Michail Fragkias

A Meta-Analysis of Global Urban Land Expansion

The conversion of Earths land surface to urban uses is one of the most irreversible human impacts on the global biosphere. It drives the loss of farmland, affects local climate, fragments habitats, and threatens biodiversity. Here we present a meta-analysis of 326 studies that have used remotely sensed images to map urban land conversion. We report a worldwide observed increase in urban land area of 58,000 km2 from 1970 to 2000. India, China, and Africa have experienced the highest rates of urban land expansion, and the largest change in total urban extent has occurred in North America. Across all regions and for all three decades, urban land expansion rates are higher than or equal to urban population growth rates, suggesting that urban growth is becoming more expansive than compact. Annual growth in GDP per capita drives approximately half of the observed urban land expansion in China but only moderately affects urban expansion in India and Africa, where urban land expansion is driven more by urban population growth. In high income countries, rates of urban land expansion are slower and increasingly related to GDP growth. However, in North America, population growth contributes more to urban expansion than it does in Europe. Much of the observed variation in urban expansion was not captured by either population, GDP, or other variables in the model. This suggests that contemporary urban expansion is related to a variety of factors difficult to observe comprehensively at the global level, including international capital flows, the informal economy, land use policy, and generalized transport costs. Using the results from the global model, we develop forecasts for new urban land cover using SRES Scenarios. Our results show that by 2030, global urban land cover will increase between 430,000 km2 and 12,568,000 km2, with an estimate of 1,527,000 km2 more likely.

Quantifying Spatiotemporal Patterns of Urban Land-use Change in Four Cities of China with Time Series Landscape Metrics

This paper provides a dynamic inter- and intra-city analysis of spatial and temporal patterns of urban land-use change. It is the first comparative analysis of a system of rapidly developing cities with landscape pattern metrics. Using ten classified Landsat Thematic Mapper images acquired from 1988 to 1999, we quantify the annual rate of urban land-use change for four cities in southern China. The classified images were used to generate annual maps of urban extent, and landscape metrics were calculated and analyzed spatiotemporally across three buffer zones for each city for each year. The study shows that for comprehensive understanding of the shapes and trajectories of urban expansion, a spatiotemporal landscape metrics analysis across buffer zones is an improvement over using only urban growth rates. This type of analysis can also be used to infer underlying social, economic, and political processes that drive the observed urban forms. The results indicate that urban form can be quite malleable over relatively short periods of time. Despite different economic development and policy histories, the four cities exhibit common patterns in their shape, size, and growth rates, suggesting a convergence toward a standard urban form.

Urban land teleconnections and sustainability

This paper introduces urban land teleconnections as a conceptual framework that explicitly links land changes to underlying urbanization dynamics. We illustrate how three key themes that are currently addressed separately in the urban sustainability and land change literatures can lead to incorrect conclusions and misleading results when they are not examined jointly: the traditional system of land classification that is based on discrete categories and reinforces the false idea of a rural–urban dichotomy; the spatial quantification of land change that is based on place-based relationships, ignoring the connections between distant places, especially between urban functions and rural land uses; and the implicit assumptions about path dependency and sequential land changes that underlie current conceptualizations of land transitions. We then examine several environmental “grand challenges” and discuss how urban land teleconnections could help research communities frame scientific inquiries. Finally, we point to existing analytical approaches that can be used to advance development and application of the concept.

Does Size Matter? Scaling of CO2 Emissions and U.S. Urban Areas

Urban areas consume more than 66% of the world’s energy and generate more than 70% of global greenhouse gas emissions. With the world’s population expected to reach 10 billion by 2100, nearly 90% of whom will live in urban areas, a critical question for planetary sustainability is how the size of cities affects energy use and carbon dioxide (CO2) emissions. Are larger cities more energy and emissions efficient than smaller ones? Do larger cities exhibit gains from economies of scale with regard to emissions? Here we examine the relationship between city size and CO2 emissions for U.S. metropolitan areas using a production accounting allocation of emissions. We find that for the time period of 1999–2008, CO2 emissions scale proportionally with urban population size. Contrary to theoretical expectations, larger cities are not more emissions efficient than smaller ones.

Trees grow on money: Urban tree canopy cover and environmental justice

This study examines the distributional equity of urban tree canopy (UTC) cover for Baltimore, MD, Los Angeles, CA, New York, NY, Philadelphia, PA, Raleigh, NC, Sacramento, CA, and Washington, D.C. using high spatial resolution land cover data and census data. Data are analyzed at the Census Block Group levels using Spearman’s correlation, ordinary least squares regression (OLS), and a spatial autoregressive model (SAR). Across all cities there is a strong positive correlation between UTC cover and median household income. Negative correlations between race and UTC cover exist in bivariate models for some cities, but they are generally not observed using multivariate regressions that include additional variables on income, education, and housing age. SAR models result in higher r-square values compared to the OLS models across all cities, suggesting that spatial autocorrelation is an important feature of our data. Similarities among cities can be found based on shared characteristics of climate, race/ethnicity, and size. Our findings suggest that a suite of variables, including income, contribute to the distribution of UTC cover. These findings can help target simultaneous strategies for UTC goals and environmental justice concerns.

Evolving rank-size distributions of intra-metropolitan urban clusters in South China

Abstract Cities are the dominant form of human settlements and their interaction with the global environment presents great challenges for sustainability. This paper analyzes the evolution of urban form in three rapidly-growing Chinese metropolitan areas in the Pearl River Delta: Shenzhen, Foshan and Guangzhou. It is the first study to utilize a combination of time-series satellite imagery, GIS, and a time-series of spatial pattern statistics based on rank-size distributions to evaluate the evolving nature of urban clusters in Chinese cities. Defining the urban clusters – contiguous urban built-up areas – as the unit of our analysis, we estimate exponents of rank-size distributions for each city’s clusters for the years between 1988 and 1999. We observe substantial variation in the evolution of urban form across time. For all three metropolitan areas, the rank-size distribution exponents evolve in an oscillatory fashion within the 11-year period as the metropolitan areas grow through a process of cluster birth and coalescence. The analysis sheds light on the evolving nature of urban clusters that can help us better understand urban phenomena, and make inferences on how socioeconomic processes influence urban form which in turn has considerable effects on the ecology of the urban system and the local and regional environment. We show that a time-series analysis of rank-size distributions of urban clusters reveals trends in spatial patterns of urban form that can aid in the design of cities and help achieve more sustainable land-uses.

Modeling Urban Growth in Data-Sparse Environments: A New Approach

Although there exist numerous urban growth models, most have significant data input requirements, limiting their utility in a developing-world context. Yet, it is precisely in the developing world where there is an urgent need for urban growth models and scenarios since most expected urban growth in the next two decades will occur in such countries. This paper describes a physical urban growth model that requires few, but widely available, spatially explicit data. Utilizing binary urban/nonurban maps generated by satellite imaging, our model can inform urban planners and policy makers about the most probable locations and periods of future urban land-use change. Using a discrete choice framework, the model employs a spatially explicit logistic regression analysis to evaluate probabilities of urban growth for a baseline period. It calibrates parameters, validates results, predicts urban land-use change and examines future growth scenarios. Future growth scenarios can be generated through the inclusion of land prohibited from development, transportation routes, or new planned urban developments. A novel and important element of the model is the incorporation of an explicit policy-making framework that captures and reduces model uncertainty (theory and specification uncertainties), effectively addressing problems of predictive bias; this framework also allows the user or policy maker to associate predictions with a loss function. The model is applied to three cities in southern China that have experienced dramatic urban land growth in the last two decades. From 1988 to 1999, urban land in the region increased by 451.6% or at an annual rate of approximately 16.5%. Results show that the model achieves 73% – 77% accuracy for different cities at 30 m and 60 m resolutions. Aggregating the predictions to the county/administrative district shows that prediction through thresholding underperforms in comparison to the technique of sample enumeration.

Stewardship of the Biosphere in the Urban Era

We are entering a new urban era in which the ecology of the planet as a whole is increasingly influenced by human activities (Ellis 2011; Steffen et al. 2011a, b; Folke et al. 2011). Cities have become a central nexus of the relationship between people and nature, both as crucial centres of demand of ecosystem services, and as sources of environmental impacts. Approximately 60 % of the urban land present in 2030 is forecast to be built in the period 2000–2030 (Chap. 21). Urbanization therefore presents challenges but also opportunities. In the next two to three decades, we have unprecedented chances to vastly improve global sustainability through designing systems for increased resource efficiency, as well as through exploring how cities can be responsible stewards of biodiversity and ecosystem services, both within and beyond city boundaries.

A Synthesis of Global Urbanization Projections

This chapter reviews recent literature on global projections of future urbanization, covering the population, economic and physical extent perspectives. We report on several recent findings based on studies and reports on global patterns of urbanization. Specifically, we review new literature that makes projections about the spatial pattern, rate, and magnitude of urbanization change in the next 30–50 years. While projections should be viewed and utilized with caution, the chapter synthesis reports on several major findings that will have significant socioeconomic and environmental impacts including the following: By 2030, world urban population is expected to increase from the current 3.4 billion to almost 5 billion; Urban areas dominate the global economy – urban economies currently generate more than 90 % of global Gross Value Added; From 2000 to 2030, the percent increase in global urban land cover will be over 200 % whereas the global urban population will only grow by a little over 70 %. Our synthesis of recent projections suggest that between 50%–60% of the total urban land in existence in 2030 will be built in the first three decades of the 21st century.

Global scenarios of urban density and its impacts on building energy use through 2050

Significance Urban density significantly impacts urban energy use and the quality of life of urban residents. Here, we provide a global-scale analysis of future urban densities and associated energy use in the built environment under different urbanization scenarios. The relative importance of urban density and energy-efficient technologies varies geographically. In developing regions, urban density tends to be the more critical factor in building energy use. Large-scale retrofitting of building stock later rather than sooner results in more energy savings by the middle of the century. Reducing building energy use, improving the local environment, and mitigating climate change can be achieved through systemic efforts that take potential co-benefits and trade-offs of both higher urban density and building energy efficiency into account. Although the scale of impending urbanization is well-acknowledged, we have a limited understanding of how urban forms will change and what their impact will be on building energy use. Using both top-down and bottom-up approaches and scenarios, we examine building energy use for heating and cooling. Globally, the energy use for heating and cooling by the middle of the century will be between 45 and 59 exajoules per year (corresponding to an increase of 7–40% since 2010). Most of this variability is due to the uncertainty in future urban densities of rapidly growing cities in Asia and particularly China. Dense urban development leads to less urban energy use overall. Waiting to retrofit the existing built environment until markets are ready in about 5 years to widely deploy the most advanced renovation technologies leads to more savings in building energy use. Potential for savings in energy use is greatest in China when coupled with efficiency gains. Advanced efficiency makes the least difference compared with the business-as-usual scenario in South Asia and Sub-Saharan Africa but significantly contributes to energy savings in North America and Europe. Systemic efforts that focus on both urban form, of which urban density is an indicator, and energy-efficient technologies, but that also account for potential co-benefits and trade-offs with human well-being can contribute to both local and global sustainability. Particularly in growing cities in the developing world, such efforts can improve the well-being of billions of urban residents and contribute to mitigating climate change by reducing energy use in urban areas.