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A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl.

ABSTRACT: The phenomenon of urban sprawl has received much attention. Accurately confirming the spatial expansion degree of urban sprawl (SEDUS) is a prerequisite to controlling urban sprawl. However, there is no reliable metric to accurately measure SEDUS. In this paper, based on binary entropy, we propose a new index named the spatial expansion degree index (SEDI), to overcome this difficulty. The study shows that the new index can accurately determine SEDUS and, compared with other commonly used measures, the new index has an obvious advantage in measuring SEDUS. The new index belongs to the second-order metrics of point pattern analysis, and greatly extends the concept of entropy. The new index can also be applied to other spatial differentiation research from a broader perspective. Although the new index is influenced by the scaling problem, because of small differences between different scales, given that the partition scheme in the research process is the same, the new index is a quite robust method for measuring SEDUS.

SUBMITTER: Chen Z

PROVIDER: S-EPMC7513086 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature

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A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl.

Chen Zhen Z Zhou Yinkang Y Jin Xiaobin X

Entropy (Basel, Switzerland) 20180727 8

The phenomenon of urban sprawl has received much attention. Accurately confirming the spatial expansion degree of urban sprawl (SEDUS) is a prerequisite to controlling urban sprawl. However, there is no reliable metric to accurately measure SEDUS. In this paper, based on binary entropy, we propose a new index named the spatial expansion degree index (SEDI), to overcome this difficulty. The study shows that the new index can accurately determine SEDUS and, compared with other commonly used measur ...[more]

PMID: 33265648

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Project description:Urban growth is a major threat to biodiversity conservation at the global scale. Its impacts are expected to be especially detrimental when it sprawls into the landscape and reaches sites of high conservation value due to the species and ecosystems they host, such as protected areas. I analyzed the degree of urbanization (i.e., urban cover and growth rate) from 2006 to 2015 in protected sites in the Natura 2000 network, which, according to the Habitats and Birds Directives, harbor species and habitats of high conservation concern in Europe. I used data on the degree of land imperviousness from COPERNICUS to calculate and compare urban covers and growth rates inside and outside Natura 2000. I also analyzed the relationships of urban cover and growth rates with a set of characteristics of Natura sites. Urban cover inside Natura 2000 was 10 times lower than outside (0.4% vs. 4%) throughout the European Union. However, the rates of urban growth were slightly higher inside than outside Natura 2000 (4.8% vs. 3.9%), which indicates an incipient urban sprawl inside the network. In general, Natura sites affected most by urbanization were those surrounded by densely populated areas (i.e., urban clusters) that had a low number of species or habitats of conservation concern, albeit some member states had high urban cover or growth rate or both in protected sites with a large number of species or habitats of high conservation value. Small Natura sites had more urban cover than large sites, but urban growth rates were highest in large Natura sites. Natura 2000 is protected against urbanization to some extent, but there is room for improvement. Member states must enact stricter legal protection and control law enforcement to halt urban sprawl into protected areas under the greatest pressure from urban sprawl (i.e., close to urban clusters). Such actions are particularly needed in Natura sites with high urban cover and growth rates and areas where urbanization is affecting small Natura sites of high conservation value, which are especially vulnerable and concentrated in the Mediterranean region.

Project description:Urban sprawl has become the main pattern of spatial expansion in many large cities in China, and its ecological and environmental effects profoundly impact Chinese urban development. In this paper, nighttime light data and statistical yearbook data are adopted as basic data sources to simulate the evolution trend of the urban sprawl in the upper Yangtze River (UYR), China. First, the urban sprawl index (USI) is employed to assess the level of urban sprawl and to determine the characteristics of urban sprawl under different scales. Second, the spatial autocorrelation model is applied to reveal the spatial pattern change characteristics of urban sprawl from 1992 to 2015. Third, a scenario analysis model of urban sprawl is constructed to simulate the evolution trend of the urban sprawl under different scenarios. Finally, based on the Geodetector, the influence of factors and factor interactions influencing urban sprawl in different time periods is analyzed. The results yield the following main conclusions: (1) The urban sprawl in the UYR first intensifies and then stabilizes over time. The number of cities with high USI in Sichuan province, medium cities, and Chengdu-Chongqing urban agglomeration increases over time, indicating that urban sprawl is intensifying in these areas. (2) The urban sprawl hot spots experience a pattern transformation process of point-like expansion-point-ring expansion-point-axis expansion-axis radiation. (3) Under the scenarios with different scales, the urban land sprawl in large cities is the highest, accounting for more than 47% of the UYR. Urban land sprawl extent in the Chengdu-Chongqing urban agglomeration is the highest, accounting for more than 51% of the UYR. The cities exhibiting the highest sprawl are Chongqing, Lijiang, and Kunming, accounting for 25.84%, 7.37%, and 5.11%, respectively, of the UYR. (4) In the different time scenario simulations, the urban land in large cities exhibits the highest sprawl, accounting for approximately 48.16% of the UYR. The urban land in the Chengdu-Chongqing urban agglomeration demonstrates the highest sprawl, accounting for 50.92% of the UYR. (5) From 1996 to 2002, the driver with the highest influence on urban sprawl was secondary industry share of GDP, with a q-statistic of 0.616. From 2009 to 2015, the driver with the highest influence on urban sprawl was green space per capita with a q-statistic of 0.396.

Dataset Information

A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl.

Publications

A Novel Index Based on Binary Entropy to Confirm the Spatial Expansion Degree of Urban Sprawl.

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