Abstract

Abstract- The availability of attractive green spaces is an integral part of urban quality of life. But the traditional methods of evaluating the level of green spaces shared by urban dwellers have some disadvantages. They are as follows: (1) Area of green spaces is always taken as an only indicator so that the importance of green gross inside the green space is ignored. (2) The spatial scale of the indicators is so macro that the micro- spatial pattern of the green spaces can’t be reflected. (3) Evaluation of green spaces’ system generally depends on the total area of green spaces. But other constraint factors are not taken into account. Keeping the limitation above in mind, this paper adopts a new approach for calculating the green spaces’ qualities then tries to design a new model as to how green spaces attract citizens in the neighborhood with the help of RS&GIS technology. The green gross is equal to the sum of vegetation fractions derived from Thematic Mapper images of the green space. The model is based on the theory of spatial interaction. The meanings of all the parameters are as follows: The attractiveness is in direct ratio with the green spaces’ qualities while in inverse ratio with the exponential distance. Furthermore, the model also considers several restriction factors such as the accessibility, entrance fees, quietness, spaciousness and so on. The weights are given by simulation of Hopfield neuron network. At last the approaches and model above are applied into the city of Shanghai in China. Taking the green spaces of parks inside the outer ring road as the study sample, the results are in accord with the actual spatial characteristic satisfactorily. The model is made operational easily, which can not only monitor space-time variety of urban green space, but also provide a new indicator for urban green space system planning.

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