a b s t r a c tThe national ecological footprint of both consumption and production are significantly spatially autocorrelated at global level. This violates the assumption of independently distributed errors of most conventional estimation techniques. Using a spatial econometric approach, this paper re-examine the relationship between economic growth and environmental impact for indicator of ecological footprint. The results do not show evidence of inverted U-shape Environmental Kuznets Curve. The domestic ecological footprint of consumption (or production) was obviously influenced by the ecological footprint of consumption (or production), income and biocapacity in neighborhood countries. We also found that the consumption footprint is more sensitive to domestic income, while production footprint is more sensitive to domestic biocapacity, which is often unnoticed in EKC hypothesis analyses that focus exclusively on the consumption-based or production-based indictors.
Remote sensing image classification is an important and complex problem. Conventional remote sensing image classification methods are mostly based on Bayesian subjective probability theory, but there are many defects for its uncertainty. This paper firstly introduces evidence theory and decision tree method. Then it emphatically introduces the function of support degree that evidence theory is used on pattern recognition. Combining the D-S evidence theory with the decision tree algorithm, a D-S evidence theory decision tree method is proposed, where the support degree function is the tie. The method is used to classify the classes, such as water, urban land and green land with the exclusive spectral feature parameters as input values, and produce three classification images of support degree. Then proper threshold value is chosen and according image is handled with the method of binarization. Then overlay handling is done with these images according to the type of classifications, finally the initial result is obtained. Then further accuracy assessment will be done. If initial classification accuracy is unfit for the requirement, reclassification for images with support degree of less than threshold is conducted until final classification meets the accuracy requirements. Compared to Bayesian classification, main advantages of this method are that it can perform reclassification and reach a very high accuracy. This method is finally used to classify the land use of Yantai Economic and Technological Development Zone to four classes such as urban land, green land and water, and effectively support the classification.
a b s t r a c tThe wetlands of the Yellow River delta play important roles for Asian and west Pacific birds during migration. Marshes are the main component of wetlands in the delta, and their coverage area has experienced a decreasing trend for the last few decades. Wetland changes in the Yellow River delta have been analyzed in previous studies; however, those studies only partially analyzed the causes of the decline. Using statistical and spatial analysis based on observational data and remote sensing imagery for the period of 1986-2005, we found that the annual mean temperature and annual precipitation tended to increase, and the evapotranspiration and the moisture index tended to decrease. Consequently, these climate factors led to a significant decrease in river runoff, which resulted in decreased water supply for the marshes in the delta. A Wetland Restoration Project was launched in 1992, and it successfully conserved marshes within a relatively small area. However, the inadequate water supply still resulted in an overall decrease in marsh area over the entire study area. These results provide more insights into managing wetlands eco-restoration.
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