Planning Theory, Methodology and Academic Commentary

As China's urbanisation enters a new stage, the people-centred and quality-oriented urban development goals put forward higher requirements for urban ergonomics. At the same time, the fourth industrial revolution, which relied on the integration of computers and communications, is changing cities with a series of disruptive technologies. Three ways to promote urban development with emerging technologies were concluded in this paper. Specifically, the first way is to provide new data and methods for urban studies, the second is to influence urban space and urban life and eventually change the cognition of cities, and the third way is future-oriented, which introduces digital innovation into urban planning and designs to make cities smarter. This paper aims to provide some references for urban studies, management, as well as planning and design practice. 关键词： 科技革命，城市实验室，智慧城市，未来城市，城市人因工程学

right-sizing strategy has been an imperative method in solving urban problems caused by urban shrinkage all over the world, and the green infrastructure(GI) is the core of right-sizing planning. In this paper, the authors suggested to build a right-sizing model for Chinese shrinking cities based on GI, which including GI plan, land bank and corporative plan to address the shrinking problems caused by depopulation and lead shrinking cities to their right size. In addition, in order to fi ll the gap that current GI plan throughout the world lack the consideration of GI at a micro level, GI design fl ow charts are also introduced in the paper to offer treatment menu for vacant parcels to achieve social, ecological and economic benefi ts at the same time.

The paper provides an overview on the transformation of Chinese urban study driven by the emergence of new data environment in China in recent years. We firstly give a brief introduction on the new data environment, which has been made possible by the availability of big data and open data in recent years, as well as a review on the research progress both in China and abroad. It is followed by an analysis on four major transformations in quantitative urban study, supported by typical research cases, which are (1) transformation in spatial scale from high resolution but small coverage or wide coverage but low resolution to wide coverage with high resolution, (2) transformation in temporal scale from static cross-sectional to dynamic consistent, (3) transformation in granularity from land-oriented to human-oriented, (4) transformation in methodology from conventional research group to crowd-sourcing. The paper also points out that quantitative urban research is faced with problems like data bias, lack of long term analysis, lack of linkage to planning practice, etc. 关键词： 大数据 ； 开放数据 ； 城市规划 ； 大模型 ； 众包

Cities, used to be as simple as spatial entities surrounded by city walls in ancient time, have been getting increasingly complex. For instance, the total number of Chinese cities has increased from about 100 in 1949 to 653 in 2014, not to mention the frequent spatial adjustments of a single city ( Wu, Long, Mao, & Liu, 2015). A universal dif ficulty for urban studies is how a city can be de fined properly (Batty, 2006; Krugman 1996 ). There are several lenses to look at a city, morphologically, functionally, and administratively. From the morphology dimension, a city can be de fined as an area with a minimum of population or continuous built-up area. For instance, Densely Inhabited District (DID) in Japan indicating a city whose population density is over 4000 people per km 2 is a similar concept. Urban areas in UK are derived from constructions-built areas where certain real-estate densities are detected in satellite images or other datasets ( Hu, Wu, Xiong, & Pan, 2008 ). From the functional dimension, a city can be regarded as a functional urban area with a dense core and peripheral area as its commuting catchment (Cottineau, Hatna, Arcaute, & Batty, 2016). For instance, labor force markets and commuter sheds are utilized to represent Metropolitan Areas (MA) in US ( Berry, Goheen, & Goldstein, 1969).

As the emergence of big/open urban data in recent years, there have been lots of transformations going on in urban study and planning. In this article, we aim to provide a review of the major trends in this round of transformation. The review is started with a brief introduction to the new data environment, which has been made possible by the availability of big data and open data in recent years, as well as a review on the research progress in China, a developing country recently embracing the technology and data boom. It is followed by an analysis on the four major trends in quantitative urban study, supported by typical research cases. The four trends are (1) transforma- tion in spatial scale from high resolution but small coverage or wide coverage but low resolution to wide coverage with high resolution, (2) transformation in temporal scale fro m static cross-sectional to dynamic consistent, (3) transformation in granularity from land-oriented to human-oriented and (4) transforma tion in methodology from conven- tional research group to crowdsour cing. The paper also points out that quantitative urban research is faced with problems like data bias, lack of long-term analysis, lack of li nkage to planning practice etc. ARTICLE HISTORY Received 17 March 2016 Accepted 8 July 2016

Based on the research on the existing planning support system (PSS), this paper proposes the planner agent framework to support land use pattern scenario analysis (LUPSA). In the planner agent framework, importance is attached to the role of planners and the negotiation and coordination of different agents. Land use pattern is made based on planners’ planning rules identified through such methods as the data mining of existing planning schemes, comprehensive constraints, and special plans. The framework is initially tested in hypothetical spaces, followed by an experiment in Beijing. Results show that the proposed planner agent theory is suitable for LUPSA and can improve the efficiency and reasonability of LUPSA.

GeoJournal Library 116 Ying/uni00A0Long Zhenjiang/uni00A0Shen Geospatial Analysis to Support Urban Planning in Beijing GeoJournal Library V olume 116 Managing Editor Daniel Z. Sui, College Station, USA Founding Series Editor Wolf Tietze, Helmstedt, Germany Editorial Board Paul Claval, France Yehuda Gradus, Israel Sam Ock Park, South Korea Herman van der Wusten, The Netherlands More information about this series at http://www.springer.com/series/6007 Ying Long  Zhenjiang Shen Geospatial Analysis to Support Urban Planning in Beijing ISSN 0924-5499 ISSN 2215-0072 (electronic) GeoJournal Library ISBN 978-3-319-19341-0 ISBN 978-3-319-19342-7 (eBook) DOI 10.1007/978-3-319-19342-7 Library of Congress Control Number: 2015942626 Springer Cham Heidelberg New York Dordrecht London © Springer International Publishing Switzerland 2015 This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part of the material is concerned, specifi cally the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfi lms or in any other physical way, and transmission or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed. The use of general descriptive names, registered names, trademarks, service marks, etc.

目前地理信息系统( GIS) 中采用的数据结构主要有栅格和矢量两种 。 栅格数据结构简单,图形运算速度快 ,但是难以实现拓扑和网络分析 ;矢量数据可以对实体的空间关系进行全面的描述 ,但结构复杂 ,而且当图层中包含很多空间对象时 ,图形运算速度会非常慢 。 根据一张北京市远景土地利用规划图片,利用处理栅格格式的 GIS 软件提取各种土地利用类型的用地面积 ,取得了很好的效果 。 这种栅格处理的方法不仅可以用于图片资料处理,在遥感影像数据包含的内容比较复杂 、 边界比较模糊时,这种方法同样适用 。