城市滨水区两岸均衡度发展量化评估模型研究

Quantitative Evaluation Model of Balanced Development at Two Sides of an Urban Waterfront Area

在快速城镇化向稳定城镇化换挡、工业化中期向后期发展的阶段,城市滨水区两岸的均衡度发展日渐受到城市研究者重视,但当前从宏观角度出发针对此议题的研究难以全面精准地测度两岸均衡度发展状况,为响应这一情况,基于高德API计算更精准的等时圈范围,整合新数据与新技术方法,以上海、广州、武汉、宁波四个城市为例,结合与滨水区两岸均衡度发展相关的Po I数量与多样性、基于LBS数据的人口密度、步行出行可达性、机动车出行可达性等社会经济系统指标,以及腹地范围和形态指数、开发强度、路网密度等物质空间指标,再利用AHP层次分析法对上述指标进行权重计算,最后结合岸线形态构建基于多源数据的滨水区两岸均衡度发展情况量化评估模型,为精细化的滨水区城市设计实践提供有力支持。

Owing to the transition from fast urbanization to stable urbanization,the renewal and development of urban waterfront areas,which are considered to be representative of urban vitality have become an important part of urban planning and development.At present,the urban sprawl of waterfront areas in many cities globally has experienced rapid expansion on both sides of rivers.Thus,the integrated development of urban waterfronts has become a significant issue and has attracted more and more research attention.Most studies on waterfront areas primarily focus on transportation,public spaces,industrial development,or natural ecology from the perspective of planning,both social and economic.However,current research has found it difficult to measure the integrated development of urban waterfront areas comprehensively and accurately.The evolution of the comprehensive value of urban areas and the integrated development of urban waterfront areas both require the consideration of multiple elements within the physical space and the social system.Therefore,a comprehensive quantitative index system is of more exploratory value for waterfront development evaluation for synergistic and balanced urban development.The emergence of big data environments and digital technologies provide new opportunities for researchers to understand the public space in urban waterfront areas.Many forms of data,including POI data,mobile phone data,space syntax analysis,and multi-agent pedestrian flow simulation have been widely used in waterfront public space surveys.However,the current use of data is often limited to a specific group or spatial feature.The use of multidimensional data for integrated analyses is still relatively rare.Thus,this research used multi-source data to propose a comprehensive integrated development model for the analysis of waterfront areas.The methods of scope definition,key indicator selection,and waterfront integration evaluation are all applied to finally construct a qualitative model for evaluating the integrated development of urban waterfront areas,which provides support to urban design practices in waterfront areas.The concept of an isochron is introduced to define the study area herein.The navigation route calculation function in the Gaode platform was used to calculate the 15-min and the 30-min isochrons,which are accessible by taking a bus or by walking from the waterfront to other places in the city.Subsequently,multisource data including POI,LBS,and road network data were collected,and the environment data inside isochrones were built.The number of POIs,the population density based on LBS data,and traveling potential from the data were extracted as socioeconomic indicators,while the scope and shape index,development intensity,and road network density were calculated as physical space indicators.The analytic hierarchy process(AHP)was applied to calculate the weights of the abovementioned indicators to determine the waterfront integration degree(WID).Next,WID was combined with the shape index of the shoreline to help formulate a qualitative evaluation model.The integrated development degrees of Shanghai,Guangzhou,Wuhan,and Ningbo in 15-min and 30-min isochrone areas were calculated.During the assessment of the 15-min isochronous area,the WID and the development gap between the two sides of the river in Shanghai and Wuhan were relatively low.In comparison,Guangzhou and Ningbo exhibited higher WIDs and smaller development gaps between the two sides of the river.For the 30-min isochronous area,the WIDs of four cities were improved.Among them,the WID of Shanghai was improved the most,which was consistent with its first-tier city level and the large width of the Huangpu River.In general,Ningbo and Guangzhou maintained a higher WID than the two other cities,accompanied by a relatively even distribution of integrated development.In contrast,the development of the waterfront in Shanghai exhibited an extremely uneven trend,manifesting in a high score in hinterlands,but a low score in the riverside area.Among the four cities,the WIDs of the core waterfront area in Wuhan were the lowest in each range.The urban space distribution varies significantly,with poor accessibility,weak diversity,and low development intensity.The results show that the waterfront integration development index can effectively and quantitatively evaluate the development at the two sides of the waterfront and in the hinterland.The isochronous area obtained by the actual navigation route can measure the accessibility of the urban waterfront more accurately.Moreover,this study established a quantitative evaluation system by integrating new analysis tools(including Python,Mapbox,Arc GIS,and s DNA)with POI,LBS,road network,and built environment data.This proves the possibility of using multi-source big data and new analysis tools to measure the"unmeasurable"aspect of traditional studies on urban development.In addition,the proposed analytical framework not only provides strong analysis support for the practical urban design of waterfront areas,but can also be used in many other fields,such as urban function composite degree evaluation,urban vitality assessment,urban spatial accessibility measurement,and spatial quality assessment.Moreover,it can be applied to the practical design of master planning,regulatory planning,and special planning,which is conducive to refining urban designs.