Spatiotemporal Evolution of Urban Form and Land-Use Structure in Hangzhou, China: Evidence from Fractals

Feng, Jiao; Chen, Yanguang

doi:10.1068/b35078

Cited by 100 publications

(103 citation statements)

References 25 publications

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“…Therefore, measurement of land urbanization is as important as population urbanization. The dynamic evaluation of land urbanization focuses mainly on measuring the quantity, speed and change of land-use structures Wang and Li, 2011;Deng et al, 2009;Xu et al, 2009;Tang, 2009;Feng and Chen, 2010;Zhang et al, 2010;Dong et al, 2011). However, most of the research is based on single or limited cases, which are unfavorable for inter-city comparisons.…”

Section: Introductionmentioning

confidence: 99%

Spatial differences and driving forces of land urbanization in China

Lin

Wang

et al. 2015

J. Geogr. Sci.

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Abstract:Land urbanization plays an important supporting and restriction role in the rapid and sustainable development of urbanization in China, and it shows distinctive spatial heterogeneity. Applying urban area as the basic research unit and urban construction land area as the core indicator, this paper establishes the conceptual framework and calculation method for the quantity and rate of land urbanization process. The study evaluates the spatial differentiation pattern of absolute and relative process of land urbanization in 658 cities in China from 2000 to 2010. The spatial distribution of cities with rapid land urbanization process is discussed, and the contribution rate and its spatial heterogeneity of major land use types are examined with the aid of GIS. The main conclusions are as follows: (1) Land urbanization in China shows a clear spatial difference. The greater the city scale, the faster its land urbanization. The cities with rapid land urbanization show a significant pattern of central distribution in coastal regions and a scattered distribution in the inland regions. (2) Over the last 10 years, the average quantity of land urbanization in the 656 cities was 3.82 km 2 , the quantity of land urbanization is differentiated by administrative grade. The average rate of land urbanization was 6.89%, obviously faster than the speed of population urbanization. The rate of land urbanization reveals a pattern of differentiation between coastal and other cities. (3) In the past 10 years, the two primary land use types associated with land urbanization in China are residential and industrial, with a combined contribution rate of 52.49%. The greater the scale of the city, the more significant the driving effect of industrial land. In small-and medium-scale cities of the western and central regions, the growth of residential land is the primary driver of land urbanization, while in coastal urban agglomerations and cities on important communication axes, the growth of industrial land is the main driver. (4) Overall, urban population agglomeration, industrial growth and investment are the three drivers of land urbanization in China, but cities of different scales have different drivers.

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Section: Introductionmentioning

confidence: 99%

Spatial differences and driving forces of land urbanization in China

Lin

Wang

et al. 2015

J. Geogr. Sci.

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“…Two types of box counting can be applied to fractal dimension estimation of cities [31,42]: one is to fix the largest box [46], and the other is to unfix the largest box [44]. In the former way, the size and shape of the first level box do no change for different years; in the latter way, the size and shape of the largest box change with urban growth in different years.…”

Section: Results and Findings Based On Fixed Box Methodsmentioning

confidence: 99%

“…The spatial patterns of Hangzhou's urban land use bear fractal structure, and can be characterized with fractal dimension (Figure 6). Using the functional box-counting method, Feng and Chen [44] once calculated the capacity dimension of Hangzhou's urban form in four different years (1949, 1959, 1980, and 1996). Different from the case of Beijing city, the variable boxes were employed to make spatial measurement for suiting city sizes in different years.…”

Section: Observational Evidences and Findings Based On Unfixed Box Mementioning

confidence: 99%

“…This method was originally adopted [43] to analyze radar rain data, and Chen [26] improved this method in urban studies by replacing the largest box (the first level box) with arbitrary area with the largest box with a measure area of an urban system. In fact, the functional box-counting method can be termed Rectangle Space Subdivision (RSS) method [42,44]. The geometrical basis of RSS is the recursive subdivision of space and the cascade structure of hierarchies [30,45].…”

Section: Study Area Data and Approachesmentioning

confidence: 99%

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Understanding the Fractal Dimensions of Urban Forms through Spatial Entropy

Chen

Wang

Feng

2017

Entropy

Self Cite

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Abstract:The spatial patterns and processes of cities can be described with various entropy functions. However, spatial entropy always depends on the scale of measurement, and it is difficult to find a characteristic value for it. In contrast, fractal parameters can be employed to characterize scale-free phenomena and reflect the local features of random multi-scaling structure. This paper is devoted to exploring the similarities and differences between spatial entropy and fractal dimension in urban description. Drawing an analogy between cities and growing fractals, we illustrate the definitions of fractal dimension based on different entropy concepts. Three representative fractal dimensions in the multifractal dimension set, capacity dimension, information dimension, and correlation dimension, are utilized to make empirical analyses of the urban form of two Chinese cities, Beijing and Hangzhou. The results show that the entropy values vary with the measurement scale, but the fractal dimension value is stable is method and study area are fixed; if the linear size of boxes is small enough (e.g., <1/25), the linear correlation between entropy and fractal dimension is significant (based on the confidence level of 99%). Further empirical analysis indicates that fractal dimension is close to the characteristic values of spatial entropy. This suggests that the physical meaning of fractal dimension can be interpreted by the ideas from entropy and scaling and the conclusion is revealing for future spatial analysis of cities.

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“…The relations between the fractal dimension of urban form and landscape patterns were discussed based on fractal theory and urban land-use maps [51,52].Terzi and Kaya [53] found that the fractal dimension of urban areas presented a positive correlation with the urban sprawl index. In this research, it indicated that some landscape metrics showed positive correlations with the fractal dimension (LSI, TE), and some showed negative correlations (ED, CI).…”

Section: Factors Associated With Built-up Land Expansion Patternsmentioning

confidence: 99%

Characterizing Factors Associated with Built-Up Land Expansion in Urban and Non-Urban Areas from a Morphological Perspective

Zhang

Xiao

et al. 2017

Sustainability

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Abstract:In this paper, built-up land expansion patterns and the associated factors were characterized in urban and non-urban areas across the Wen-Tai region of eastern China. Fractal dimension can be used as a reliable indicator of the complexity of built-up land form, and the increasing trend of fractal dimension indicated a more complex, dispersed pattern of built-up land in urban areas. Spatial regression models were quantitatively implemented to identify the indicators influencing the variation of fractal dimensions. Our findings suggested that the fractal dimension of built-up land forms was positively correlated to the patch density and elevation when built-up land expansion was more concentrated. Both landscape shape index and Gross Domestic Product (GDP) were positively correlated with fractal dimension in urban areas, and total edge, edge density, and connective index had impacts on fractal dimension in non-urban areas. Slope and agricultural population also showed an influence on fractal dimension. This study provided a new way for urban studies in interpreting the complex interactions between fractal dimension and related factors. The combined approach of fractal dimension and spatial analysis can provide the government planners with valuable information that can be efficiently used to realize the influences of land use policies in urban and non-urban areas.

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Spatiotemporal Evolution of Urban Form and Land-Use Structure in Hangzhou, China: Evidence from Fractals

Cited by 100 publications

References 25 publications

Spatial differences and driving forces of land urbanization in China

Spatial differences and driving forces of land urbanization in China

Understanding the Fractal Dimensions of Urban Forms through Spatial Entropy

Characterizing Factors Associated with Built-Up Land Expansion in Urban and Non-Urban Areas from a Morphological Perspective

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