Characterizing Spatial Variations of Urban Growth Patterns in Beijing, China through Spatial Analysis and Geovisualization

Abstract. As the capital city and one of the largest cities of China, Beijing has experienced rapid urban growth in the past several decades. Despite the numerous research efforts of monitoring the spatiotemporal urban growth patterns in Beijing, there is a lack of consensus and comparable results for theory development or decision-making.This paper presents a systematic approach of characterizing urban growth patterns in Beijing through spatial analysis and geovisualization. Specifically, we focus on characterizing the different dimensions of urban growth across scales, including density, continuity, direction, and centrality (Galster et al. 2001). We first derive general land cover information in Beijing from satellite imagery for the years of 1998, 2008, and 2018. The urban extent of Beijing is extracted for each year to be used for further analysis. We then characterize the urban growth patterns through various geovisualization and spatial analysis techniques at both the metropolitan level and the local/cell level (Table 1).At the metropolitan level, we present the general trends of urban growth patterns in Beijing through landscape pattern metrics and spatial statistics. In addition, we compare the measurements of density, continuity and direction across the four functional zones in Beijing, i.e., urban core, extensive urban, new urban, and ecological conservation zone. The result reveals the regional variations and the underlying processes of urban growth in the Beijing metropolitan area. At the local level, we measure the spatial variations of urban growth patterns using a GIS-based moving windows analysis. As the moving window passes over the landscape, each calculated metrics is returned to the focal cell. This creates a surface representation of the selected metrics, which enables the creation of a contour map. The distribution of the contours delineates the spatial variations of urban growth at a finer scale. The developed approach can be applied to urban studies of other geographic areas, which will eventually lead to a comparative study of urban development.

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Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing

Landscape and Urban Planning ◽

10.1016/j.landurbplan.2008.11.010 ◽

2009 ◽

Vol 91 (2) ◽

pp. 51-64 ◽

Cited By ~ 190

Author(s):

Jun Luo ◽

Y.H. Dennis Wei

Keyword(s):

Urban Growth ◽

Spatial Variations ◽

Growth Patterns ◽

Chinese Cities

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Monitoring of Urban Growth Patterns in Rapidly Growing Bahir Dar City of Northwest Ethiopia with 30 year Landsat Imagery Record

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi9090548 ◽

2020 ◽

Vol 9 (9) ◽

pp. 548 ◽

Cited By ~ 1

Author(s):

Mengistie Kindu ◽

Daniela Angelova ◽

Thomas Schneider ◽

Martin Döllerer ◽

Demel Teketay ◽

...

Keyword(s):

Urban Growth ◽

Forest Cover ◽

Accuracy Assessment ◽

Landsat Imagery ◽

Local Level ◽

Northwest Ethiopia ◽

Growth Patterns ◽

Bahir Dar ◽

Change Analysis ◽

Rapid Reduction

Monitoring urban growth patterns is an important measure to improve our understanding of land use/land cover (LULC) changes and a central part in the proper development of any city. In this study, we analyzed the changes over a period of 30 years (1985–2015) in Bahir Dar, one of the rapidly growing cities of northwest Ethiopia. Satellite images of Landsat TM (1985, 1995, and 2008), and OLI (2015) were used. The classification was carried out using the object-based image analysis technique and a change analysis was undertaken using post-classification comparison in GIS as a novel framework. An accuracy assessment was conducted for each reference year. Eight LULC types were successfully captured with overall accuracies ranging from 88.3% to 92.9% and a Kappa statistic of 0.85 to 0.92. The classification result revealed that cropland (66%), water (12.5%), and grassland (6%) were the dominant LULC types with a small share of areas covered by built-up areas (2.4%) in 1985. In 2015, cropland and water continued to be dominant followed by built-up areas. The change result shows that a rapid reduction in natural forest cover followed by grassland and wetland occurred between the first (1985–1995), second (1995–2008), and third (2008–2015) study periods. On the contrary, build-ups increased in all three periods by 9.3%, 121.3%, and 44.8%, respectively. Although the conversion between the LULC classes varied substantially, analysis of the 30-year change matrix revealed that about 31% was subject to intensive change between the classes. Specifically, the built-up area has increased by 250.5% during the study years. The framed approach used in this research is a good repeatable example of how to assess and monitor urban growth at the local level, by combining remote sensing and GIS technologies. Further study is suggested to investigate detailed drivers, consequences of changes, and future options.

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Spatial analysis of urban growth based on city center and central business district (a case study of Antananarivo, the capital city of Madagascar)

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/389/1/012010 ◽

2019 ◽

Vol 389 ◽

pp. 012010

Author(s):

A Fetraniaina ◽

A Deliar ◽

A B Harto

Keyword(s):

Spatial Analysis ◽

Urban Growth ◽

Central Business District ◽

Capital City ◽

City Center ◽

Business District

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Retail Suburbanization, Modernization, and Growth in Sydney during Australia’s Postwar Boom

Journal of Urban History ◽

10.1177/00961442211023600 ◽

2021 ◽

pp. 009614422110236

Author(s):

Matthew Bailey

Keyword(s):

Capital City ◽

Growth Strategies ◽

Capital Cities ◽

Form And Function ◽

Urban Core ◽

Socially Constructed ◽

And Function ◽

Retail Formats ◽

Car Driving

This article uses Sydney as a case study to examine the process of retail decentralization during Australia’s postwar boom, showing how the form and function of capital city retailing changed completely in just a couple of decades. Suburban migration, the emergence of mobile car-driving consumers, socially constructed gender roles, the ongoing importance of public transport networks, planning regimes that sought to concentrate development in designated zones, and business growth strategies that deployed retail formats developed in America all played a role in shaping the form and function of Australian retailing during the postwar boom. In the process, the retail geographies of Australia’s capital cities were transformed from highly centralized distribution structures dominated by the urban core, to decentralized landscapes of retail clusters featuring modern retail forms like the supermarket and shopping center that would come to define Australian retailing for the remainder of the century.

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Spatial variations and macroeconomic determinants of life expectancy and mortality rate in China: a county-level study based on spatial analysis models

International Journal of Public Health ◽

10.1007/s00038-019-01251-y ◽

2019 ◽

Vol 64 (5) ◽

pp. 773-783 ◽

Cited By ~ 4

Author(s):

Shaobin Wang ◽

Zhoupeng Ren

Keyword(s):

Spatial Analysis ◽

Mortality Rate ◽

Life Expectancy ◽

Spatial Variations ◽

County Level ◽

Macroeconomic Determinants ◽

Analysis Models

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Patterns of Population and Urban Growth in Southwest Europe: 1920-2010

Journal of Urban History ◽

10.1177/0096144217726974 ◽

2017 ◽

Vol 43 (6) ◽

pp. 1021-1040 ◽

Cited By ~ 4

Author(s):

Cathy Chatel ◽

Mateu Morillas-Torné ◽

Albert Esteve ◽

Jordi Martí-Henneberg

Keyword(s):

Regression Model ◽

Social Organization ◽

Iberian Peninsula ◽

Urban Growth ◽

Local Level ◽

Population Data ◽

Population Geography ◽

Urbanization Process ◽

Geographic Factors ◽

Population Concentration

This work seeks to measure, locate, and explain changes in the distribution of population and urban growth in the territory formed by France, Italy, and the Iberian Peninsula between 1920 and 2010. This is based on population data of more than fifty-six thousand local units obtained from population censuses: the Geokhoris database that we built. Our starting viewpoint is that it is only possible to understand the extent of the urbanization process within the context of the evolution of all of the municipalities. The description of the distribution and growth of population at the local level shows the population concentration in the various urban agglomerations, and, since 1970, a relative deconcentration and extension of the cities. Within this context, a regression model helped us to identify the geographic factors that correlate with these fundamental transformations in population geography, which were also indicative of new forms of social organization within the territory.

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Urban Growth: From pixel to reality

Abstracts of the ICA ◽

10.5194/ica-abs-1-353-2019 ◽

2019 ◽

Vol 1 ◽

pp. 1-1

Author(s):

Shyamantha Subasinghe

Keyword(s):

Pattern Recognition ◽

Urban Growth ◽

Growth Pattern ◽

Open Space ◽

Spatial Configuration ◽

Urban Land ◽

Growth Patterns ◽

Zone Model ◽

Spatial Pattern Analysis ◽

Ancillary Data

Abstract. Urban growth is a complex process created through the interaction of human and environmental conditions. The spatial configuration and dynamic process of urban growth is an important topic in contemporary geographical studies (Thapa and Murayama, 2010). However, urban growth pattern recognition is a challengeable task and it has become one of the major fields in Cartography. Since classical era of cartography, several methods have been employed in modelling and urban growth pattern recognition. It shows that there is no agreement among cartographer or any other spatial scientists on how to map the diverse patterns of urban growth.Typical urban theories such as von Thünen’s (1826) bid-rent theory, Burgess’s (1925) concentric zone model, Christaller’s (1933) central place theory, and Hoyt’s (1939) sector model explain the urban structure in different manner. Most of them do not contribute to visualize the urban growth pattern spatiotemporally. Recently, by addressing this limitations, several sophisticated methods are used in urban growth visualization. Among them, morphological spatial pattern analysis (MSPA) is one of emerging raster data analysis methods which allows us to integrate neighbourhood interaction rules in urban growth pattern recognition and visualization. Angel et al. (2010) developed urban land classification (urban, suburban, rural, fringe open space, exterior open space, and rural open space) based on built and non-built land categories and detected three major types of urban growth (infill, extension, and leapfrog). However, developing urban land classifications using binary land use type and recognising only three types of urban growth pattern may be insufficient due to the existence of a higher complexity of urban growth. In such context, the present study introduce a geovisualization approach to map spatial patterns of urban growth using multiple land categories and develops three sub-levels of urban growth pattern for each major urban growth pattern.The entire process of urban growth pattern recognition developed in this study can be summarized into three steps (Figure 1): (1) urban land mapping &ndash; Landsat imageries representing two time points (2001 and 2017) were classified into two land categories (built and non-built) and developed into multiple classes using ancillary data, (2) recognizing three major patterns of urban growth (infill, extension, and leapfrog) &ndash; the raster overlay method based on neighbourhood interaction rules, (3) development of sublevels of urban growth &ndash; major three patterns were further developed and visualized nine urban growth patterns, namely low infill (LI), moderate infill (MI), high infill (HI), low extension (LE), moderate extension (ME), high extension (HE), low leapfrog (LL), moderate leapfrog (ML), and high leapfrog (HL). The developed procedure of this study in urban growth pattern recognition was tested using a case study of Colombo metropolitan area, Sri Lanka.

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Spatiotemporal simulation of urban growth patterns using agent-based modeling: The case of Tehran

Cities ◽

10.1016/j.cities.2013.01.005 ◽

2013 ◽

Vol 32 ◽

pp. 33-42 ◽

Cited By ~ 100

Author(s):

Jamal Jokar Arsanjani ◽

Marco Helbich ◽

Eric de Noronha Vaz

Keyword(s):

Urban Growth ◽

Agent Based Modeling ◽

Growth Patterns ◽

Agent Based ◽

Spatiotemporal Simulation

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Riesgos socioambientales derivados de la pérdida de servicios ecosistémicos: el caso de Ecatepec de Morelos, Estado de México

10.22201/fesa.rdp.2021.3.03 ◽

2021 ◽

pp. 32-53

Author(s):

Omar Rojas García

Keyword(s):

Quality Of Life ◽

Urban Growth ◽

Complex Variables ◽

Medium Term ◽

Conservation Areas ◽

High Slope ◽

Analysis Methodology ◽

Ecological Conservation ◽

Environmental Risk Analysis

This paper was originated in an investigation carried out in the Municipality of Ecatepec de Morelos in the period from October 2019 to March 2020, and which served as support for the update of the Municipal Urban Development Plan 2020 for the same municipality. The purpose is to recognize the socio-environmental factors that drive the construction of human settlements in ecological conservation areas and that, in the medium term, alter the surrounding ecosystems and increase their vulnerability to geological and hydrometeorological phenomena. Through an environmental risk analysis methodology, the socio-environmental impacts generated by irregular settlements on ecological conservation areas are analyzed, as the houses are located in areas of high slope, it makes them more vulnerable to the phenomena mencioned. Even these areas are accessible to certain sectors of the population, in terms of rent or purchase of housing, such practices are usually illegal, and bring with them the deterioration of the existing natural vegetation, in addition to the loss of ecosystem services derived from the unplanned urban growth. These invasions correspond to a permanent process that includes complex variables, such as the deterioration of the quality of life, economic insufficiency to satisfy needs and in a synergistic way, generates social problems such as insecurity and violence.

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