数据驱动的武汉市城镇低效居住用地评价模型研究

Research on a Data-driven Evaluation Model for Inefficient Residential Land in Urban Areas of Wuhan City

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摘要为聚焦低效用地再开发,促进城市土地集约节约利用,以武汉市为研究对象,研究多源数据下基于数据驱动的城镇低效居住用地评价模型。通过搜集多源公开数据集,挖掘低效居住用地概念内涵,构建低效居住用地识别体系,考虑居住用地特征及其在城市生活中的整体作用,兼顾经济、生活、生态、安全等多元需要,构建了内外部综合评价指标体系。利用数据驱动构建内外部综合评价模型,实现对武汉市低效居住用地的评价。结果表明,该方法能更加充分利用和表达多维度评价指标信息;武汉市低效居住用地分布呈正向自相关性,表现为城区中心的高高聚集和周围的低低聚集;内部性指标评分较低,低效居住用地再开发在提升容积率、居住用地绿化率等方面仍有较大进步空间。 To focus on the redevelopment of inefficient land and promote the intensive and economical use of urban land,taking Wuhan City as a case study,we explored a data-driven evaluation model for inefficient residential land.We collected multi-source public datasets,excavated the conceptual connotation of inefficient residential land,and constructed the inefficient residential land identification system.Considering the characteristics of residential land and its overall role in urban life,we established a comprehensive evaluation indicator system which balanced economic,social,ecological and safety needs.By developing the internal and external comprehensive evaluation models based on data-driven,we evaluated the inefficient residential land inWuhan City.The conclusions show that the method can more fully utilize and express multi-dimensional evaluation indicators.The distribution of inefficient residential land in Wuhan City exhibits positive spatial autocorrelation,characterized by high clustering in urban center and low clustering in surrounding areas.The scores of internal indicators for inefficient residential land are relatively low,indicating significant opportunities for improvement in redevelopment,particularly in terms of increasing floor area ratio and enhancing the greening rate of residential land.

作者周志诚梁思周祎博陈江平何艺 ZHOU Zhicheng;LIANG Si;ZHOU Yibo;CHEN Jiangping;HE Yi(Hubei Institute of Photogrammetry and Remote Sensing,Wuhan 430074,China;School of Remote Sensing and Information Engineering,Wuhan University,Wuhan 430079,China)

机构地区湖北省航测遥感院武汉大学遥感信息工程学院

出处《地理空间信息》 2025年第1期34-40,52,共8页 Geospatial Information

关键词城镇低效用地土地识别评价指标深度学习 urban inefficient land land identification evaluation indicator deep learning

分类号 P208 [天文地球—地图制图学与地理信息工程]

作者简介第一作者:周志诚(1974-),本科,正高级工程师,从事遥感数据处理、应用技术体系建设、自然资源监测监管等技术研究与应用服务推广工作,E-mail:179978287@qq.com;通信作者:梁思(1985-),硕士研究生,工程师,从事摄影测量与遥感生产管理和技术研究工作,E-mail:442493532@qq.com。