摘要
在城市不断发展与扩展的同时,许多建成区可能会出现空置,表现为人口、企业稀少,生产水平严重低下,对城市空置区域的评估能够反映当前城市内部各区域发展状况,能够作为城市改造更新的依据。本文提出了一个以空置指数来量化评估城市内部层面空置现象,并对其影响因素进行探究的方法。根据"空城"的外在特征:建筑水平与社会活动水平,空置指数通过较高分辨率夜光遥感影像(Luojia1-01)和土地覆盖信息得到;同时依据城市空间活力营造原则,通过社会感知数据与路网数据量化产生空置现象的内在影响因素;并通过随机森林模型对空置指数精细化以及对影响因素重要性排序。以武汉市城区为例,用该方法对空置指数可视化,可识别出空置现象严重的区域,主要为老旧城区、工厂库房、单一功能的公共设施区域等,同时道路的可达性与人流密度对空置现象影响较大,且建立的随机森林模型精度R^2可达84.6%,对空置指数通过随机森林拟合后,其可视化分辨率由130 m优化至25 m。本研究结果可为城市中空置现象的改进提供依据。
With the rapid construction of urban areas,it is necessary to make assessment of the built-up areas.As the city develops and expands,many of the build-up areas may show the phenomenon of vacancy with a small population,few businesses,and seriously low productivity.It is a serious obstacle to urban development and leads to the decrease of street vitality.In order to promote the healthy development of cities,it is necessary to evaluate the existing phenomenon of vacancy in cities.This paper proposes a method to quantify and evaluate the phenomenon of vacancy at the city block level with avacancy index,as well as investigate its influencing factors.Firstly,a vacancy index is determined by the characteristics of a vacant town based on nighttime light data and land cover information.The nighttime light data of Luojia-1A satellite whose resolution is higher than DMSP-OLS and NPP-VIIR,reflect the intensity of nocturnal activity.In SAR interferometry,coherence is the criteria of phase stability.Stabilized objects in urban areas can be identified as buildings according to the coherence,which shows the external characteristics of vacant towns.By visualizing the vacancy index in the study area,failed construction in urban areas can be identified.Then,based on classical urban design theories on spatial vitality promotion,a series of factors of urban vitality are summarized as the internal influencing factors of the vacancy phenomenon,including the distance to the street,integration,choice,the crowd density,function of street-block,mixture of primary use,and mixture of building ages.These internal influencing factors of the vacancy phenomenon are quantified by social sensing data and road information.Lastly,the extrinsic and intrinsic features of vacancy are combined,a Random Forest model is employed to refine the vacancy index and rank the importance of the influencing factors.We use the urban area of Wuhan as a case study.Wuhan develops and expands fast in recent years.The areas with severe vacancy can be identified by visu
作者
杨建思
柳帅
王艳东
廖明生
YANG Jiansi;LIU Shuai;WANG Yandong;LIAO Mingsheng(School of Urban Design,Wuhan University,Wuhan 430072,China;State Key Laboratory of Information Engineering in Surveying,Mapping and Remote Sensing,Wuhan University,Wuhan 430079,China)
出处
《地球信息科学学报》
CSCD
北大核心
2020年第5期997-1007,共11页
Journal of Geo-information Science
基金
国家重点研发计划项目(2018YFB2100500)。
