The relation between city and ecological environment forms in the coupling process of urban systems and environmental factors, in which there is a definite rule. Urban competitiveness embodies the evolvement and development of the city, using the dissipative structure principle and mathematical analysis, this paper probes into the coupling rule between urban competitiveness and ecological environment. It is indicated that the amicability degree of human environmental behavior determines the shape of environmental Kuznets curve, the human amicable behavior and technological progress are significant for coordinating the city development and improving the urban competitiveness.

With the development of global changes, researchers from all over the world attach attention to land use changes increasingly, and large scale land use changes which have resulted from urban expansion catch people’s eyes. In this paper, urban expansion and their spatial and temporal variability of the Beijing city has been studied over a period of 21 years (1984–2005) via statistical classification approaches based on the remotely sensed images obtained from sensors both Landsat TM5 and SPOT4. The research method includes three parts: First, using multi-temporal images, land use/land cover change is detected by means of remote sensing. Then, based on result of classification images, the process of land use/land cover change and the model of urban expansion are analyzed by GIS technologies. It includes markov and transfer matrix, trajectories analysis, the spatial distribution rules of urban land and the spatial distribution rules of urban expansion intensity. Concretely, these include Markov and transitional probabilities matrix and the spatial distribution rules of urban land and urban expansion intensity. Finally, the relationship of population, GDP and urban land area are built up through a linear regression analysis. Research shows that: 1) Land use/land cover change detection using multitemporal images by means of remote sensing and ration research of model of urban expansion by GIS are good means of research of urban expansion. 2) Research of time sequence land use / land cover change through analysis of urban expansion trajectories and index reveals of urban distribution rules in terms of spatial-temporal. 3) Combined the analysis of social economic data, the simulation of expansion urban land is given in amount. 1.

Abstract: Over the past 10 years, the rapid urbanization in China has brought profound impact on China economy and society, and had certain influence on urban micro-climate. Taking Jinan city as an example, based on the model about the relation between the urban development and urban climate change, the trend of Jinan temperature and precipitation are analyzed, the relative impact between the urban climate and the urban development is studied. The results show that there are noticeable Heat Island Effect and Rain Island Effect in Jinan, the impact on the urban climate change caused by the urban development could not precisely match the Kuznets Curve in Jinan.

variability Abstract. A total of 2668 surface soil samples (-0.5 m ~ 0 m) and 637 sub-layer soil samples (-1.0 m ~-0.5 m) were collected from a contaminated site with an area of 26.19 hectares and analyzed the concentration of arsenic, so as to get the spatial distribution of arsenic concentrations in the soil contaminated by highly toxic As-chemicals. The results indicated that spatial correlation of arsenic content in surface soil was moderate. The optimal semivariogram model was the exponential model, and the best interpolation model was simple Kriging interpolation. The arsenic content of sub-layer was similar to that of surface soil in space structure, but weakly correlated. Analysis on the arsenic content in vertical sections showed that contamination was mainly concentrated in surface soil. The arsenic content in most of the collected samples reduced as the soil layer depth increased. Spatial variability of arsenic could be significantly affected by anthropogenic factors such as excavation & destruction of highly toxic As-chemicals and farming.