Study on the Spatial and Temporal Characteristics and Influencing Factors of Vitality of Urban Waterfront Parks:A Case Study Based on Kunming City
Waterfront parks are an essential part of urban blue spaces.Improving the vitality of waterfront parks is crucial to constructing livable cities.The study analyzed the spatial and temporal features of the vitality of 24 typical waterfront parks in Kunming City in different periods and relevant influencing factors using mobile phone signaling data.Vitality kurtosis and skewness were proposed based on existing studies to analyze spatial and temporal distribution features of the vitality of waterfront parks in different periods.Additionally,the relationship between the built environment of waterfront parks and vitality was discussed in depth,and the spatial and temporal features of vitality were disclosed through a quantitative study.The key influencing factors of service,traffic and landscape as well as their interactions were further analyzed.The results show that:(1)concerning temporal distribution,the vitality of waterfront parks in Kunming is characteristic of a"valley in morning and evening,but peak in afternoon."The vitality peak occurs in the afternoon,but the vitality peak during workdays(after 17:00)is later than on non-workdays(after 15:00).Vitality on all days presents a general trend of steady,rising,and decreasing.The vitality of waterfront parks concentrates obviously on workdays,with prominent peaks.The vitality peak on non-workdays disperses and is relatively balanced.(2)Regarding spatial distribution,the vitality of waterfront parks is characteristic of"high in the north,low in the south and concentrating in east."The east bank areas are close to the main urban area and have high traffic accessibility.Waterfront parks with high vitality mainly focus on the northeast bank areas of Dian Lake.The road network density on the west bank of Dian Lake is low,and the waterfront parks are large in scale.However,the overall comprehensive vitality is relatively low.There is some mismatch between the level scale and the vitality of waterfront parks.(3)The function integration of various facility types within 1,000 m of waterfront parks is a common factor that influences vitality in different periods.The road network density of 500 m and number of bus stations have significant influences on workdays,while the distance to the CBD and water area have significant influences on non-workdays.The vitality of waterfront parks is influenced by multidimensional factors.Landscape dimensions have more significance than other dimensions.On this basis,some optimization suggestions to further improve the vitality of waterfront parks in Kunming City were proposed.For function perfection,the opening of waterfront parks shall be prolonged according to temporal distribution features of vitality to improve utilization of waterfront parks.For spatial coordination,the empirical study has discovered the imbalanced resource allocation of waterfront parks surrounding Dian Lake,resulting in the spatial distribution pattern of"high in the north,low in the south and concentrating in east."Hence,it is necessary to strengthen planning guidance and formulate scientific and reasonable greenway construction planning.For facility configuration,the function integration of service facilities and traffic accessibility significantly influence the vitality of waterfront parks in different periods.Therefore,attention should be paid to the differential allocation of facilities in waterfront parks and improving function integrity and traffic convenience.For landscape improvement,the water area is a key factor in improving the vitality of waterfront parks on non-workdays and interacts significantly with other factors.Hence,making full use of a combination of natural landscapes,facility construction,and creating rich spatial levels and landscape effects through vegetation and terrain construction will improve the landscape benefits of waterfront parks.
waterfront parkspatial and temporal characteristics of vitalityinfluencing factorsKunming
国家科技期刊平台
NSTL
万方数据
