Research On The Differentiation And Optimization Of Green Space Perception Of Streets Of Fang City In Shenyang Based On Green View Index

As China’s urbanization mode gradually shifts from speed to quality,residents’psychological perception and mental health in cities are gradually valued in urban design.Admittedly,greening of urban public space quality on people have experience in it cannot ignore the direct impact,however due to the limitations of the measurement and the subjective feeling of the restriction of the measure itself(for example,most of the research is based on the level of urban greening overhead data,but this is often the perception of green and public view do not exactly match)even if the streets and Green view index provides new train of thought,its impact on the public perception of quantitative has not reached a consensus.The new computer technology and its application in urban planning provide the possibility to realize this goal.In this study,the public perception analysis of the Green view index in the green space of old urban streets is taken as the research direction,and the correlation between the Green view index and spatial perception as well as the green construction and renewal strategy of urban space are studied and expounded by using the image recognition data of Baidu street view.Around Shenyang to the urban design of micro step in street green space is the research content,from Green view index and other green space elements level each other city within the scope of the 41 street green space characteristics of comb summary,and from the perspective of the five samples of street green space and green rate by fine collection and analysis of distribution features of induction Angle of different levels of street green space and green rate data distribution.Using typical street view images from content planting level and planting form factors and is surrounded degree and green rate,open degree,complexity,engagement Angle of street space influence factors such as combining the public perception of typical street view image evaluation data survey and statistics for street view nodes for typical statistics and quantitative analysis and summarizing different groups for different functional properties and characteristics of street space and Green view index of green space differentiation characteristics of feel.Using neural network analysis of the sample rate of green space and green learning outcomes for all the public perception of street green space research,combined with the characteristics and difficulties of green space construction and update from space at different features and different audience levels on the street green space and Green view index distribution and improve demand put forward the corresponding optimization strategy,discover the old city greening design in micro update strategy,guide the urban space quality of fine update and run,to coordinate the urban design of micro intervention,improving the quality of street material environment,the construction of more beautiful and conform to the public expects living environment provides the basis.