协频城市:时空数据增强设计中的频度协同*

Synergised City: Frequency Synergy in Spatiotemporal Data-Augmented-Design

沈 尧
自然资源部国土空间智能规划技术重点实验室 同济大学建筑与城市规划学院 副教授,博士生导师 英国伦敦大学学院高级空间分析中心 荣誉研究员


摘要: 真实的城市瞬息变化,持续演进。得益于海量的跨模态高频时空感知数据的涌现,城市分析方法与干预手段持续“高频化”,与较为“低频”的传统规划理论形成互补,为城市的短期、长期干预分别提供了路径。“低频城市”与“高频城市”有机结合的复合态是未来城市的特点,进而提出一种新的规划设计视角——“协频城市”,其强调高低频协同的城市研究和干预方法,以城市时间频度为切入点,运用频度与空间规划的单元、尺度、粒度、距离等要素的紧密联系,提倡尊重时空数据的自然频度和尺度涌现机制,以及与城市议题干预需求对应的必要性,以智能技术作为一种协频和调频工具箱形成以地点为视角、时空规律发现为特点的时空数据增强的路径。提出以整合城市频度作为一种发现城市智能和探索新规划理论的重要手段,指出在城市研究和实践中运用“频度智能”对于规划智能化的积极意义。

Abstract: Real cities continue shifting and evolving almost instantly. With the massive cross-modal, high-frequency, and spatiotemporal data, the approaches in urban analytics and spatial intervention are now known to be high-frequency, complementing the conventional, low-frequency methods, and providing new possibilities for short-term and long-term decision-making for urban wellbeing. The so-called "high-frequency city" and "low-frequency city" imply two paradigms that are not well-associated and mutually referenced, and the scrutiny on the urban frequency and on the cities under different frequencies is very still absent. This research introduces a new paradigm named "hybrid-frequency city" as a new methodology to incorporate the high-frequency city and low-frequency city comprehensively. It is argued that neither a fully high-frequency city nor a pure low-frequency city is the ultra-form of the future city. Urban frequency is defined as a fundamental element in the hybrid-frequency city, which is closely associated with domains, resolution, scales, etc. In our framework, the method to calibrate proper resolutions and scales for the purposed spatial domain is proposed and a frequency modulator is required for synergising the interventions across domains, scales, and resolutions for various urban issues. It is demonstrated that urban frequency is an essential type of urban intelligence that benefits relevant urban studies and practice with domain-scale-resolution precision.

关键词:大数据;频度;数据增强设计;城市科学;规划协同

Keyword: big data; frequency; Data Augmented Design; urban science; planning synergy

中图分类号:TU981

文献标识码: A

资金资助

国家重点研发计划课题 “城市韧性测度及动态演化机理” 2020YFB2103901-1

吴志强,甘惟. 转型时期的城市智能规划技术实践[J]. 城市建筑,2018(3):26-29.
WU Zhiqiang, GAN Wei. Urban intelligent planning technology practice in transitional period[J]. Urbanism and Architecture, 2018(3): 26-29.
BATTY M. Inventing future cities[M]. Cambridge: MIT Press, 2018.
柴彦威,端木一博. 时间地理学视角下城市规划的时间问题[J]. 城市建筑,2016(16):21-24.
CHAI Yanwei, DUANMU Yibo. Time problem in urban planning from the perspective of time-geography[J]. Urbanism and Architecture, 2016(16): 21-24.
沈尧. 动态的空间句法——面向高频城市的组构分析框架[J]. 国际城市规划,2019(1):54-63.
SHEN Yao. Dynamic space syntax: towards the configurational analysis of the high frequency cities[J]. Urban Planning International, 2019(1): 54-63.
BATTY M. High and low frequency cities, big data and urban theory[M]//WILLIS K,AURIGI A.The Routledge companion to smart cities. London: Routledge, 2020: 51-60.
龙瀛,沈尧. 数据增强设计——新数据环境下的规划设计回应与改变[J]. 上海城市规划,2015(2):81-87.
LONG Ying, SHEN Yao. Data Augmented Design: urban planning and design in the new data environment[J]. Shanghai Urban Planning Review, 2015(2): 81-87.
ALEXANDER C. A city is not a tree[M]. Portland: Sustasis Press, 1968.
LIU Y, LIU X, GAO S, et al. Social sensing: a new approach to understanding our socioeconomic environments[J]. Annals of the Association of American Geographers, 2015, 105(3): 512-530.
MICHAEL B. The new science of cities[M]. Cambridge: MIT press, 2013:13-20.
杨滔,张晔珵,秦潇雨. 城市信息模型(CIM)作为“城市数字领土”[J]. 北京规划建设,2020(6):75-78.
YANG Tao, ZHANG Yecheng, QIN Xiaoyu. City Information Modelling (CIM) as the digital territory of the city[J]. Beijing Planning Review, 2020(6): 75-78.
牛强,夏源,牛雪蕊,等. 智慧城市的大脑——智慧模型的概念、类型和作用[J]. 上海城市规划,2018(1):40-43,62.
NIU Qiang, XIA Yuan, NIU Xuerui, et al. Smart model: the brain of smart city and its concept, categories and function[J]. Shanghai Urban Planning Review, 2018(1): 40-43, 62.
甄峰,孔宇. “人—技术—空间”一体的智慧城市规划框架[J]. 城市规划学刊,2021(6):45-52.
ZHEN Feng, KONG Yu. An integrated "human-technology-space" framework of smart city planning[J]. Urban Planning Forum, 2021(6): 45-52.
龙瀛,沈尧. 大尺度城市设计的时间、空间与人(TSP)模型——突破尺度与粒度的折中[J]. 城市建筑,2016(16):33-37.
LONG Ying, SHEN Yao. A Time-Space-People (TSP) model for the human focused, fine-resolution and large-scale urban design[J]. Urbanism and Architecture, 2016(16): 33-37.
SHUGART H H. A theory of forest dynamics: the ecological implications of forest succession models[M]. Caldwell: The Blackburn Press, 1984.
SONG C, QU Z, BLUMM N, et al. Limits of predictability in human mobility[J]. Science, 2010, 327(5968): 1018-1021.
ZHONG C, BATTY M, MANLEY E, et al. Variability in regularity: mining temporal mobility patterns in London, Singapore and Beijing using smart-card data[J]. PloS ONE, 2016, 11(2): e0149222.
CHENG T, ADEPEJU M. Modifiable Temporal Unit Problem (MTUP) and its effect on space-time cluster detection[J]. PloS ONE, 2014, 9(6): e100465.
沈尧,卓健,吴志强. 精准城市设计面向社会效应精准提升的城市形态[J]. 时代建筑,2021(1):26-33.
SHEN Yao, ZHUO Jian, WU Zhiqiang. Precise urban design toward socially sustainable urban form[J]. Time+ Architecture, 2021(1): 26-33.
麦克•巴迪,沈尧. 城市规划与设计中的人工智能[J]. 时代建筑,2018(1):24-31.
BATTY M, SHEN Yao. Artificial intelligence in city planning and design[J]. Time+ Architecture, 2018(1): 24-31.
塔娜,柴彦威. 行为地理学的学科定位与前沿方向[J]. 地理科学进展,2022,41(1)::1-15.
TA Na, CHAI Yanwei. Disciplinary position and research frontiers of behavioral geography[J]. Progress in Geography, 2022, 41(1): 1-15.
龙瀛,张恩嘉. 科技革命促进城市研究与实践的三个路径:城市实验室、新城市与未来城市[J]. 世界建筑,2021(3):62-65.
LONG Ying, ZHANG Enjia. Three ways to promote urban research and practice with emerging technologies: from the perspectives of city laboratory, new city, and future city[J]. World Architecture, 2021(3): 62-65.
SENOUSI A M, ZHANG J, SHI W, et al. A proposed framework for identification of indicators to model high-frequency cities[J]. ISPRS International Journal of Geo-Information, 2021, 10(5): 317.

微信扫一扫
关注“上海城市规划”
公众号