Distance to the Scaling Law: A Useful Approach for Unveiling Relationships between Crime and Urban Metrics

We report on a quantitative analysis of relationships between the number of homicides, population size and ten other urban metrics. By using data from Brazilian cities, we show that well-defined average scaling laws with the population size emerge when investigating the relations between population and number of homicides as well as population and urban metrics. We also show that the fluctuations around the scaling laws are log-normally distributed, which enabled us to model these scaling laws by a stochastic-like equation driven by a multiplicative and log-normally distributed noise. Because of the scaling laws, we argue that it is better to employ logarithms in order to describe the number of homicides in function of the urban metrics via regression analysis. In addition to the regression analysis, we propose an approach to correlate crime and urban metrics via the evaluation of the distance between the actual value of the number of homicides (as well as the value of the urban metrics) and the value that is expected by the scaling law with the population size. This approach has proved to be robust and useful for unveiling relationships/behaviors that were not properly carried out by the regression analysis, such as the non-explanatory potential of the elderly population when the number of homicides is much above or much below the scaling law, the fact that unemployment has explanatory potential only when the number of homicides is considerably larger than the expected by the power law, and a gender difference in number of homicides, where cities with female population below the scaling law are characterized by a number of homicides above the power law.     

Urban scaling and its deviations: revealing the structure of wealth, innovation and crime across cities

With urban population increasing dramatically worldwide, cities are playing an increasingly critical role in human societies and the sustainability of the planet. An obstacle to effective policy is the lack of meaningful urban metrics based on a quantitative understanding of cities. Typically, linear per capita indicators are used to characterize and rank cities. However, these implicitly ignore the fundamental role of nonlinear agglomeration integral to the life history of cities. As such, per capita indicators conflate general nonlinear effects, common to all cities, with local dynamics, specific to each city, failing to provide direct measures of the impact of local events and policy. Agglomeration nonlinearities are explicitly manifested by the superlinear power law scaling of most urban socioeconomic indicators with population size, all with similar exponents (1.15). As a result larger cities are disproportionally the centers of innovation, wealth and crime, all to approximately the same degree. We use these general urban laws to develop new urban metrics that disentangle dynamics at different scales and provide true measures of local urban performance. New rankings of cities and a novel and simpler perspective on urban systems emerge. We find that local urban dynamics display long-term memory, so cities under or outperforming their size expectation maintain such (dis)advantage for decades. Spatiotemporal correlation analyses reveal a novel functional taxonomy of U.S. metropolitan areas that is generally not organized geographically but based instead on common local economic models, innovation strategies and patterns of crime.     

The statistics of urban scaling and their connection to Zipf's law

Urban scaling relations characterizing how diverse properties of cities vary on average with their population size have recently been shown to be a general quantitative property of many urban systems around the world. However, in previous studies the statistics of urban indicators were not analyzed in detail, raising important questions about the full characterization of urban properties and how scaling relations may emerge in these larger contexts. Here, we build a self-consistent statistical framework that characterizes the joint probability distributions of urban indicators and city population sizes across an urban system. To develop this framework empirically we use one of the most granular and stochastic urban indicators available, specifically measuring homicides in cities of Brazil, Colombia and Mexico, three nations with high and fast changing rates of violent crime. We use these data to derive the conditional probability of the number of homicides per year given the population size of a city. To do this we use Bayes' rule together with the estimated conditional probability of city size given their number of homicides and the distribution of total homicides. We then show that scaling laws emerge as expectation values of these conditional statistics. Knowledge of these distributions implies, in turn, a relationship between scaling and population size distribution exponents that can be used to predict Zipf's exponent from urban indicator statistics. Our results also suggest how a general statistical theory of urban indicators may be constructed from the stochastic dynamics of social interaction processes in cities.     

Urban green space availability in European cities

Urban green space (UGS) availability has become an increasingly important aspect of planning and research because of the importance of green spaces for the wellbeing of urban residents. Municipalities across the European Union (EU) use different indicators in this area. Some cities provide per-capita threshold values for urban green space (UGS); some have recommendations regarding the minimum distance to green space while others have no recommendations at all. In this study, we assess green space availability in 299 EU cities according to land use and a population data grid. The results show a diverse picture across the EU. Southern European cities show below-average availability values, which may be explained by their low forest and tree cover and reflect the history of cities in Southern Europe. Comparatively, the above-average availability values in Northern European cities are a result of not only their biophysical conditions and the presence of rich forestland in general but also of Northern European attitudes toward urban living that naturally value having forests close to home.This assessment is complemented by a detailed case study analysis of two European cities ⿿ Berlin, Germany and ſódź, Poland. Results showed that this approach's explanatory power depends on the data used, scale of interest, resolution of data and estimated threshold value. By comparing results using different datasets and threshold values, we discuss opportunities and limitations for developing indicators of green space availability. We conclude that UGS availability is an important indicator to navigate urban complexity to improve human health and wellbeing but is only one component of the intricate social-ecological interactions within cities.     

城市化景观格局对本土植物多样性的多尺度影响——以北京市顺义区为例

景观格局对植物多样性的影响已经在很多研究中得到了验证,但有关城市景观的影响仍然知之甚少。为了探究城市化景观格局对植物多样性的影响及其尺度效应,本研究在北京市顺义区调查了105个样地,计算每个样地的α和β多样性指数;并以100 m为步长,分析了100～1000 m范围内的10个尺度43个城市的景观格局指数。结果表明: 在所有尺度上,城市景观面积指数、核心类指数和边缘指数与本土植物多样性均呈负相关;形状复杂性指数在小尺度内有利于植物多样性,而面积加权复杂性指数则在较大尺度上影响明显。其他指数如城市斑块的连接性、邻近性、内聚性、破碎性和散布并列指数与本土植物多样性之间的关系轻微且不稳定。城市化强度与尺度呈负相关,与各个尺度的植物多样性呈负相关。合理将城市区域分为许多边缘简单的小斑块,能够更好地保护本土植物多样性。该研究提出了保护城市植物多样性的景观格局建议,为生态城市建设提供参考。     

Urbanization in Southeast Asia: Assessing Policy Process and Progress toward Sustainability

In investigating the relationship between urbanization and sustainability in cities of developing countries, many researchers have looked to rising incomes as a driver for environmental improvement. This article challenges the transition and evolutionary models of urban environmental development that suggest that as cities grow in per capita income, their local environmental problems will diminish. The transition model is outcomes-based, and a competing model based on greater attention to participation in setting sustainability goals and assessing the progress toward those goals is presented.
Consensus on appropriate sustainability indicators is a key element, albeit a challenging one, in the task of pursuing urban sustainability. This is due to the contested nature of the concept of sustainability and also the fact that much of the work done on sustainability has been conducted among countries or on a national scale. A brief review of health, urban transport, air quality, and sewerage indicators suggests that cities do not necessarily see more progress as the per capita income increases. Low-income cities in Southeast Asia that are performing well are likely to see a deterioration in standards with rapid economic and population growth.     

Power Law Distributions of Patents as Indicators of Innovation

The total number of patents produced by a country (or the number of patents produced per capita) is often used as an indicator for innovation. Here we present evidence that the distribution of patents amongst applicants within many countries is well-described by power laws with exponents that vary between 1.66 (Japan) and 2.37 (Poland). We suggest that this exponent is a useful new metric for studying innovation. Using simulations based on simple preferential attachment-type rules that generate power laws, we find we can explain some of the variation in exponents between countries, with countries that have larger numbers of patents per applicant generally exhibiting smaller exponents in both the simulated and actual data. Similarly we find that the exponents for most countries are inversely correlated with other indicators of innovation, such as research and development intensity or the ubiquity of export baskets. This suggests that in more advanced economies, which tend to have smaller values of the exponent, a greater proportion of the total number of patents are filed by large companies than in less advanced countries.     

Material flow analysis and material use efficiency of Brazil's mortar and concrete supply chain

Cementitious materials, mostly concrete and mortar, account for about one‐third of all materials extraction worldwide. Material flow data in this industry are still unsatisfactory, especially related to unused extraction materials, quarry wastes, and water consumption, aspects which usually are not included in environmental analysis studies. The aim of this study is to conduct a material flow analysis (MFA) of the Brazilian concrete and mortar supply chain to quantify material use efficiency (ME) and dematerialization potential. The MFA includes extraction, production, and construction stages for the following indicators: i) unused extraction; ii) quarry waste; iii) water consumption; iv) material wastage; v) raw material consumption; vi) energy carriers; and vii) atmospheric emissions. The results demonstrated that the primary raw material footprint is about 456 million metric tons (Mt) corresponding to a metabolic rate of 2.2 metric tons/capita (t/capita). After including unused extraction, quarry wastes, water consumption, and secondary materials this value increases to 4.1 t/capita corresponding to a total material consumption of 840 Mt. Concrete and mortar can be produced using two routes—mixing on site or industrial mixing. We conclude that the industrial scenario allows for dematerialization by about 8% for concrete and 24% for mortar, by mass; and the average material use efficiency is low, at about 53% for concrete and 34% for mortar.     

浙江三大城市群绿色发展效率时空分异及影响机理

提升浙江三大城市群绿色发展效率是浙江加快建成美丽中国先行示范区的重要途径之一.以三大城市群包含的41个县(市)为依托,以2000-2019年县域面板数据为样本,将超效率SBM模型与窗口分析及测度效率相结合,运用空间计量分析方法研究效率的空间分布及区域差异,并借助面板固定效应模型探索效率的差异化影响机理.结果 表明:研究...