Scale-Adjusted Metrics for Predicting the Evolution of Urban Indicators and Quantifying the Performance of Cities

More than a half of world population is now living in cities and this number is expected to be two-thirds by 2050. Fostered by the relevancy of a scientific characterization of cities and for the availability of an unprecedented amount of data, academics have recently immersed in this topic and one of the most striking and universal finding was the discovery of robust allometric scaling laws between several urban indicators and the population size. Despite that, most governmental reports and several academic works still ignore these nonlinearities by often analyzing the raw or the per capita value of urban indicators, a practice that actually makes the urban metrics biased towards small or large cities depending on whether we have super or sublinear allometries. By following the ideas of Bettencourt et al. [PLoS ONE 5 (2010) e13541], we account for this bias by evaluating the difference between the actual value of an urban indicator and the value expected by the allometry with the population size. We show that this scale-adjusted metric provides a more appropriate/informative summary of the evolution of urban indicators and reveals patterns that do not appear in the evolution of per capita values of indicators obtained from Brazilian cities. We also show that these scale-adjusted metrics are strongly correlated with their past values by a linear correspondence and that they also display crosscorrelations among themselves. Simple linear models account for 31%–97% of the observed variance in data and correctly reproduce the average of the scale-adjusted metric when grouping the cities in above and below the allometric laws. We further employ these models to forecast future values of urban indicators and, by visualizing the predicted changes, we verify the emergence of spatial clusters characterized by regions of the Brazilian territory where we expect an increase or a decrease in the values of urban indicators.     

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.     

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.     

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.     

Ranking of invasive spread through urban green areas in the world’s 100 most populous cities

Urban landscapes are highly fragmented (leading to the extinction of native species) as well as transformed and disturbed (creating novel environments). Such conditions provide non-native species with opportunities to establish and spread through “urban green areas” (UGAs). UGAs can serve as stepping stones for many alien species to recruit and may become sources of propagules to launch invasions in adjoining natural ecosystems. There is great diversity in the spatial structures of UGAs worldwide; these are determined by the city’s level of development, human density, urban planning policy, and history. We explore the invasion risks of, and the potential of invasive spread in, UGAs in the world’s 100 most populous cities (in 40 countries). Based on maps of enhanced vegetation index at 250 m resolution over the extent of 25 by 25 km for each city centre, we simulate the invasion and spread of a reference species (a virtual ruderal invasive species) from the city centre into surrounding urban or rural areas. Doing so allowed us to provide an objective baseline for comparing urban susceptibility to such invasions across diverse cultures, histories and societies. We derive the global ranking of invasive spread potential for each city based on the rate of spread of the reference species, and the ranking of 40 countries, based on the average rate of spread in their cities. We explore correlates of spread rates after 100 time steps (years) by examining the roles of climate (mean annual temperature and rainfall), human demography (city population size and growth rate), and socio-economic indicators [human footprint, human development index and gross domestic product (GDP) per capita]. Small city population size and high GDP per capita are the only significant predictors of high potential for invasive spread. Among the G20 countries, Canada, South Korea, South Africa, France, USA and Brazil all feature in the top-10 countries, and Atlanta, Washington, D.C. and Dallas in the USA, Chittagong in Bangladesh, Toronto in Canada and Brasilia in Brazil are listed among the top 10 cities overall. Our results can serve as a global baseline assessment of invasive spread risks through UGAs, and call for improved protocols for monitoring, planning and management of UGAs.     

Surveying the Environmental Footprint of Urban Food Consumption

Assessments of urban metabolism (UM) are well situated to identify the scale, components, and direction of urban and energy flows in cities and have been instrumental in benchmarking and monitoring the key levers of urban environmental pressure, such as transport, space conditioning, and electricity. Hitherto, urban food consumption has garnered scant attention both in UM accounting (typically lumped with “biomass”) and on the urban policy agenda, despite its relevance to local and global environmental pressures. With future growth expected in urban population and wealth, an accounting of the environmental footprint from urban food demand (“foodprint”) is necessary. This article reviews 43 UM assessments including 100 cities, and a total of 132 foodprints in terms of mass, carbon footprint, and ecological footprint and situates it relative to other significant environmental drivers (transport, energy, and so on) The foodprint was typically the third largest source of mass flows (average is 0.8 tonnes per capita per annum) and carbon footprint (average is 2.1 tonnes carbon dioxide equivalents per capita per annum) in the reviewed cities, whereas it was generally the largest driver of urban ecological footprints (average is 1.2 global hectares per capita per annum), with large deviations based on wealth, culture, and urban form. Meat and dairy are the primary drivers of both global warming and ecological footprint impacts, with little relationship between their consumption and city wealth. The foodprint is primarily linear in form, producing significant organic exhaust from the urban system that has a strong, positive correlation to wealth. Though much of the foodprint is embodied within imported foodstuffs, cities can still implement design and policy interventions, such as improved nutrient recycling and food waste avoidance, to redress the foodprint.     

中国城市低碳发展水平评估方法研究

城市低碳发展水平评估对推动城市可持续发展,提高城市应对气候变化能力具有重要意义。基于低碳城市理念和内涵,构建了由6类(碳排放、经济发展、社会进步、交通、人居环境和自然环境)、13个具体指标组成的城市低碳发展评价指标体系及综合评价指数,并结合中国35个城市2010—2015年社会经济发展数据,对参评城市的低碳发展水平及趋势进行评价与分析。结果表明:多数参评城市的低碳发展水平呈现上升的趋势,其中,城市低碳发展水平最高和最低城市名单无明显变化,且深圳市在2010年和2015年均为低碳发展水平最高的城市。与2010年相比,杭州市、银川市、郑州市、石家庄市和昆明市的城市低碳发展指数相对持平,而成都市、长沙市、合肥市和大连市有所下降。城市低碳发展水平较低可能是由于城市碳排放、经济、社会、交通、人居环境和自然环境等方面之间协调发展程度不够造成的。最后,对如何提高我国城市低碳发展水平给出了对策和建议。     

Impact of the Economic Structure of Cities on Urban Scaling Factors: Implications for Urban Material and Energy Flows in China

We explore the population‐scaling and gross domestic product (GDP)‐scaling relationships of material and energy flow (MEF) parameters in different city types based on economic structure. Using migration‐corrected population data, we classify 233 Chinese city propers (Shiqu) as “highly industrial” (share of secondary GDP exceeds 63.9%), “highly commercial” (share of tertiary GDP exceeds 52.6%), and “mixed‐economy” (the remaining cities). We find that, first, the GDP population‐scaling factors differ in the different city types. Highly commercial and mixed‐economy cities exhibit superlinear GDP population‐scaling factors greater than 1, whereas highly industrial cities are sublinear. Second, GDP scaling better correlates with city‐wide MEF parameters in Chinese cities; these scaling relationships also show differences by city typology. Third, highly commercial cities are significantly different from others in demonstrating greater average per capita household income creation relative to per capita GDP. Further, highly industrial cities show an apparent cap in population. This also translates to lower densities in highly industrial cities compared to other types, showing a size effect on urban population density. Finally, a multiple variable regression of total household electricity showed significant and positive correlation with population, income effect, and urban form effect. With such multivariate modeling, the apparent superlinearity of household electricity use with respect to population is no longer observed. Our study enhances understanding of MEFs associated with Chinese cities and provides new insights into the patterns of scaling observed in different city types by economic structure. Results recommend dual scaling by GDP and by population for MEF parameters and suggest caution in applying universal scaling factors to all cities in a country.     

Universities Scale Like Cities

Recent studies of urban scaling show that important socioeconomic city characteristics such as wealth and innovation capacity exhibit a nonlinear, particularly a power law scaling with population size. These nonlinear effects are common to all cities, with similar power law exponents. These findings mean that the larger the city, the more disproportionally they are places of wealth and innovation. Local properties of cities cause a deviation from the expected behavior as predicted by the power law scaling. In this paper we demonstrate that universities show a similar behavior as cities in the distribution of the ‘gross university income’ in terms of total number of citations over ‘size’ in terms of total number of publications. Moreover, the power law exponents for university scaling are comparable to those for urban scaling. We find that deviations from the expected behavior can indeed be explained by specific local properties of universities, particularly the field-specific composition of a university, and its quality in terms of field-normalized citation impact. By studying both the set of the 500 largest universities worldwide and a specific subset of these 500 universities -the top-100 European universities- we are also able to distinguish between properties of universities with as well as without selection of one specific local property, the quality of a university in terms of its average field-normalized citation impact. It also reveals an interesting observation concerning the working of a crucial property in networked systems, preferential attachment.     

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...     

中国城市生态与经济社会协同性评估

为认识城市经济社会和生态的协同特征,本研究基于城市人均绿地面积、人均GDP和人均期望寿命等构建城市生态与经济社会功能协同性指标评价体系,建立城市生态与经济社会协同性指数评价方法。通过比较中国35个典型城市的协同性指数与功能综合得分,分析了中国城市协同性特征,并按照城市规模、行政区类型分析城市协同性差异和城市功能综合得分差异,对协同水平进行分类。结果表明: 2016年,中国35个城市生态与经济社会平均协同性指数为28.79,协同性最强城市的协同性指数为3.83,最弱的城市为63.04,表明中国城市协同性不高且城市间差异较大。协同性指数、城市经济功能、社会功能与城市人口规模、经济规模呈显著正相关。不同人口规模、经济规模、不同行政职能城市之间协同性指数差异具有显著性。中国城市化总体仍处于功能失衡的发展阶段,城市发展有利于各城市功能性提高但并未有效提升协同性,生态功能的高低显著影响城市协同性,城市生态功能不高是当前中国城市协同性高低的主要制约因素。     

Credit or debit? Resource input changes population dynamics of city-slicker birds

The underlying evolutionary mechanisms of urban bird populations have hardly been studied. High food density and low predation risk serve to explain the global pattern of extremely high urban bird population densities. Both these bottom-up and top-down effects are paradoxical since the per capita amount of food is small due to competition, and domestic predator density is high in cities. The bottom-up paradox can be resolved by taking into account the high food resource-predictability in cities. Concerning the top-down effect, recent studies suggest that at least when it comes to nest predation the effect of cats is minor. I suggest that the combination of high food predictability and low predation risk in cities alter bird foraging behaviour, which in turn affects population dynamics. In terms of density, the result is that bird populations exceed the carrying capacity of the urban environment, costing heavily on body condition and/or life span. Under such conditions the population should consist of a few winners and many losers. Only the winners have sufficient access to food resources and the opportunity to reproduce. The highly predictable continuous input of food in the urban environment allows them to "live on their credit". They may trade off between offspring body condition and clutch size. In the lack of predation, the losers among the fledglings may survive for a relatively long period, getting just enough energy to survive. Though they may never become healthy enough to reproduce, they will have a major contribution to the observed population density. Results of several case studies seem to support the credit card hypothesis and suggest that it can serve as a general rule for the evolution of animal populations and communities in highly predictable human managed environments.     

Open Space Loss and Land Inequality in United States' Cities, 1990–2000

Urban growth reduces open space in and around cities, impacting biodiversity and ecosystem services. Using land-cover and population data, we examined land consumption and open space loss between 1990 and 2000 for all 274 metropolitan areas in the contiguous United States. Nationally, 1.4 million ha of open space was lost, and the amount lost in a given city was correlated with population growth (r(272) = 0.85, P<0.001). In 2000, cities varied in per capita land consumption by an order of magnitude, from 459 m²/person in New York to 5393 m²/person in Grand Forks, ND. The per capita land consumption (m²/person) of most cities decreased on average over the decade from 1,564 to 1,454 m ²/person, but there was substantial regional variation and some cities even increased. Cities with greater conservation funding or more reform-minded zoning tended to decrease in per capita land consumption more than other cities. The majority of developed area in cities is in low-density neighborhoods housing a small proportion of urban residents, with Gini coefficients that quantify this developed land inequality averaging 0.63. Our results suggest conservation funding and reform-minded zoning decrease per capita open space loss.     

Forest and the city: A multivariate analysis of peri-urban forest land cover patterns in 283 European metropolitan areas

Heterogeneous definitions of urban areas and poorly homogenized forest data at the country scale have hampered the comparative assessment of peri-urban forest structure in developed countries. The present study investigates selected landscape characteristics of peri-urban forests in 283 metropolitan areas in Europe controlling for the role of the local context and regional suburbanization trends. Using landscape metrics derived from Urban Atlas maps (a Copernicus/GMES initiative providing a comprehensive land-use assessment of European cities >100,000 inhabitants), significant differences in peri-urban forest structure were detected under five European regions. Specific class metrics (percent forest area, mean patch size, perimeter-to-area ratio) were correlated with urban morphology, landscape and territorial indicators. On average, forest cover is larger in northern and southern European metropolitan areas. Forest patch size increases from western to eastern Europe, with more regular patch shapes in central and eastern regions and less regular shapes in the rest of Europe. Forest class area increases with the area of discontinuous, medium-density settlements. Forest patch size increases with the average patch size of discontinuous dense urban fabric. Our evidence outlines a ‘sprawl model' shaping fringe landscapes characterized by discontinuous urban settlements mixed with fragmented – but possibly well protected – forest patches.     

Endless Urban Growth? On the Mismatch of Population,Household and Urban Land Area Growth and Its Effects on the Urban Debate

In European cities, the rate of population growth has declined significantly, while the number of households has increased. This increase in the number of households is associated with an increase in space for housing. To date, the effects of both a declining population and decreasing household numbers remain unclear. In this paper, we analyse the relationship between population and household number development in 188 European cities from 1990–2000 and 2000–2006 to the growth of urban land area and per capita living space. Our results support a trend toward decreasing population with simultaneously increasing household number. However, we also found cites facing both a declining population and a decreasing household number. Nevertheless, the urban land area of these “double-declining” cities has continued to spread because the increasing per capita living space counteracts a reduction in land consumption. We conclude that neither a decline in population nor in household number “automatically” solve the global problem of land consumption.     

Measles on the edge: coastal heterogeneities and infection dynamics

Mathematical models can help elucidate the spatio-temporal dynamics of epidemics as well as the impact of control measures. The gravity model for directly transmitted diseases is currently one of the most parsimonious models for spatial epidemic spread. This model uses distance-weighted, population size-dependent coupling to estimate host movement and disease incidence in metapopulations. The model captures overall measles dynamics in terms of underlying human movement in pre-vaccination England and Wales (previously established). In spatial models, edges often present a special challenge. Therefore, to test the model's robustness, we analyzed gravity model incidence predictions for coastal cities in England and Wales. Results show that, although predictions are accurate for inland towns, they significantly underestimate coastal persistence. We examine incidence, outbreak seasonality, and public transportation records, to show that the model's inaccuracies stem from an underestimation of total contacts per individual along the coast. We rescue this predicted 'edge effect' by increasing coastal contacts to approximate the number of per capita inland contacts. These results illustrate the impact of 'edge effects' on epidemic metapopulations in general and illustrate directions for the refinement of spatiotemporal epidemic models.     

Rural to Urban Population Density Scaling of Crime and Property Transactions in English and Welsh Parliamentary Constituencies

Urban population scaling of resource use, creativity metrics, and human behaviors has been widely studied. These studies have not looked in detail at the full range of human environments which represent a continuum from the most rural to heavily urban. We examined monthly police crime reports and property transaction values across all 573 Parliamentary Constituencies in England and Wales, finding that scaling models based on population density provided a far superior framework to traditional population scaling. We found four types of scaling: i) non-urban scaling in which a single power law explained the relationship between the metrics and population density from the most rural to heavily urban environments, ii) accelerated scaling in which high population density was associated with an increase in the power-law exponent, iii) inhibited scaling where the urban environment resulted in a reduction in the power-law exponent but remained positive, and iv) collapsed scaling where transition to the high density environment resulted in a negative scaling exponent. Urban scaling transitions, when observed, took place universally between 10 and 70 people per hectare. This study significantly refines our understanding of urban scaling, making clear that some of what has been previously ascribed to urban environments may simply be the high density portion of non-urban scaling. It also makes clear that some metrics undergo specific transitions in urban environments and these transitions can include negative scaling exponents indicative of collapse. This study gives promise of far more sophisticated scale adjusted metrics and indicates that studies of urban scaling represent a high density subsection of overall scaling relationships which continue into rural environments.     

基于能值分析的福州与厦门城市生态系统比较研究

能值分析方法(Emergy Analysis)为综合评价城市复合生态系统提供了新的手段和方法。以福州和厦门为研究对象,对其城市各种生态流进行计算和归类,建立了相应的城市复合生态系统与可持续发展能值指标,并对两城市复合生态系统中自然、经济、社会三大子系统进行了综合评价与对比分析。结果表明:厦门在经济发展水平和社会人均福利方面优于福州,在生态安全和可持续发展能力方面落后于福州。从能值角度出发,福州应加快城市基础设施建设,加强城郊地区能值反馈,科学引导人口转移;厦门应积极发展绿色产业,降低生产能耗物耗,提高废弃物循环利用率;两城市应加强区际资源互补和消除技术壁垒,促成两城市互补、互利、可持续发展。     

Estimating the per‐capita contribution of habitats and pathways in a migratory network: a modelling approach

Every year, migratory species undertake seasonal movements along different pathways between discrete regions and habitats. The ability to assess the relative demographic contributions of these different habitats and pathways to the species’ overall population dynamics is critical for understanding the ecology of migratory species, and also has practical applications for management and conservation. Metrics for assessing habitat contributions have been well‐developed for metapopulations, but an equivalent metric is not currently available for migratory populations. Here, we develop a framework for estimating the demographic contributions of the discrete habitats and pathways used by migratory species throughout the annual cycle by estimating the per capita contribution of cohorts using these locations. Our framework accounts for seasonal movements between multiple breeding and non‐breeding habitats and for both resident and migratory cohorts. We illustrate our framework using a hypothetical migratory network of four habitats, which allows us to better understand how variations in habitat quality affect per capita contributions. Results indicate that per capita contributions for any habitat or pathway are dependent on habitat‐specific survival probabilities in all other areas used as part of the migratory circuit, and that contribution metrics are spatially linked (e.g. reduced survival in one habitat also decreases the contribution metric for other habitats). Our framework expands existing theory on the dynamics of spatiotemporally structured populations by developing a generalized approach to estimate the habitat‐ and pathway‐specific contributions of species migrating between multiple breeding and multiple non‐breeding habitats for a range of life histories or migratory strategies. Most importantly, it provides a means of prioritizing conservation efforts towards those migratory pathways and habitats that are most critical for the population viability of migratory species.     

The Changing Metabolism of Cities

Data from urban metabolism studies from eight metropolitan regions across five continents, conducted in various years since 1965, are assembled in consistent units and compared. Together with studies of water, materials, energy, and nutrient flows from additional cities, the comparison provides insights into the changing metabolism of cities. Most cities studied exhibit increasing per capita metabolism with respect to water, wastewater, energy, and materials, although one city showed increasing efficiency for energy and water over the 1990s. Changes in solid waste streams and air pollutant emissions are mixed.
The review also identifies metabolic processes that threaten the sustainability of cities. These include altered ground water levels, exhaustion of local materials, accumulation of toxic materials, summer heat islands, and irregular accumulation of nutrients. Beyond concerns over the sheer magnitudes of resource flows into cities, an understanding of these accumulation or storage processes in the urban metabolism is critical. Growth , which is inherently part of metabolism, causes changes in water stored in urban aquifers, materials in the building stock, heat stored in the urban canopy layer, and potentially useful nutrients in urban waste dumps.
Practical reasons exist for understanding urban metabolism. The vitality of cities depends on spatial relationships with surrounding hinterlands and global resource webs. Increasing metabolism implies greater loss of farmland, forests, and species diversity; plus more traffic and more pollution. Urban policy makers should consider to what extent their nearest resources are close to exhaustion and, if necessary, appropriate strategies to slow exploitation. It is apparent from this review that metabolism data have been established for only a few cities worldwide, and interpretation issues exist due to lack of common conventions. Further urban metabolism studies are required.