Terrestrial ecosystem and climate system are closely related to each other. Faced with the unavoidable global climate change, it is important to investigate terrestrial ecosystem responding to climate change. In inland river basin of arid and semi-arid regions in China, sensitivity difference of vegetation responding to climate change from 1998 to 2007 was analyzed in this paper. (1) Differences in the global spatio-temporal distribution of vegetation and climate are obvious. The vegetation change shows a slight degradation in this whole region. Degradation is more obvious in densely vegetated areas. Temperature shows a general downward trend with a linear trend coefficient of -1.1467. Conversely, precipitation shows an increasing trend with a linear trend coefficient of 0.3896. (2) About the central tendency response, there are similar features in spatial distribution of both NDVI responding to precipitation (NDVI-P) and NDVI responding to AI (NDVI-AI), which are contrary to that of NDVI responding to air temperature (NDVI-T). Typical sensitivity region of NDVI-P and NDVI-AI mainly covers the northern temperate arid steppe and the northern temperate desert steppe. NDVI-T typical sensitivity region mainly covers the northern temperate desert steppe. (3) Regarding the fluctuation amplitude response, NDVI-T is dominated by the lower sensitivity, typical regions of the warm temperate shrubby, selui-shrubby, bare extreme dry desert, and northern temperate meadow steppe in the east and temperate semi-shrubby, dwarf arboreous desert in the north are high response. (4) Fluctuation amplitude responses between NDVI-P and NDVI-AI present a similar spatial distribution. The typical sensitivity region mainly covers the northern temperate desert steppe. There are various linear change trend responses of NDVI-T, NDVI-P and NDVI-AI. As to the NDVI-T and NDVI-AI, which are influenced by the boundary effect of semi-arid and semi-humid climate zones, there is less correlation of their linear change tendency along the border. There is stronger correlation in other regions, especially in the NDVI-T in the northern temperate desert steppe and NDVI-AI in the warm temperate shrubby, selui-shrubby, bare, extreme and dry desert.
Land surface emissivity is one of the important parameters in temperature inversion from thermal infrared remote sensing. Using MOD11C3 of Terra-MODIS L3 level products, spatio-temporal data sets of land surface emissivity in China for 10 years from 2001 to 2010 are obtained. The results show that the land surface emissivity in the northwest desert region is the lowest in China, with little seasonal variations. In contrast, there are significant seasonal variations in land surface emissivity in northeast China and northern Xinjiang, the Qinghai- Tibet Plateau, the Yangtze River Valley and the eastern and southern China. In winter, the land surface emissivity in the northeast China and northern Xinjiang is relatively high. The land surface emissivity of the Qinghai-Tibet Plateau region is maintained at low value from November to March, while it becomes higher in other months. The land surface emissivity of the Yangtze River Valley, eastern and southern China, and Sichuan Basin varies from July to October, and peaks in August. Land surface emissivity values could be divided into five levels: low emissivity (0.6163-0.9638), moderate-low emissivity (0.9639-0.9709), moderate emissivity (0.9710-0.9724), moderate-high emissivity (0.9725-0.9738), and high emissivity (0.9739-0.9999). The percentages of areas with low emissivity, moderate-low emissivity and moderate emissivity are, respectively, about 20%, 10% and 20%. The moderate-high emissivity region makes up 40%-50% of China's land surface area. The inter-annual variation of moderate-high emissivity region is also very clear, with two peaks (in spring and autumn) and two troughs (in summer and winter). The inter-annual variation of the high emissivity region is very significant, with a peak in winter (10%), while only 1% or 2% in other seasons. There is a clear association between the spatio-temporal distribution of China's land surface emissivity and temperature: the higher the emissivity, the lower the temperature, and vice versa. Emissivity is an inherent property of any object, but the precise value of its emissivity depends very much on its surrounding environmental factors.
A total of 12 indices of temperature extremes and 11 indices of precipitation extremes at 111 stations in southwestern China at altitudes of 285-4700 m were examined for the period 1961-2008. Significant correlations of temperature extremes and elevation included the trends of diurnal temperature range, frost days, ice days, cold night frequency and cold day frequency. Regional trends of growing season length, warm night frequency, coldest night and warmest night displayed a statistically significant positive correlation with altitude. These characteristics indicated the obvious warming with altitude. For precipitation extreme indices, only the trends of consecutive dry days, consecutive wet days, wet day precipitation and the number of heavy precipitation days had significant correlations with increasing altitude owing to the complex influence of atmospheric circulation. It also indicated the increased precipitation mainly at higher altitude areas, whereas the increase of extreme precipitation events mainly at lowers altitude. In addition, the clearly local influences are also crucial on climate extremes. The analysis revealed an enhanced sensitivity of climate extremes to elevation in southwestern China in the context of recent warming.
This study examines the hydrological and meteorological data of the source region of the Yellow River from 1956 to 2010 and future climate scenarios from regional climate model (PRECIS) during 2010-2020. Through analyzing the flow variations and revealing the climate causes, it predicts the variation trend for future flows. It is found that the annual mean flow showed a decreasing trend in recent 50 years in the source region of the Yellow River with quasi-periods of 5a, 8a, 15a, 22a and 42a; the weakened South China Sea summer monsoon induced precipitation decrease, as well as evaporation increase and frozen soil degeneration in the scenario of global warming are the climate factors, which have caused flow decrease. Based on the regional climate model PRECIS prediction, the flows in the source region of the Yellow River are likely to decrease generally in the next 20 years.
Based on the data of eight meteorological stations from the 1950s to 2007, current cropping patterns, field water moisture management, we use the Mann-Kendall and the Rescaled Range Analysis methods to research the changes of humidity and crop irrigation water requirements in the Lancang River Basin. The results show that the annual and dry season average temperatures significantly increased, and the dry season rainfall increased while wet season rainfall decreased. Evaportranspiration (ET0) increased during both dry and wet seasons at all stations except Dali, Jianchuan and Gengma, and the aridity-humidity index decreased at most of the stations. The turning points of weather factors, ET0, the aridity- humidity index, paddy irrigation requirements and total agricultural water requirements occurred from the 1960s to the 1990s. The spatial changing tendency of paddy irrigation quota increased with the increase of altitude and latitude, and the correlation coefficients are 0.513 and 0.610, respectively. The maximum value is observed in Weixi, while the minimum in Mengla.
In this study, a monthly dataset of temperature time series (1961-2010) from 12 meteorological stations across the Three-River Headwater Region of Qinghai Province (THRHR) was used to analyze the climate change. The temperature variation and abrupt change analysis were examined by using moving average, linear regression, Spline interpolation, Mann-Kendall test and so on. Some important conclusions were obtained from this research, which mainly contained four aspects as follows. (1) There were several cold and warm fluctuations for the annual and seasonal average temperature in the THRHR and its three sub-headwater regions, but the temperature in these regions all had an obviously rising trend at the statistical significance level, especially after 2001. The spring, summer, autumn and annual average temperature increased evidently after the 1990s, and the winter average temperature exhibited an obvious upward trend after entering the 21st century. Except the standard value of spring temperature, the annual and seasonal temperature standard value in the THRHR and its three sub-headwater regions increased gradually, and the upward trend for the standard value of winter average temperature indicated significantly. (2) The tendency rate of annual average temperature in the THRHR was 0.36℃10a-1, while the tendency rates in the Yellow River Headwater Region (YERHR), Lancangjiang River Headwater Region (LARHR) and Yangtze River Headwater Region (YARHR) were 0.37℃10a-1, 0.37℃10a-1 and 0.34℃10a-1 respectively. The temperature increased significantly in the south of Yushu County and the north of Nangqian County. The rising trends of temperature in winter and autumn were higher than the upward trends in spring and summer. (3) The abrupt changes of annual, summer, autumn and winter average temperature were found in the THRHR, LARHR and YARHR, and were detected for the summer and autumn average temperature in the YERHR. The abrupt changes of annual and summer average temperatures were mainly in the late 1990s, while the abrupt changes of autumn and winter average temperatures appeared primarily in the early 1990s and the early 21st century respectively. (4) With the global warming, the diversities of altitude and underlying surface in different parts of the Tibetan Plateau were possibly the main reasons for the high increasing rate of temperature in the THRHR.
Palaeo-hydrological field investigation was carried out in the middle reaches of the Jinghe River. A set of palaeoflood slackwater deposit beds was identified in the Holocene loess-soil sequence in the riverbanks. The sediment samples were collected from the profile, and the particle-size distribution, magnetic susceptibility, loss-on-ignition were analyzed in laboratory. The analytical results showed that the palaeoflood slackwater deposits have recorded extraordinary flood events in the Jinghe River valley. According to stratigraphic correlation and OSL dating, the palaeoflood events were dated to 4100-4000 a BP. The palaeoflood peak discharges were estimated to be 19,410-22,280 m3/s by using the hydrological model and checked by different approaches. These results have the flood data sequence of the Jinghe River extended to 10,000-year time-scale. It provided significant data for hydraulic engineering and for mitigation of flood hazards in the Jinghe River drainage basin.
Based on the analysis of ion chemical composition of lake water and shallow groundwater in the Badain Jaran Desert, this paper discussed the characteristics of ion chemical composition, spatial variation of lake water, and possible supply sources of lake water and groundwater in the desert areas. The results show that the pH, salinity, TDS and electrical conductivity of the lake water are greater than those of groundwater. The ion contents of water samples are dominated by Na+ and Cl-. Most of the higher salinity lakes are Na (K)-Cl-(SO4) type, and a few of low salinity lakes belong to the Na-(Mg)-(Ca)-Cl-(SO4)-(HCO3) type. Most of the groundwater is Na-(Ca)-(Mg)-Cl-(SO4)-(HCO3) type, attributed to subsaline lake, and only a few present the Na-Cl-SO4 type, flowing under saline lake. The pH, salinity, TDS and electrical conductivity in the southeastern lakes are relatively low, and there are slightly alkaline lakes. The pH, salinity, TDS and electrical conductivity in the northern lakes are much greater than those of the southeastern lakes, and the northern lakes are moderately alkaline and saline ones. In the southeastern part of the Badain Jaran Desert, the ion chemical characteristics of the lake water from south to north show a changing trend of subsaline →saline→hypersaline. The changing trend of chemical compositions of ions in recent 9 years indicates that most of the ion contents have a shade of reduction in Boritaolegai, Badain, Nuoertu and Huhejilin lakes, which state clearly that the amount of fresh water supply is increasing in the 9-year period. The ion chemical composition of the lake water reveals that the flow direction of lake water is from southeast to northwest in the Badain Jaran Desert. The ion chemical composition, moisture content of sand layer water level height and hierarchical cluster analysis of the lake water and groundwater demonstrate that the lake water is mainly supplied by local rainfall and infiltration of precipitation in Yabulai Mountains and Heishantou Mountain, and the supply from the Qilian Mountains is almost impossible.
Physical geography and human geography are the principal branches of the geographical sciences. Physical process simulation and human process simulation in geography are both quantitative methods used to recover past events and even to forecast events based on precisely determined parameters. There are four differences between physical process simulation and human process simulation in geography, which we summarize with two specific cases, one of which is about a typhoon's development and its precipitation, and the other of which is regarding the evolution of three industrial structures in China. The differences focus on four aspects: the main factors of the research framework; the knowledge background of the systematic analysis framework; the simulation data sources and quantitative method; and the core of the study object and the method of forecast application. As the human- land relationship is the key ideology of the man-land system, the relationship between the physical and human factors is becoming increasingly close at present. Physical process simulation and human process simulation in geography will exhibit crossing and blending in the future to reflect the various geographical phenomena better.
Employing DEA model and Malmquist productivity index, this paper probes into the urban efficiencies of 24 typical resources-based cities in China and their changes from 2000 to 2008. The research finds that the overall efficiencies of the resources-based cities are just at a general level, and only a few of them reach the optimal level. The scale efficiency is the major determining factor of the achievement of overall efficiency, the effect of which, nevertheless, is reducing. From the perspective of classification characteristics, the resources- based cities in northeastern region have been in the front rank in terms of overall efficiency, pure technical efficiency and scale efficiency. There is a certain positive correlation between urban population scale and urban efficiency. The analysis of urban efficiency changes shows that the changes in overall efficiency of resources-based cities from 2000 to 2008 had a weak improving tendency. Both the technical change index and productivity change index decreased, indicating that the urban efficiency did not improve during this period, and the tendency of technical recession and productivity decline was obvious. In terms of the classification of urban efficiency changes, the urban overall efficiency improved in each of the four regions from 2000 to 2008, among which western region witnessed the greatest increase. Cities with different resource types have improved their urban overall efficiencies except steel-based cities. The urban overall efficiency increased in resources-based cities of different scales, with greater improvement in small and medium-sized cities than in big cities.
Urban agglomeration on Yangtze River Delta (UA-YRD) had some advantages in the aspects of water, land, ecological environment, location and transportation. Relying on the resource-environment bases and other advantages, UA-YRD has achieved great development. Based on index system and model of comprehensive evaluation, the paper calculates the development level of UA-YRD since 1978. The result shows that from 1978 to 2007, the development level increased year by year at an annual rate of 0.0333, and the process of development could be divided into three stages, i.e. low-speed development stage (1978-1991), rapid development stage (1991-2000), and high-speed development stage (2000-2007). The speeds are 0.0083, 0.0356 and 0.0766, respectively. During the 30-year development, foreign economic activity has the greatest effect on development, followed by transportation, industrial economic activity and telecommunication (in order). Additionally, different driving forces have different effects in different stages. The paper suggests that more attention should be paid to the high-speed development stage and the important driving forces to drive its development. At the same time, the limitation of resource and environment should not be neglected and a long effective mechanism needs to be established to sustain harmonious development among the UA development, resource utilization and environmental protection. Some comparative studies should be carried out urgently to support and promote sustainable development of UA effectively, especially towards evolution, driving forces and braking forces.
The impervious surface area (ISA) at the regional scale is one of the important environmental factors for examining the interaction and mechanism of Land Use/Cover Change (LUCC)-ecosystem processes-climate change under the interactions of urbanization and global environmental change. Timely and accurate extraction of ISA from remotely sensed data at the regional scale is challenging. This study explored the ISA extraction based on MODIS and DMSP-OLS data and the incorporation of China's land use/cover data. ISA datasets in Beijing-Tianjin-Tangshan Metropolitan Area (BTTMA) in 2000 and 2008 at a spatial resolution of 250 m were developed, their spatiotemporal changes were analyzed, and their impacts on water quality were then evaluated. The results indicated that ISA in BTTMA increased rapidly along urban fringe, transportation corridors and coastal belt both in intensity and extents from 2000 to 2008. Three cities (Tangshan, Langfang and Qinhuangdao) in Hebei Province had higher ISA growth rates than Beijing due to the pressure of population-resources- environments in the city resulting in increasingly transferring industries to the nearby areas. The dense ISA distribution in BTTMA has serious impacts on water quality in the Haihe River watershed. Meanwhile, the proportion of ISA in sub-watersheds has significantly linear relationships with the densities of river COD and NH3-N.
Land use transition refers to the changes in land use morphology (both dominant morphology and recessive morphology) of a certain region over a certain period of time driven by socio-economic change and innovation, and it usually corresponds to the transition of socio-economic development phase. In China, farmland and rural housing land are the two major sources of land use transition. This paper analyzes the spatio-temporal coupling characteristics of farmland and rural housing land transition in China, using high-resolution Landsat TM (Thematic Mapper) data in 2000 and 2008, and the data from the Ministry of Land and Resources of China. The outcomes indicated that: (1) during 2000-2008, the correlation coefficient of farmland vs. rural housing land change is -0.921, and it shows that the change pattern of farmland and rural housing land is uncoordinated; (2) the result of Spearman rank correlation analysis shows that rural housing land change has played a major role in the mutual transformation of farmland and rural housing land; and (3) it shows a high-degree spatial coupling between farmland and rural housing land change in southeast China during 2000-2008. In general, farmland and rural housing land transition in China is driven by socio-economic, bio-physical and managerial three-dimensional driving factors through the interactions among rural population, farmland and rural housing land. However, the spatio-temporal coupling phenomenon and mechanism of farmland and rural housing land transition in China are largely due to the “dual-track” structure of rural-urban development.
Taking Yucheng, a typical agricultural county in Shandong Province as a case, this study applied Logistic regression models to spatially identify factors affecting farmland changes. Using two phases of high resolution imageries in 2001 and 2009, the study obtained the land use and farmland change data in 2001-2009. It was found that the farmland was reduced by 5.14% in the period, mainly due to the farmland conversion to forest land and built-up land, although part of forest land and unused land was converted to farmland. The results of Logistic regressions indicated that location, population growth and farmer income were main factors affecting the farmland conversion, while soil types and pro-curvature were main natural factors controlling the distribution of farmland changes. Regional differences and temporal-spatial variables of farmland changes affected fitting capability of the Logistic regression models. The ROC fitting test indicated that the Logistic regression models gave a good explanation of the regional land-use changes. Logistic regression analysis is a good tool to identify major factors affecting land use change by quantifying the contribution of each factor.
This book, written by Tian-Xiang Yue, on surface modelling, was published by CRC Press. It consists of 20 chapters. Chapter 1 reviews the existing classical methods for surface modeling and analyzes their shortcomings.
Land system change has never been out of human concerns. It is always one of the hottest themes in global environmental change research (Seto et al., 2002; Gutman et al., 2004).
