cold seasons are the main natural factors influencing the development of rural household biogas. According to the natural suitability, the development of household biogas can be divided into three different regions in rural China on the basis of regional principles, such as security, efficiency, conjugacy and integrity of the administrative regions, as well as regional indicator, such as frozen soil and temperature,. The naturally suitable regions are located in south China; conditionally suitable regions are in north China and west Sichuan - east Tibet Plateau; while the unsuitable regions in China are the cold area. Meanwhile, each region has some different sub-regions. It is not necessary to provide heat-retaining condition in naturally suitable regions, considering the heat preservation of household biogas digesters in winter. However, in conditionally suitable regions, to satisfy the heat-retaining condition is very important. In unsuitable regions, due to the low temperature, it is unsuitable to develop household biogas even if fully-closed heating barn is put up. Moreover, naturally suitable region in south China is further divided into three different sub-regions, which are the best level of naturally suitable sub-region in south China (including Southeastern Tibet), the medium level of naturally suitable sub-region in South of Changjiang River (including Sichuan Plateau) and the third level of naturally suitable sub-region in Han and Huaihe River valley. The conditionally suitable region is divided into five different sub-regions, including simply thermal suitable region in the area from north China plain to Loess Plateau and others, and Western Sichuan - Eastern Tibet Plateau is divided into two sub-regions including the high latitude cold area in northwestern part of northeast China and Tibetan Plateau high elevation cold area. Every region and its sub-regions are analyzed in different aspects, including the basic situation, natural suitability of household biogas development, basic requirements of building and heat preservation in winter of household biogas digesters. This study can provide scientific basis and decision guidance for the development of household biogas in the rural areas of China.

Different government departments and researchers have paid considerable attention at various levels to improving the eco-environment in ecologically fragile areas. Over the past decade, large numbers of people have emigrated from rural areas as a result of the rapid urbanization in Chinese society. The question then remains: to what extent does this migration affect the regional vegetation greenness in the areas that people have moved from? Based on normalized difference vegetation index (NDVI) data with a resolution of 1 km, as well as meteorological data and socio-economic data from 2000 to 2010 in Inner Mongolia, the spatio-temporal variation of vegetation greenness in the study area was analyzed via trend analysis and significance test methods. The contributions of human activities and natural factors to the variation of vegetation conditions during this period were also quantitatively tested and verified, using a multi-regression analysis method. We found that: (1) the vegetation greenness of the study area increased by 10.1% during 2000-2010. More than 28% of the vegetation greenness increased significantly, and only about 2% decreased evidently during the study period. (2) The area with significant degradation showed a banded distribution at the northern edge of the agro-pastoral ecotone in central Inner Mongolia. This indicates that the eco-environment is still fragile in this area, which should be paid close attention. The area where vegetation greenness significantly improved showed a concentrated distribution in the southeast and west of Inner Mongolia. (3) The effect of agricultural labor on vegetation greenness exceeded those due to natural factors (i.e. precipitation and temperature). The emigration of agricultural labor improved the regional vegetation greenness significantly.

Obligation assignment of carbon emission reduction needs to evaluate carbon emission charge by taking into account interregional transfer of carbon emissions. Carbon footprint, as a concept of carbon emission measurement, can evaluate life cycle carbon emissions of production and service to meet final demand. It should include direct carbon emissions caused by fossil energy as well as indirect carbon emissions induced by intermediate products production. This paper aims to estimate carbon footprint of each province and inter-provincial transfer of carbon emissions in China based on an input-output approach and China IRIO 2002 database. The results indicate there are significant differences of carbon footprint and per capita carbon footprint among provinces in China. The provinces with higher carbon footprint, mainly located in northern China, have large economic scale. The provinces with high per capita carbon footprint include developed metropolitan regions and energy-rich regions with a high proportion of energy intensive sectors. Interregional transfer of carbon emissions has emerged from energy-rich regions with a high proportion of energy intensive sectors to developed coastal regions and developing regions with incomplete industrial systems. The results imply developed coastal regions should bear more obligation of carbon emission reduction. As a significant amount of carbon emissions of energy-rich regions with a high proportion of energy intensive sectors is induced by provision of energy intensive products for developed coastal regions and developing regions with incomplete industrial systems, interregional transfer of carbon emissions should be taken into account for regional obligation assignment of carbon emission reduction. It can be considered to reduce obligation of carbon emission reduction for those energy-rich regions with a high proportion of energy intensive sectors. Otherwise, a compensation mechanism should be considered for developed coastal provinces to provide financial and technological aid to energy-rich regions with a high proportion of energy intensive sectors for improvement of energy use efficiency and reduction of carbon emissions.

The carbon emissions intensities of China’s thirty provinces caused by energy consumption were calculated according to the reference approach provided by IPCC. Exploratory spatial data analysis (ESDA), space-time transition measurement method and geographically weighted regression (GWR) model were employed to analyze the spatial dependence of provincial carbon emissions intensity and spatial heterogeneity of its driving factors from 1995 to 2015. The results were shown as follows: 1) There was a significant positive spatial correlation in carbon emissions intensity among provinces. Global spatial autocorrelation decreased first and then increased and last fluctuated slightly. The provinces with similar carbon intensity tended to be agglomerate, indicating that provincial carbon intensity had an obvious spatial dependence characteristics. 2) An uneven development pattern of carbon emission intensity existed in China's provinces. The provinces with H-H agglomeration were mainly distributed in the northwest of China, while the ones with L-L agglomeration mainly distributed in the southeast of China. 3) The spatial agglomeration of carbon intensity presented an overall trend of optimization, the provinces with H-H agglomeration decreased, while ones with L-L agglomeration increased. However, different provinces played different roles in the spatial agglomeration of carbon intensity. 4) The driving factors of carbon emissions intensity had obvious spatial heterogeneity among China’s provinces, and there was a positive correlation between the 4 explanatory variables and carbon intensity. The influence degree of 4 explanatory variables on carbon intensity was as follows: energy intensity>energy structure>industrial structure>per capita GDP. Different policies of carbon intensity reduction should be formulated according to the actual situation of each province. Therefore, in order to achieve regional differences in carbon emission reduction, it is necessary to take full account of the actual situation of carbon intensity in each province and the spatial differences of carbon intensity affected by different factors.