基于时序街景数据的城市街道绿化结构演变——以上海市中心城区为例  

Evolution of Urban Street Greening Structure Based on Time Series Street View Data:A Case Study of the Central Urban Area of Shanghai

作　　者：王磊 章璇 韩昊英[2,3] 何捷 WANG Lei;ZHANG Xuan;HAN Haoying;HE Jie(the School of Architecture,Tianjin University;the School of Civil Engineering and Architecture,Zhejiang University;the Faculty of Innovation and Design,City University of Macao;the School of Architecture,Harbin Institute of Technology(Shenzhen))

机构地区：[1]天津大学建筑学院 [2]浙江大学建筑工程学院 [3]澳门城市大学创新设计学院,中国澳门 [4]哈尔滨工业大学(深圳)建筑学院

出　　处：《风景园林》2024年第9期42-50,共9页Landscape Architecture

基　　金：哈尔滨工业大学深圳校区新引进高精尖缺人才科研启动经费“数字人文与空间历史大数据支持的城乡文化赋能”(编号ZX20230488);浙江大学平衡建筑研究中心资助项目“韧性城市的指标体系与规划方法”(编号K横20203512-02B)。

摘　　要：【目的】城市街道绿化结构的演变和优化是评价城市发展质量的重要指标,特别是在中国的典型城市上海,街道绿化对于改善城市微气候、减少空气污染以及提供居民休憩空间具有至关重要的作用。为了提升城市街道绿化质量,深入探究上海市中心城区在2013—2019年之间的城市街道绿化结构演变规律。【方法】基于时序街景图像数据,利用DeepLabV3+语义分割技术,详细分析上海市中心城区城市街道绿化结构的空间和时间演变规律。【结果】2013—2019年,上海城市街道绿化结构中的植物视觉要素占比有所增加,乔木、灌木和草本植物的视觉要素占比分别增加了25.09%、19.32%和42.39%。在街景的地理空间分布中,2019年综合性城市街道绿化结构(乔-灌-草)的数量相比2013年增加了23.99%,尤其是浦东新区和杨浦区的绿化结构增量变化更加明显。表明了城市街道绿化结构要素和绿化结构的增量具有空间分布一致性。【结论】基于人工智能技术的城市绿化监测方法能够有效识别城市街道绿化结构演变规律,为城市决策者和规划者提供了维护和增强城市绿化的全新视角。[Objective]For urban street space,a main place for residents'daily public activities,its greening structure plays a crucial role in influencing walking index,environmental assessment,residents'health and economic benefits.Street greening can significantly enhance residents'life satisfaction,especially in highdensity urban environments.With the development of computer technology,it has become possible to combine visual analysis techniques to conduct a finegrained research on urban street greening structure.Studying the spatial and temporal evolution of street greening structure not only helps understand the spatial experience and landscape changes of urban streets,but also has great significance in scientifically evaluating and optimizing urban street greening,and promoting the high-quality and sustainable development of urban street space.Urban street greening structure is a three-dimensional plant composition concept,which usually includes high-level trees,mid-level shrubs and herbaceous plants.Through historical research and analysis of street view images,the research shows that traditional street greening measurements cannot effectively reflect the three-dimensional visual experience of residents,and therefore new methods are needed to more accurately analyze the greening structure of urban streets.In summary,the purpose of this research is to propose a new research framework to finely analyze the change trends and influence mechanisms at the level of urban street greening structure.Taking the Chinese city Shanghai as an example,the research adopts advanced artificial intelligence technology and time series street view data to conduct an in-depth research on the greening structure of urban streets.[Methods]At the data level,the road network is downloaded through OpenStreetMap,and street view sampling points are set at an interval of 50 m along the road network.Time series street view image data on the central urban area of Shanghai in summers during the period from 2013 and 2019 are collected via Baidu Map.At

关 键 词：风景园林 人工智能 时序街景 绿化结构 百度街景 

分 类 号：TU986[建筑科学—城市规划与设计]