The problem associated with a city’s administrative boundary being “under-” or “over-bounded” has become a global phenomenon. A city’s administrative boundary city does not effectively represent the actual size and impact of its labor force and economic activity. While many existing case studies have investigated the functional urban areas of single cities, the problem of how to delineate urban areas in geographic space relating to large bodies of cities or at the scale of an entire country has not been investigated. This study proposed a method for FUA identification that relies on ride-hailing big data. In this study, over 43 million anonymized 2016 car-hailing records were collected from Didi Chuxing, the largest car-hailing online platform in the world (to the best of our knowledge). A core-periphery approach is then proposed that uses nationwide and fine-grained trips to understand functional urban areas in Mainland China. This study examined 4,456 out of all 39,007 townships in an attempt to provide a new method for the definition of urban functional areas in Chinese Mainland. In addition, four types of cities are identified using a comparison of functional urban areas with their administrative limits, and a further evaluation is conducted using 23 Chinese urban agglomerations. With the rapidly increasing use of internet-based ride-hailing services, such as Didi, Grab, Lyft, and Uber, globally, this study provides a practical benchmark for the delineation of functional urban areas at larger scales.
With the obvious regionalization trend in the new period of urbanization in China, the scientific delineation of functional regions (FRs) at different scales has become a heated topic recently. Since the 20th century, western academia has formed a basic idea of metropolitan areas’ (MAs) delineation based on population density and commuting rate, for which the subjectivity of threshold setting is difficult to overcome. In this study, community detection algorithms from the field of network science are employed, namely the Louvain algorithm with adjustable resolutions and Combo with high-precision output, respectively. We take the nationwide car-hailing data set as an example to explore a bottom-up method for delineating regional economic geography at different scales based on the interconnection strength between nodes. It was found that most of the prefecture-level cities in China have a dominant commuting region and two or three secondary commuting sub-regions, while regional central cities have extended their commuting hinterlands over jurisdictional boundaries, which is not common due to the larger initial administrative divisions and the comprehensive development niveau of cities. The feasibility and limitation of community detection partitioning algorithms in the application of regional science are verified. It is supposed to be widely used in regional delimitation supported by big data. Both of the two algorithms show a shortage of ignorance of spatial proximity. It is necessary to explore new algorithms that can adjust both accuracy and spatial distance as parameters.
Urban forms reflect spatial structures of cities, which have been consciously and dramatically changing in China. Fast urbanisation may lead to similar urban forms due to similar habits and strategies of city planning. However, whether urban forms in China are identical or significantly different has not been empirically investigated. In this paper, urban forms are investigated based on two spatial units: city and block. The boundaries of natural cities in terms of the density of human settlements and activities are delineated with the concept of ‘redefined city’ using points of interests (POIs), and blocks are determined by road networks. Urban forms are characterised by city-block two-level spatial morphologies. Further, redefined cities are classified into four hierarchies to examine the effects of different city development stages on urban forms. The spatial morphology is explained by urbanisation variables to understand the effects. Results show that the urban forms are spatially clustered from the perspective of city-block two-level morphologies. Urban forms tend to be similar within the same hierarchies, but significantly varied among different hierarchies, which is closely related to the development stages. Additionally, the spatial dimensional indicators of urbanisation could explain 41% of the spatial morphology of redefined cities.
Scientifically identifying cities in the spatial dimension is a basis for objectively understanding urbanization, improving urban and rural statistics and formulating urban and rural planning strategies. In this article, using communities as basic administrative units and the data of urban built-up areas, a straightforward method to identify physical urban area has been established. We used this method to identity the physical urban area in Chinese whole territory and redefined Chinese city system. According to our studies, there are total 1,227 cities in China from the perspective of physical urban area covering 60,535km2 and this city amount is 86.2% higher than the amount of Chinese administrative cities which is 659. There are 126 Chinese administrative cities did not contain any cities from the physical urban area perspective, including 19 prefecture level cities, such as Sanming, Nanping, Chongzuo, Lincang, Yan’an, Yulin, Ya’an, Karamay, Donghai and 107 county level cities, such as Sansha and Alar, Dunhuang, Tongren, Wugang, Zhangshu, Jianyang and Wuyishan. There are 10 administrative cites contain at least 5 cities from the physical urban area perspective, which can be suggested to be divided into several smaller cities for management. They are Chongqing (16 cities), Beijing (12 cities), Suzhou (9 cities), Changzhou (7 cities), Shanghai (7 cities), Tianjin(6 cities), Wuhan (6 cities), Zaozhuang (6 cities), Shantou (6cities) and Foshan (6 cities). Our study is expected to provide supports for urban and rural planning and construction department and ministry of civil affairs to adjust urban administrative boundaries.
We have already shared the derived spatial cities of China in 2015 in the Data Released channel (see Data "38 Spatial cities of China in 2015").
Modern Chinese cities are defined from the administrative view and classified into several administrative categories, which makes it inconsistent between Chinese cities and their counterparts in western countries. Without easy access to fine-scale data, researchers have to rely heavily on statistical and aggregated indicators available in officially released yearbooks, to understand Chinese city system. Not to mention the data quality of yearbooks, it is problematic that a large number of towns or downtown areas of counties are not addressed in yearbooks. To address this issue, we have redefined the Chinese city system, using percolation theory in the light of newly emerging big/open data. In this paper, we propose our alternative definition of a city with road/street junctions, and present the methodology for extracting city system for the whole country with national wide road junctions. A city is defined as “a spatial cluster with a minimum of 100 road/street junctions within a 300 m distance threshold”. Totally we identify 4,629 redefined cities with a total urban area of 64,144 km2 for the whole China. We observe total city number increases from 2,273 in 2009 to 4,629 in 2014. We find that expanded urban area during 2009 and 2014, comparing with urban areas in 2009 are associated with 73.3% road junction density, 25.3% POI density and 5.5% online comment density. In addition, we benchmark our results with the conventional Chinese city system by using yearbooks.
The last several decades have witnessed a rapid yet uneven urban expansion in developing countries. The existing studies rely heavily on official statistical yearbooks and remote sensing images. However, the former data sources have been criticized due to its non-objectivity and low quality, while the latter is labor and cost consuming in most cases. Recent efforts made by fractal analyses provide alternatives to scrutinize the corresponding “natural urban area”. In our proposed framework, the dynamics of internal urban contexts is reflected in a quasi-real-time manner using emerging new data and the expansion is a fractal concept instead of an absolute one based on the conventional Euclidean method. We then evaluate the magnitude and pattern of natural cities and their expansion in size and space. It turns out that the spatial expansion rate of official cities (OCs) in our study area China has been largely underestimated when compared with the results of natural cities (NCs). The perspective of NCs also provides a novel way to understanding the quality of uneven urban expansion. We detail our analysis for the 23 urban agglomerations in China, especially paying more attention to the three most dominating urban agglomerations of China: Beijing-Tianjin-Hebei (BTH), Yangtze River Delta (YRD) and Pearl River Delta (PRD). The findings from the OC method are not consistent with the NC method. The distinctions may arise from the definition of a city, and the bottom-up NC method contributes to our comprehensive understanding of uneven urban expansion.