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Eco‐efficiency is an important indicator which serves as a helpful instrument for the studies of sustainable development. This paper estimated the eco‐efficiency of 26 cities in China's Yangtze River Delta urban agglomerations. Based on different matrixes, Moran's I was applied to analyze the spatial correlation. The spatial Durbin model was applied to analyze the direct and indirect effect of influencing factors. Some conclusions were drawn. (a) The average eco‐efficiency showed an increasing trend. The regional difference of eco‐efficiency decreased and then increased. Shanghai's eco‐efficiency had been the highest. (b) The eco‐efficiency showed positive spatial autocorrelation and it also exhibited significant characteristic of local spatial autocorrelation. (c) Economic development, fixed assets investment, and technological level of one city had a significant positive impact on the eco‐efficiency of the city itself. Industrial structure, fiscal decentralization, and foreign direct investment of a city had a significant negative impact on the eco‐efficiency of the city itself. Changes in the economic development and technological levels in a city had positive impacts on the eco‐efficiency of its neighboring cities. Foreign direct investment had a negative spatial spillover effect. (d) This paper suggested that it is necessary to pay attention to the interaction of influencing factors among cities. [ABSTRACT FROM AUTHOR]

This article introduces measures to quantify spatial autocorrelation for vectors. In contrast to scalar variables, spatial autocorrelation for vectors involves an assessment of both direction and magnitude in space. Extending conventional approaches, measures of global and local spatial associations for vectors are proposed, and the associated statistical properties and significance testing are discussed. The new measures are applied to study the spatial association of taxi movements in the city of Shanghai. Complications due to the edge effect are also examined. [ABSTRACT FROM AUTHOR]

The integrated application of remote sensing, geographic information system and quantitative analytical modeling can provide scientific and effective methods for monitoring and studying urban heat island, based on land surface temperature (LST) retrieved from thermal infrared channel data of sensors. In this paper, LST is retrieved from Landsat TM6 and ETM + 6 data of Shanghai central city in 1989, 1997, 2000 and 2002, by using the mono-window algorithm. Based on the data, global and local spatial autocorrelation analysis, and geostatistical methods are adopted to quantitatively describe the characteristics of spatial heterogeneity and temporal evolution of land surface thermal landscape at different scales and periods in Shanghai central city, by utilizing exploratory spatial data analysis. Results show that LST field in Shanghai central city tends to fragmentize and complicate with the development of Shanghai, and its global spatial difference becomes greater gradually. The spatial variance pattern of the change of LST field from 1997 to 2002 indicates that the dynamic change of LST presents a tendency of increase in circularity. LST declines distinctly in the districts of Puxi and Pudong near and inside the inner ring road, while it rises obviously outside the central city and near the out ring road. The extrema of temporal change in LST field have a characteristic of spatial clustering. Besides, as the city of Shanghai expands in a circular pattern as a whole, the directional difference of dynamic change of urban surface thermal landscape exists but is not very obvious. [ABSTRACT FROM AUTHOR]