As an important theme of regional sustainable development, the relationship between population distribution and resources, environment, and socio- economic development has attracted much attention for a long time. The resources restriction on population distribution becomes more significant for population growth in China, especially the water resources. The population was 0.54 billion in 1949, and per capita water resource was about 5000 m3 in China at that time. Then, with the growing of population from 0.5 billion to 0.7 billion, till 1 billion, China's per capita water resource had dropped to 4000 m3 and 2800 m3 accordingly. When population reached 1.3 billion in 2005, per capita water resource dropped to about 2151 m3, till 2099 m3 in 2010, which means the restriction of water resource to socio-economic development had kept strengthening. A basic objective of this study is to investigate the water resources restriction and intensity on population distribution at different levels in China. This paper established a series of models for evaluating water resources restriction to population distribution. The spatio-temporal features of water resources restriction to population distribution in China were assessed comprehensively from 2000 to 2010 at three levels: national, provincial and county. The intensity, spatial pattern and changing law of water resources restriction to population pattern were also revealed quantitatively. The results showed that: 1) at the national level, the carrying capacity of water resources was dominated by water surplus in China during 1949- 2010, and the relationship between population and water resources has been strained. The restriction of water resources on population distribution in China increased during 2000-2010, up to 35.25 from 30.66, meaning that the water resources restriction to population distribution enhanced. 2) At the provincial level, the carrying capacity of water resources was also led by water surplus in China from 2000 to 2010 and the water resources restriction to population distribution was at low level in most provinces. To be specified, the restriction intensity of water resources for overall population distribution showed an upward trend at the provincial level during 2000-2010. 3) At the county level, the main feature of the carrying capacity of water resources in China was water surplus. From the aspect of the number of the counties, about 3/4 of the counties in China were not influenced by water resources restriction in 2000 and 2010. The restriction intensity of water resources restriction on population distribution was overall low at the county level and showed an upward trend from 2000 to 2010. 4) The basic spatial pattern of water resources restriction to population distribution showed that the northern China was higher than the southern and the Yellow River Basin was higher than the Yangtze River Basin.
The alteration of land use spatial pattern includes not only historical information of land use, but also trends of land use in the future. It is significant to use proper information to analyze the process of farmland conversion. This paper conducts a study of the spatial unbalanced development of farmland conversion in Wuhan city based on the land use data from 1990 to 2011. By using spatial statistics and spatial analyst functions in ArcGIS, a spatial Lorenz curve of farmland conversion in Wuhan city was fitted and a curve of farmland conversion gravity centers which was classification based on speed of farmland conversion was formed. Meanwhile, the correlation among the diffusion route of farmland conversion, GDP gravity centers curve and population gravity centers curve was discussed. The main conclusions are as follows: Firstly, Wuhan city was a typical mono-centric city, not a multi-center city which was traditional considered. The spatial distribution of farmland was unbalanced in Wuhan city, and the farmland conversion mainly occurred around the city center. The speed of farmland conversion in Wuhan city was unbalanced and the degree of this unbalanced development was declining from 0.8285 to 0.5289 measured by Gini coefficient. Secondly, during urban land expansions from 1990 to 2011, 36.15% of the expansion land comes from farmland. The fastest speed of farmland conversion is up to 55.58 km2 per year during 2005 to 2011. The multi-layer superposition based on the speed of farmland conversion classification shows that with the increasing of farmland conversion speed, the farmland conversion gravity centers of different layers move from the fringe to the center of Wuhan city and have a tendency of becoming dense. Thirdly, the trajectories of farmland conversion diffusion route, GDP and population gravity centers curves were following the same law that they moved to the north, then south and again north in south-north direction, and to the west, then east in east-west direction. The correlation among farmland conversion, GDP, and population indicated farmland conversion in Wuhan city was carried out orderly in space. This paper explores the spatial pattern of farmland conversion from several aspects, and the results perfectly reveal the unbalanced development of farmland conversion in Wuhan city and achieve this unbalance a visualization, moreover, explores the relationship among farmland conversion, GDP and population.
Spatial conflict is a kind of objective geographical phenomena, which is due to the scarcity of spatial resources and spillover of spatial function. It is an opposite phenomena associated with the resource allocation and competition in the process of human-land interaction. Geographic space is the basic object of research on geography, spatial pattern and process has been the core content of geographical research, the spatial conflict is the result as well as an influencing factor of spatial process, and it is also reflected in the spatial pattern. From the perspective of geography the basic point of space conflict is the disharmony of proportion structure, spatial pattern and mutual transformation process between different types of geographic space. Based on this, referring to landscape ecology index theory and method, identifying the connotation and calculating methods, and choosing Changsha-Zhuzhou- Xiangtan (Chang- Zhu- Tan) urban agglomeration to take the verification, the results showed that: 1) The spatial conflict index is the quantized index used to measure space conflict intensity, speed of changes and direction. It is an important basis of evaluation for spatial conflict risk, revealing the mechanism of the formation and evolution of spatial conflict. Based on the direction of geography, the types of spatial index can be divided into spatial type conflict index (STC), spatial structure conflict index (SSC) and spatial process conflict index (SPC). 2) It has been concluded from the test of spatial conflict index on Chang-Zhu- Tan urban agglomeration that the total spatial structure is barely reasonable. The spatial conflict has not happened yet, but the speed of transformation from un-constructional space to constructional space is too fast. Because the limited agriculture space, and irrational distribution of some districts especially industrial districts, conflict of spatial type and process has been emerged. Even in some units the space conflict has exceeded the upper limit threshold, where there is a large possibility for the happening of spatial conflict risk. Additionally, patterns of spatial conflicts present urban-rural gradient changes, and the spatial type conflict in city area is prominent, while the districts with serious spatial pattern and process conflict mainly are distributed in the suburbs or mutual connection of Chang-Zhu-Tan. After verification, the conclusions of empirical analysis are basically consistent with the actual situation, which further explains that the construction of spatial conflict index is scientific and has geographical significance.
Land use change has been one of the most important drivers to significantly influence the provision of ecosystem services. Impacts of land use change on ecosystem services have been one focus of ecology research and attracted more and more attentions from domestic and international. However,impacts of cropland change on ecosystem services in eastern coastal developed regions of China are still not clear, which limits comprehensive understanding of the mechanism between land use change and ecosystem services. In this paper, the Taihu Lake Basin was chosen as the study area due to its representativeness of rapid economic development and commodity grain base in this area. Based on remote sensing data and the statistics, spatial and temporal change of cropland and its impacts on ecosystem services were carried out in the Taihu Lake Basin. Three key ecosystem services—gain production, carbon sequestration and water conservation were selected to examine what extent and how cropland change on eco-logical services. The results showed that: 1) The area of cropland decreased significantly over the past 25 years in the Taihu Lake Basin, mainly transforming into urban and built-up areas. A small reduction of cropland with 1346.84 km2 in 1985-2000, mainly concentrated in Shanghai Municipality and Jiangsu Province. While cropland area decreased by 4317.46 km2 in 2000- 2010, which presented an obvious degraded trend at the county-level. 2) Ecosystem services in the Taihu Lake Basin in 1985-2010 presented an obvious degraded trend. Rice and oil production decreased by 39.6% and 56.6%, respectively, only wheat production presented a very small increment. Regulating function decreased significantly, of which soil carbon storage obviously decreased, but little effect on water conservation capacity. We propose to strengthen the protection of cropland to coordinate the balance between cropland protection, economic development and ecological services in the Taihu Lake Basin, which is beneficial for reducing pressure on degradation of ecosystem services for cropland decrease.
Understanding the responses of soil respiration to land use changes becomes critical in predicting soil carbon cycling under conversion of arable land into grassland on the Loess Plateau. From March 2011 to December 2012, CO2 efflux from the soil surface was measured from 8:00 to 12:00 am in clear days by a Licor-8100 closed chamber system (Li-COR, Lincoln, NE, US). Also, soil temperature and soil moisture at the 5 cm depth was measured using a Li- Cor thermocouple and a hand- held frequency-domain reflectometer (ML2x, Delta-T Devices Ltd, UK) at each PVC collar, respectively. Since returning cultivated land for 27 years, the mean grassland soil respiration (3.55 μmol·m-2·s-1) was averaged 2.61 times higher than paired cropland soil respiration (1.36 μmol·m-2·s-1) and the cumulative CO2-C emission in grassland (981 g C·m-2) was 2.75 times higher than that in cropland (357 g C·m-2). In 2011, the temperature sensitivity of grassland (Q10) improved by 24.5% compared with cropland, and in 2012 it reduced to 2.4%. We found marked differences in soil characteristics related to different landuse types: the mean grassland SOC (10.5 g·kg-1) was averaged 61.5% higher than paired cropland SOC (6.5 g·kg-1) and the SMBC (204 mg·kg-1) was averaged 34% higher than cropland (152 mg·kg-1). Soil moisture from 0-5 cm depth was much drier in cropland and significantly different between cropland and grassland except for winter. However, there were no clear differences between soil temperatures. SOC and soil moisture differences between cropland and grassland can explain the soil respiration difference caused by land-use change, which was confirmed by the validation results.
Farmland ecological compensation is an effective economic way to motivate farmers to protect and maintain the ability of ecosystem services of farmland, which improves the externalities of ecological benefits caused by market failures. It also has a positive impact on improving environment of farmland ecosystem, expanding the open space, and increasing farmers'income. In this paper, we draw the relationship between farmers'livelihood diversity in developed areas and their participation in farmland ecological compensation policy response by the structure equation model (SEM). The results indicate that the farmers'basic features, family characteristics, livelihood diversity and regions developing level have a positive impact on farmers'supportive willingness of farmland ecological compensation policy (5% level significantly). It further gives the farmers'basic features, family characteristics and livelihood diversity characteristics generated positive influence on farmers'response of compensation policy effect, and regional developing level has a negative impact on it (5% level significantly). Finally we rank by the factors which generated more positive effect on farmers'supportive willingness and their response of ecological compensation policy. We find livelihood diversity characteristics are the dominant factor on former and the second largest factor in sequence. Overall, the livelihood diversity characteristics have a positive effect on both farmers'supportive willingness and policy response. So it is important for government to take these issues into consideration when draft an effective farmland ecological compensation policy. And those results will provide a guide for the development of farmers'livelihood diversity.
Identifying the characteristics and the prominent factors of grain output change is helpful to make specific policies for upgrading grain production capacity. Based on the statistical data of grain output and grain sowing area, the logarithmic mean weigh division index method (LMDI) and decomposition model were adopted to reveal the structural characteristics and the influencing factors of variation of China's grain output during the period between 1980 and 2010. The results showed that: 1) The total grain output of China increased by 2.26×108 t from 1980 to 2010. It was estimated that the accumulated contribution of grain sowing area and grain yield per hectare at national scale were -0.21×108 t and 2.47×108 t, respectively. Grain yield per hectare was the major contributing factor for the increment of total grain production. 2) The proportion of rice, wheat and corn in total grain output showed obvious increasing trend and the percentage rose from 80.39% to 89.33%, accounting for 102.01% of the total increment between the years 1980-2010. At the national scale, rice yield per hectare, wheat yield per hectare, corn yield per hectare and corn sowing area were the top four contributing factors for grain output increase. For the effect of grain yield per hectare, each crop had the positive impact during 1980 to 2010, and rice yield per hectare played a prominent role in the total grain increment (accounting for 34.42%), followed by wheat yield per hectare and corn yield per hectare. For the effect of grain sowing area, corn sowing area had the most significant positive effect, while rice sowing area, other crop sowing area and wheat sowing area had the obvious negative effect. 3) There was significantly spatial difference for each contributing factor of grain output increase at the provincial scale. Heilongjiang and Henan were the largest contributing provinces, whose cumulative contribution rate reached up to 30.27%. The major grain producing areas were moving to the northeast and central regions of China. The rapid growth of rice yield per hectare lead to steady rise of rice production in the south, while the superposition of rice yield per hectare and rice sowing area enhanced the total rice output rapidly in Heilongjiang province; the coupling of wheat sowing area and wheat yield per hectare further highlighted the comparative advantage of wheat production in Huang- Huai- Hai region; the combined effect that the expansion of corn sowing area and the growth of corn yield per hectare contributed to the evident increase of rice production in Huang-Huai-Hai region and Northeast region in China. The production advantage areas of wheat, corn and rice were gradually established. However, the output of soybean, potato and other crops increased slowly, and has not yet formed a clear advantage area. The paper concluded that, in addition to improving grain yield, stabilizing the grain sown areas was another important strategy to further stabilize and increase grain production capacity.
Based on multi-temporal land use data and remote sensing data, through GIS technology and the land use dynamic degree, and spatial overlay analysis model, this paper analyses Dalian Jinshitan National Tourist Resorts land use spatial pattern evolution and driving mechanism from 1992 to 2009. Research shows that: 1) land use change models show a significant reduction in arable land and construction land but transportation land increased rapidly: 1992- 2009 Jinshitan witnessed the fastest reduction of arable land in single type of land use dynamic degree, the annual rate of change was 4.66%; the fastest increase was construction land, with an annual rate of change being 21.32%; most of the arable land were transferred into construction land, during 1992-2009 891.35 hm2 of arable land were turned to construction area, accounting for 54.76% of the total cultivated land area; tourism land area increased by 425.35 hm2, representing an increase of construction land area of 27.69%. 2) Construction land space expanded along the traffic lines and the coastline, presenting the tourist attractions of central tendency, mostly in the south of Longshan, Manjiatan and Chenjiacun, and from this region to the surrounding area constantly. 3) Compared with non-tourist towns, Jinshitan gradually changed from the original single land use type of the compound to the tourism-led land transformation. Driven by the three main bodies of“government”,“enterprise”, and“residents”, Jinshitan National Tourist Holiday Resort experienced a land use spatial evolution pattern of taking“natural resources protection”–“tourism development”as the lead and–“protection as a precondition for moderate development”
At first, a multitemporal urban land use information is extracted from the Landsat images of Guiyang in 1947, 1973, 1990, 2001, 2006 and 2010 using multiple source data including historical literature, thematic maps and Landsat images, in which the spatiotemporal feature of urban expansion is analyzed after 1279. These characteristics involve expansion trend, direction, expansion intensity, scale and spatial differentiation and so on. The results show that: 1) before 1947, the main expanding directions were the south (Huaxi) and the west (Jinyang), and the main type was sprawling outwards, the velocity of urban expansion was slow. 2) The urban expansion of Guiyang filled in a small basin region from 1947 to 1973 and started an expansion out along the valley topography. The urban expansion showed a diffusion trend outward in the main urban region after 1990. 3) The expansion of urban fringe of Guiyang was arrived to the south (Huaxi), the east (Longdongbao), the northeast (Xintianzhai) and the west (Jinyang). Urban expansion of Guiyang after 2006 showed a significant Y-shaped pattern. At last, current rapid expansion of Guiyang is not suitable to the local sustainable development, Guiyang city is suggested stopping such rapid spatial expansion.
The Dongjiang River (East River) is one of the three major tributaries of the Pearl River in southern China. It is also the vital water source for lots of important cities, such as Hong Kong, Shenzhen and Dongguan. Changes of runoff will have a significant impact on the environmental security and economic development of this region. A distributed hydrological cycle model of Dongjiang River Basin was developed based on the SWAT model (Soil and Water Assessment Tool) and the hydrological cycle of 51 years (1960-2010) was simulated. The“Sequential Uncertainty Fitting Algorithm”(SUFI- 2) was used to calibrate/validate and analyze the uncertainty of the model. Firstly, the monthly flow data from 1960 to 1985 of the four main hydrometric stations was used to calibrate. Then the model was validated with the monthly flow data from 1986 to 2010. And prediction uncertainties were quantified by P-factor and Rfactor. Model performance varied from weak at Heyuan to satisfactory at Longchuan, Lingxia and Boluo (outlet of the basin). This is because Heyuan hydrologic station was located closely to Xinfengjiang Reservoir, the largest reservoir in Guangdong Province. The results (coefficient of determination, Nash-Sutcliffe efficiency) of calibration and validation at Boluo station were 0.83, 0.83 and 0.84, 0.84 respectively. The P-factor and R-factor at Boluo were 0.76, 0.54 and 0.74, 0.59 respectively. On the whole, the model performed well, and then the spatial difference of the hydrological processes was discussed. The runoff depth of Dongjiang River Basin was affected mainly by precipitation, ascending from the north to the central and descending from the central to the south. Hydrological characteristic of basin underlayer (slope, vegetation, soil, etc.) also affects the processes of runoff generation. For example, soil moisture differs significantly from the north to the south. In the north more rain turned into soil water because of the high forest coverage and the soil properties. This is conducive to water conservation and soil conservation. And also, the evapotranspiration accounted for the largest proportion of rainfall in the north attributed to the impact of forest cover.
Based on SWAT Model and SUFI-2 algorithm, combined with GIS and RS technology, runoff responses to land use change in Ganjiang Basin were analyzed quantitatively using various data derived from watershed DEM, land use, soil and meteorology in this paper. It was concluded that the top three sensitive parameters influencing model were ALPHA_BF, CN2 and ESCO, respectively. The simulation values of calibration and validation periods were in accordance with actual values, R2 and Nash-Sutcliffe efficiency coefficient ENS were higher than 0.90, the relative errors |Re| were all less than 3%. Forestland, paddyland and grassland took about 85% of the total area of Ganjiang Basin from 1990 to 2000. In the same climate condition, monthly, annual runoff manifest obviously consistent trends under two different land use scenarios, the annual runoff in 2000 is slightly larger than that of 1990 on the whole. Compared with 1990, runoff of the subbasins increases significantly in the east, southeast, southwest region in 2000. The growth of development land, irrigated land and bare rock, reduction of forest area are likely the main factors causing the increase of water production.
The Z index and Standard Precipitation Index (SPI) as well as the REOF method and Hurst exponent are used to analyze the features of droughts and floods. The spatial and temporal distribution of droughts and floods is investigated, and the long-term trend is detected. The result shows that the sensitivity of Z index is stronger, with large amplitude of changes, while the stability of SPI is better. As a whole, SPI and Z index are similar with the actual situation. According to the analysis, the result of Z index is more close to the actual in Southwest China. According to the multi- year average, the values of Z index at Zhongdian station in Yunnan, Shiqu station and Dege station in Sichuan are at the low level, which belongs to drought area. Guizhou, Guangxi and the south of Yunnan are flooding areas. SPI and Z index are broadly consistence each year, and the drought index showed a great fluctuation after 2000. The first three rotating load vectors and their corresponding principal components are given by REOF method. Through the analysis on REOF results, the southwestern five provinces/cities are divided into four areas: western Sichuan area, eastern Sichuan (including Chongqing) area, Yunnan- Guizhou (including northern Guangxi) area, and southern Guangxi area. Z index in Yunnan-Guizhou area shows downward trend, it means that waterlogging shows a decreasing trend in this area. Severe drought occurred in western Sichuan during the period of 1964-1973, and the Z index became relatively stable since 1995, but drought occurred frequently. The variation of droughts and floods in eastern Sichuan is not significant. Z index and SPI will be reduced in the future of the five provinces in Southwest China, and Hurst exponent is greater than 0.5, that is to say, the degree of drought in southwest region may continue for a period of time. As a whole, Hurst exponent analysis shows an upward trend for droughts, and shows a weak downward trend for waterlogging.
In this paper, taking vegetation of karst area as the research site, MODIS NDVI, MODIS EVI and climatic information of 2001 to 2010 are used to analyze the relationship between vegetation and climate changes. Vapor pressure, precipitation, relative humidity, maximum temperature, minimum temperature, mean temperature, dew point, air pressure, wind speed and sunshine hours are taken as climatic variables to explore the relationship between vegetation index and climatic factors over different stages. Then, differences between NDVI and EVI in response to climate factors of karst area are analyzed. The objective is to provide references for reasonable use of vegetation index to monitor vegetation changes. The results show that: 1) There is a significant correlation between vegetation index and most climatic factors for both EVI and NDVI in karst area, yet differences between NDVI and EVI responsing to climatic factors are obvious. The correlation between EVI and climatic factors are obviously higher than that of NDVI except for sunshine hours. The correlation coefficients between NDVI and climatic factors are much higher for sunshine hours, maximum temperature, and mean temperature, their average values of correlation coefficients are 0.616, 0.535 and 0.474 respectively. While the correlation coefficients between EVI and climatic factors are much higher for vapor pressure, mean temperature and dew point, their average values of correlation coefficients are 0.857, 0.844 and 0.839 respectively. 2) There is a significant lag in the response of EVI to most climatic factors. Compared with EVI, lag is stronger for NDVI than that of EVI. The highest correlation coefficient between EVI and most climatic factors appear at the earlier stage of -1, while the highest correlation coefficient between EVI and most climatic factors appear at the earlier stage of -2. For sunshine hours and wind speed, no response lag of two vegetation indices exists. The response of two vegetation indices to climatic factors is consistent for all stations except for relative humidity, sunshine hours and wind speed.
