【摘要】 以兴趣点（Point of Interest,POI）大数据为数据源，搭建POI数据和15 min生活圈要素数据的转换体系。根据实际出行特征和地形地貌影响进行出行时间算法优化，并创新性地提出“达标度”“富裕度”“覆盖度”3个关联和交叉验证的量化评价指标，旨在构建以大数据为支撑的快速、精准识别城市生活圈建设情况的研究方法。以重庆九龙坡东城区为例进行实证研究，从功能置换、交通提升、用地混和、城市更新等方面提出相应的更新优化策略。更多还原

【Abstract】 Based on POI big data source, this study builds a conversion system between POI data and 15-minute life circle elements. It optimizes travel time algorithms based on actual travel characteristics and the impact of terrain and landforms, and innovatively proposes three quantitative evaluation indicators— "compliance rate", "abundance rate",and "coverage rate" —for cross-validation. The aim is to develop a rapid identification methodology for urban life circle construction using network big data. A case study of Jiulongpo East District in Chongqingis conducted, proposing corresponding optimization strategies in four dimensions: functional transformation, transportation enhancement,mixed land use, andurban renewal.更多还原