Abstract
As one of the few generalities in ecology, Taylor’s power law admits a power function relationship V = aMb between the variance V and mean number M of organisms in a quadrat. We examine the spatial distribution data of seven urban service facilities in 37 major cities in China, and find that Taylor’s Law is validated among all types of facilities. Moreover, Taylor’s Law is robust if we shift the observation window or vary the size of the quadrats. The exponent b increases linearly with the logarithm of the quadrat size, i.e. b(s) = b0 + A log (s). Furthermore, the ANOVA test indicates that b takes distinct values for different facilities in different cities. We decompose b into two different factors, a city-specific factor and a facility-specific factor (FSF). Variations in b can be explained to a large extent by the differences between cities and types of facilities. Facilities are more evenly distributed in larger and more developed cities. Competitive interchangeable facilities (e.g. pharmacy), with larger FSFs and smaller bs, are less aggregated than complementary services (e.g. restaurants).
Highlights
Bettencourt & West [1] state: ‘ . . . cities are remarkably robust: success, once achieved, is sustained for several decades or longer, thereby setting a city on a long run of creativity and prosperity’ (p. 913)
In order to study these two key factors contributing to the difference among bs and explore the mechanism underlying the distribution of urban facilities, we decompose the inverse of exponent b by examining their contribution to the numbers of facilities located in a study region
Based on the dataset of spatial coordinates of the seven types of facilities in 37 major cities in China, we explore the micro-structure of these cities and study the characteristics of the distribution of urban facilities
Summary
Bettencourt & West [1] state: ‘ . . . cities are remarkably robust: success, once achieved, is sustained for several decades or longer, thereby setting a city on a long run of creativity and prosperity’ (p. 913). Empirical evidence is clearly needed if we can observe how b varies among different species at the same location, and how b varies for the same species across different locations In this aspect, our study might shed light on the meaning of b by exploring the potential mean – variance relationship of Taylor’s Law in the spatial distribution of urban facilities. The first tier four cities rank in the top four in the CSF values due to the high overall facility density in these cities, while restaurant tops the overall aggregation level due to their complementary nature These findings are consistent with our intuitive understandings of these cities and urban facilities.
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