scholarly journals Detecting Urban Polycentric Structure from POI Data

2019 ◽  
Vol 8 (6) ◽  
pp. 283 ◽  
Author(s):  
Deng ◽  
Liu ◽  
Liu ◽  
Luo
Keyword(s):  
Spatial Structure ◽  
Small Population ◽  
Urban Land Use ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Urban Centers ◽  
Point Of Interest ◽  
Spatial Changes ◽  
Urban Terrain ◽  
Contour Tree

It is meaningful to analyze urban spatial structure by identifying urban subcenters, and many methods of doing so have been proposed in the published literature. Although these methods are widely applied, they exhibit obvious shortcomings that limit their further application. Therefore, it is of great value to propose a new urban subcenter identification method that can overcome these shortcomings. In this paper, we propose the density contour tree (DCT) method for detecting urban polycentric structures and their spatial distributions. Conceptually, this method is based on an analogy between urban spatial structure and terrain. The point-of-interest (POI) density is visualized as a continuous mathematical surface representing the urban terrain. Peaks represent the regions of the most frequent human activity, valleys represent regions with small population densities in the city, and slopes represent spatial changes in urban land-use intensity. Using this method, we have detected the urban “polycentric” structure of Beijing and determined the corresponding spatial relationships. In addition, several important properties of the urban centers have been identified. For example, Beijing has a typical urban polycentric structure with an urban center area accounting for 5.9% of the total urban area, and most of the urban centers in Beijing serve comprehensive functions. In general, the method and the results can serve as references for the later research on analyzing urban structure.

scholarly journals Rethinking the Identification of Urban Centers from the Perspective of Function Distribution: A Framework Based on Point-of-Interest Data

2020 ◽  
Vol 12 (4) ◽  
pp. 1543 ◽  
Author(s):  
Lu Yu ◽  
Tao Yu ◽  
Yongxiang Wu ◽  
Guangdong Wu
Keyword(s):  
Spatial Distribution ◽  
Spatial Structure ◽  
Spatial Clustering ◽  
Urban Spatial Structure ◽  
Urban Center ◽  
Urban Centers ◽  
Modern Culture ◽  
Point Of Interest ◽  
Function Distribution ◽  
Urban Functions

Urban spatial structure has a significant impact on the sustainable development of cities. An important step of urban spatial structure analysis is the identification of urban centers. From the perspective of urban function distribution, this study developed a theoretical framework of three layers for urban center identification. In the first layer, point-of-interest data were collected from geospatial databases and utilized to capture the spatial distribution of urban functions. In the second layer, the density-based spatial clustering of application with noise (DBSCAN) algorithm was employed to group points of interest into urban centers according to their inter-distances and urban functions. In the third layer, the spatial distribution of the identified urban centers was visualized by the ArcGIS platform. This framework was applied in the urban center analysis of Beijing. The results showed that Beijing is in the process of transitioning from monocentric to polycentric with urban functions distributed unevenly throughout the city. To facilitate this transition, strategies such as the construction of super-large communities, the development of branch campuses and higher-education parks, and the enhancement of modern culture industries should be considered for the 11 new towns of Beijing.

Urban Spatial Structure and Travel in China

2019 ◽  
Vol 35 (1) ◽  
pp. 6-24 ◽  
Author(s):  
Lingqian Hu ◽  
Jiawen Yang ◽  
Tianren Yang ◽  
Yuanjie Tu ◽  
Jing Zhu
Keyword(s):  
Spatial Structure ◽  
Scoping Review ◽  
Contextual Factors ◽  
Mixed Effects ◽  
Empirical Literature ◽  
Future Research ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Complex Mechanisms ◽  
The Relationship

This article first provides a critical scoping review of empirical literature on the relationship between urban structure and travel in China. The review finds that residential suburbanization alone increases travel, polycentric development has mixed effects, and jobs–housing balance reduces travel. Second, this article compares the empirical findings of the urban structure–travel relationships in China with those observed in other countries, and it identifies contextual factors that can explain the differing relationships in China. We suggest that future research improve data and methodology and broaden the research scope to investigate the complex mechanisms that affect the urban structure–travel relationship in China.

scholarly journals Research on the Simulation Application of Data Mining in Urban Spatial Structure

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Jun Zhang ◽  
Xin Sui ◽  
Xiong He
Keyword(s):  
Data Mining ◽  
Internet Of Things ◽  
Spatial Structure ◽  
Urban Space ◽  
Simulation Analysis ◽  
Sustainable Urban Development ◽  
Urban Spatial Structure ◽  
Urban Centers ◽  
Urban Research ◽  
The City

Data mining and simulation of the Internet of things (IOT) have been applied more and more widely in the rapidly developing urban research discipline. Urban spatial structure is an important field that needs to be explored in the sustainable urban development, while data mining is relatively rare in the research of urban spatial structure. In this study, 705,747 POI (Point of Interest) were used to conduct simulation analysis of western cities in China by mining the data of online maps. Through kernel density analysis and spatial correlation index, the distribution and aggregation characteristics of different types of POI data in urban space were analyzed and the spatial analysis and correlation characteristics among different functional centers of the city were obtained. The spatial structure of the city is characterized by “multicenters and multigroups”, and the distribution of multicenters is also shown in cities with different functional types. The development degree of different urban centers varies significantly, but most of them are still in their infancy. Data mining of Internet of things (IOT) has good adaptability in city simulation and will play an important role in urban research in the future.

URBANISTINIS GENOTIPAS: KAI KURIE ASPEKTAI IR JŲ KAITOS TYRIMAI

2011 ◽  
Vol 35 (2) ◽  
pp. 73-81 ◽  
Author(s):  
Kęstutis Zaleckis ◽  
Irina Matijošaitienė
Keyword(s):  
Complex System ◽  
Spatial Structure ◽  
Complex Nature ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Crucial Importance ◽  
Street Network ◽  
Experimental Site ◽  
Downtown Area ◽  
Code Changes

A city is an open complex system. It should change in order to survive. Besides the need to change there is another one – to preserve stability of a valuable spatial structure. Two contradictory needs can create a problem, which is hard to solve. Concepts of urban genotype and phenotype help integrating both of the two above-mentioned needs. The same genotype can be expressed in different forms thus creating preconditions for evolution of an urban structure. On the basis of historical analogues, a conclusion was made that it is possible to describe an urban genotype in a utilitarian form in the article. The described research focuses on some aspects of urban genotype and investigation of code changes. As an experimental site for research, Kaunas downtown area was selected. This area is of crucial importance for preservation of Kaunas identity, which – at least at first glance – was protected from significant architectural and urban changes during the Soviet era… Results of the investigation reveal revolutionary changes of the genotype of the investigated area despite the fact that the street network and urban morphotype did not change much. It confirms the complex nature of the urban spatial structure and potential presence of the “butterfly effect”. Santrauka Miestas – atvira, kompleksiška sistema, kuri turi keistis tam, kad išliktų. Poreikis keistis ir išsaugoti miesto savitumui svarbias erdvines jo charakteristikas dažnai verčia rinktis vieną iš dviejų: kaitą ar stagnaciją. Urbanistinio genotipo ir fenotipo koncepcija leidžia išspręsti minėtą dilemą: keičiantis formai urbanistinis kodas ar genotipas gali išlikti nepakitęs ir taip užtikrinti evoliucinę urbanistinės struktūros kaitą. Straipsnyje, remiantis istoriniais analogais, teigiamai įvertinus urbanistinio kodo utilitaraus užrašymo galimybes, pagrindinis dėmesys skiriamas kai kuriems kodo aspektams tirti ir jų kaitai įvertinti. Kaip tyrimų poligonas naudojamas istorinis Kauno centras – miesto savasčiai svarbi ir architektūriniu požiūriu radikaliai nepakeista miesto dalis. Tyrimų rezultatai atskleidžia įvykusius didelius teritorijos urbanistinio genotipo pokyčius ir kartu patvirtina vieną iš tyrimo pradžioje padarytų prielaidų: miestui kaip kompleksiškai sistemai gali būti būdingas „drugelio efektas“ – ir nedideli pakeitimai fenotipe gali sukelti gana dideles mutacijas genotipe.

scholarly journals Detecting and Analyzing Urban Centers Based on the Localized Contour Tree Method Using Taxi Trajectory Data: A Case Study of Shanghai

2021 ◽  
Vol 10 (4) ◽  
pp. 220
Author(s):  
Mengqi Sun ◽  
Hongchao Fan
Keyword(s):  
Urban Structure ◽  
Analysis Framework ◽  
Urban Center ◽  
Trajectory Data ◽  
Urban Centers ◽  
Transportation Economics ◽  
Contour Tree ◽  
Tree Method ◽  
Taxi Trajectory

Urban structure is of vital importance to urban planning, transportation, economics and other applications. Since detecting and analyzing urban centers is crucial for understanding urban structure, a large number of studies on urban center extraction have been performed. In this paper, we propose an analysis framework to identify urban centers by using taxi trajectory data. The proposed approach differs from previous methods by employing a novel way to simulate taxi trajectory data with the topographic surface. We extracted pick-up and drop-off spots from taxi trajectory data and employed the localized contour tree method to delineate the boundaries and hierarchies of urban centers. The experiments show that the proposed method can successfully detect urban centers and analyze their temporal patterns in different periods in Shanghai, China.

scholarly journals Urban attributes of degraded towns on the example of the West Pomeranian Voivodeship

2020 ◽  
Vol 34 ◽  
Author(s):  
Mateusz Cudo
Keyword(s):  
Spatial Structure ◽  
Cultural Landscape ◽  
Current Level ◽  
Urban Spatial Structure ◽  
Urban Centers ◽  
The West ◽  
Urban Status ◽  
The Status ◽  
Post War ◽  
A Current

The article presents degraded towns in the West Pomeranian Voivodeship that currently maintain the status of a village. Five settlements, which today are seats of communes, were analyzed in detail, as well as four that performed such a function in the post-war past. First of all, the origin of the emergence as well as the circumstances of the loss of the urban status were discussed. Then a current level of development of the features of urban centers was presented, as regards to the population, functional and spatial aspects. In addition to the number of population and the structure of the economy, particular attention was given to the urban spatial structure that co-create the local cultural landscape. The summary presents the main reasons for the degradation of the discussed centres and highlights those that potentially have the greatest predisposition to regain the urban status.

scholarly journals URBANISTINIS GENOTIPAS: KAI KURIE ASPEKTAI IR JŲ KAITOS TYRIMAI

2011 ◽  
Vol 35 (2) ◽  
pp. 73-81
Author(s):  
Kęstutis Zaleckis ◽  
Irina Matijošaitienė
Keyword(s):  
Complex System ◽  
Spatial Structure ◽  
Complex Nature ◽  
Urban Structure ◽  
Urban Spatial Structure ◽  
Crucial Importance ◽  
Street Network ◽  
Experimental Site ◽  
Downtown Area ◽  
Code Changes

A city is an open complex system. It should change in order to survive. Besides the need to change there is another one – to preserve stability of a valuable spatial structure. Two contradictory needs can create a problem, which is hard to solve. Concepts of urban genotype and phenotype help integrating both of the two above-mentioned needs. The same genotype can be expressed in different forms thus creating preconditions for evolution of an urban structure. On the basis of historical analogues, a conclusion was made that it is possible to describe an urban genotype in a utilitarian form in the article. The described research focuses on some aspects of urban genotype and investigation of code changes. As an experimental site for research, Kaunas downtown area was selected. This area is of crucial importance for preservation of Kaunas identity, which – at least at first glance – was protected from significant architectural and urban changes during the Soviet era… Results of the investigation reveal revolutionary changes of the genotype of the investigated area despite the fact that the street network and urban morphotype did not change much. It confirms the complex nature of the urban spatial structure and potential presence of the “butterfly effect”. Santrauka Miestas – atvira, kompleksiška sistema, kuri turi keistis tam, kad išliktų. Poreikis keistis ir išsaugoti miesto savitumui svarbias erdvines jo charakteristikas dažnai verčia rinktis vieną iš dviejų: kaitą ar stagnaciją. Urbanistinio genotipo ir fenotipo koncepcija leidžia išspręsti minėtą dilemą: keičiantis formai urbanistinis kodas ar genotipas gali išlikti nepakitęs ir taip užtikrinti evoliucinę urbanistinės struktūros kaitą. Straipsnyje, remiantis istoriniais analogais, teigiamai įvertinus urbanistinio kodo utilitaraus užrašymo galimybes, pagrindinis dėmesys skiriamas kai kuriems kodo aspektams tirti ir jų kaitai įvertinti. Kaip tyrimų poligonas naudojamas istorinis Kauno centras – miesto savasčiai svarbi ir architektūriniu požiūriu radikaliai nepakeista miesto dalis. Tyrimų rezultatai atskleidžia įvykusius didelius teritorijos urbanistinio genotipo pokyčius ir kartu patvirtina vieną iš tyrimo pradžioje padarytų prielaidų: miestui kaip kompleksiškai sistemai gali būti būdingas „drugelio efektas“ – ir nedideli pakeitimai fenotipe gali sukelti gana dideles mutacijas genotipe.

scholarly journals Revealing Characteristics of the Spatial Structure of Megacities at Multiple Scales with Jobs-Housing Big Data: A Case Study of Tianjin, China

Land ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1144
Author(s):  
Ruixi Dong ◽  
Fengying Yan
Keyword(s):  
Big Data ◽  
Spatial Structure ◽  
Urban Space ◽  
Dynamic Characteristics ◽  
Multiple Scales ◽  
Spatial Scales ◽  
Urban Land Use ◽  
Urban Spatial Structure ◽  
Static Characteristics ◽  
Transportation Development

Urban spatial structure reflects the organization of urban land use and is closely related to the travel patterns of residents. The characteristics of urban spatial structure include both static and dynamic aspects. The static characteristics of urban spatial structure reflect the morphological features of space, and the dynamic characteristics of urban spatial structure reflect intra-city functional linkages. With the continuous agglomeration of population and industries; megacities have become the core spatial carriers leading China’s social and economic development; and their urban spatial structure has also been reconstructed. However; there is still a certain lack of understanding of the characteristics of the spatial structure of China’s megacities. This study aimed to reveal characteristics of the spatial structure of Chinese megacities at different scales using jobs-housing big data. To achieve this goal, spatial autocorrelation and a geographically weighted regression (GWR) model were applied to reveal static polycentricity, and community detection was used to reveal dynamic commuting communities. The distribution of jobs in urban space and jobs–housing balance levels in commuting communities were further analyzed. Experiments were conducted in Tianjin, China. We found that: (1) the static characteristics of the spatial structure of megacities presented the coexistence of polycentricity and a high degree of dispersion at macro- and meso-scales; (2) the dynamic characteristics of the spatial structure of megacities revealed two types of commuting communities at macro- and meso-scales and most commuting communities had a good jobs-housing balance. These findings can be referenced by urban managers and planners to formulate relevant policies for spatial distribution optimization of urban functions and transportation development at different spatial scales.

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