Growing Metropolitan Areas Research Articles

Houston, you have a problem: How large cities accommodate more housing

AbstractWe document how a select set of large and growing metropolitan areas have accommodated growth in their housing supply over 40 years. In particular, we examine how housing provision has evolved for the largest four metropolitan statistical areas (MSAs) in California and Texas. Despite differences in their topographies and regulatory environments, we find several common dynamics. As these MSAs grow, we see that fewer new net units are built at the periphery and a smaller share of the new units are built as single‐family detached houses. As a greater share of new net units are built in infill locations, more units are built using higher‐density—and more costly—multifamily housing construction techniques. Interestingly, we see these housing supply patterns in both “pro‐growth” MSAs and “highly regulated” MSAs. Among all of our sample MSAs, we also find a declining share of Census tracts that participate in accommodating growth. Our results are consistent with the existence of a convex housing supply curve. We believe that this secular trend will pose genuine challenges to many urban housing policies aimed at improving affordability.

Unveiling urban traffic accessibility patterns and phase diagrams of traffic direction through real-time navigation data in Beijing

Urban transportation accessibility plays a crucial role in assessing traffic conditions and gaining insights into urban development. Current research on accessibility patterns often relies on sensor data, focusing predominantly on specific locations or times. Recognizing the need for a more holistic study that considers the interconnected impact of both geographical location and time variables, this research conducts a spatial–temporal analysis of over 846,720 real-time location-to-location navigation data from Baidu Maps in Beijing. The findings reveal four distinct traffic accessibility patterns: the Weekend pattern (W-pattern), Southern weekday pattern (S-pattern), Northern weekday pattern (N-pattern), and Holiday pattern (H-pattern). These patterns exhibit spatial–temporal distribution characteristics and scale invariance. Significantly, scale invariance emerges as a key feature, suggesting potential phase transitions in the dynamic change process of the traffic system. To capture this phenomenon, a new indicator is introduced, utilizing the relative velocity sign to resemble the spin direction in the Ising model. Phase transition-like occurrences are identified through the phase diagram of the traffic state. These observations may provide useful insights into the geographic and temporal patterns of transportation accessibility in growing metropolitan areas.

The spatial relationship between long-term vacant housing and non-communicable diseases in U.S. shrinking and growing metropolitan areas

The rising prevalence of non-communicable diseases (NCDs) has led to increased attention on understanding how built environments affect NCD risks. However, there's a significant gap in the literature regarding the relationship between housing vacancy duration and NCDs in metropolitan areas with varying development rates. Our research addresses this gap by examining the association between housing vacancy duration and NCDs across all U.S. metropolitan areas, considering growing, shrinking, and fluctuating counties. We used a Multiscale Geographically Weighted Regression (MGWR) model to analyze this relationship, finding that longer-term vacant housing (over 3 years) is more positively associated with NCDs compared to short-term vacancies. We also discovered that this association is non-uniform across metropolitan counties, except for cancer and stroke outcomes. Shrinking counties in the Northeast are particularly affected, emphasizing the need for targeted public health interventions in these areas. This study underscores the importance of revitalizing vacant homes, especially those vacant for over 3 years, in both shrinking and growing regions to improve public health. Policymakers should adopt tailored strategies, engage public health experts, and invest in healthcare infrastructure to effectively address the health risks linked to vacant housing.

Landscape composition is a stronger determinant than noise and light of avian community structure in an urbanizing county

Urban development has drastically altered ecosystems with dramatic effects on avian diversity and community structure. Most studies investigating this phenomenon are conducted in large and established cities, with fewer conducted in areas of current urbanization. Measuring avian community structure in recently established and growing cities is necessary to understand which species are being affected in a range of urban environments. There is also a critical need to explore multiple measures of urbanization, as different axes of human influence might have varied effects on wildlife. This study investigated the relationship between avian communities and urban noise, light, and landscape composition in Weld County, CO, one of the United States’ fastest growing metropolitan areas. We tested the general hypothesis that avian community assemblages would vary with multiple urban characteristics. We measured noise, light, and landscape composition across 16 sites ranging from urban to non-urban and paired these data with avian species census data. We used multivariate analyses to test for covariance of our three measures of urban characteristics, and to examine patterns of species presence and abundances at sites. Results suggest that developed land and water covary with avian community structure across our study sites. Anthropogenic noise and light did not drive avian community patterns as strongly as percent developed land and water. These three urban characteristics did not covary or form a linear urban to non-urban gradient, suggesting that urbanization can have patchy and unpredictable effects, highlighting the value of measuring urban characteristics separately.

Integrated assessment for Sustainable Development Goals of metropolitan regions: A case study of the Pearl River Delta region, China

Achieving Sustainable Development Goals (SDGs) at the sub-national scale requires contextual insights and localized implementation. This study utilizes Driver-Pressure-State-Impact-Response (DPSIR) framework to assess SDG progress and interactions in the Pearl River Delta (PRD) metropolitan region of China. Population growth, economic development, and rapid urbanization are key drivers, exerting pressures on energy and water consumption, pollutant discharges, transportation, environmental degradation, and disaster management. The results reveal varied progress in nine goals intrinsic to this metropolitan context, with notable progress in energy and water consumption, and employment (Goals 7, 8, and 3). While moderate progress is evidenced in poverty reduction, economic growth, healthcare services, social security, access to potable water, water quality (Goals 1 and 6), challenges remain in transportation, waste generation, air quality, forest management, and disaster response (Goals 9, 11, and 15). Furthermore, target interaction analysis suggests that initiatives in high-leverage areas - ecosystem and environmental protection, equal access to resources and basic services, and climate change response - can yield substantial systemic impacts. However, poverty reduction, access to resources and basic services, ecosystem protection, and economic growth appear more dependent on system-wide efforts. By leveraging the DPSIR model, this context-sensitive SDG assessment accentuates priority zones and offers valuable perspective for cohesive SDG strategy formation and policy-making in dynamically growing metropolitan areas globally.

Megalopolitan-scale ground deformation along metro lines in the Guangdong-Hong Kong-Macao Greater Bay Area, China, revealed by MT-InSAR

As one of the most densely populated and rapidly growing metropolitan areas worldwide, the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China has been developing extensive metro networks to relieve the escalating traffic congestion inner cities and to shorten public transport time inter cities. Metro construction possibly triggers ground deformation, which may result in damage to the tunnel, pipeline, and ground structures. Fast and efficient monitoring ground deformation along metro lines is vital not only to the metro itself but also to these structures. This study provides a comprehensive investigation of ground deformation along 67 metro lines within the GBA, based on multi-temporal synthetic aperture radar interferometry (MT-InSAR) by using Sentinel-1 from March 2017 to February 2022. The results reveal that deformation velocity in this area ranges from –39.4 mm/year to 14.2 mm/year, which is mainly caused by the tunnel excavation, adjacent excavation and construction, and unfavorable geological conditions. Furthermore, risk levels have been evaluated based on the InSAR-derived results with the proposed median absolute deviation heatmap clustering method. The risky area accounts for 16.31% (∼205.24 km2) of the whole study area in the GBA, among which 13.76%, 2.16%, and 0.39% are classified as three risk levels, with mean deformation velocities of –2.2 mm/year, –3.4 mm/year, and –6.5 mm/year, respectively. This study presents a comprehensive megalopolitan-scale ground deformation monitoring, for the first time, along metro lines in six cities of the GBA, which provides important insights into future metro line constructing, operating and planning.

Optimal Regional Allocation of Future Population and Employment under Urban Boundary and Density Constraints: A Spatial Interaction Modeling Approach

This paper develops an optimization modeling framework to select strategies of land development and population and employment densities for a growing metropolitan area. The modeling core involves a non-linear commuting model, which accounts for spatial structure variables and is empirically estimated by Tobit regression. This commuting model is then embedded into a non-linear optimization model that allocates increments in the population and employment (activities) to available land, while minimizing the total future commuting costs under various combinations of land expansion boundaries and population and employment densities. The resulting minimum cost surface is approximated via polynomial regression and combined with land development and congestion cost functions to derive the overall optimal strategy. These models are estimated and calibrated with data from the Census Transportation Planning Package (CTPP) and Auditor’s property database, and are applied to the Fredericksburg metropolitan area, Virginia. The results demonstrate that the optimal development densities are very sensitive to the congestion cost function. A land development strategy that allows for limited sprawl might be a smart policy to reduce both regional vehicle mile travel (VMT) and related congestion and pollution.

SPATIO TEMPORAL MAPPING AND MONITORING OF LAND COVER DYNAMICS OF ISLAMABAD USING MULTI-TEMPORAL REMOTE SENSING DATA

Land cover resources are changing continuously both spatially and temporallywhereas the accurate and timely information regarding their dynamics is very important. Spatialgrowth is an expected phenomenon particularly in fast growing metropolitan areas like Islamabad, thecapital of Pakistan. In this study spatial and temporal dynamics of land cover changes were quantifiedfrom 1975 to 2010 using Landsat images, a supervised classification algorithm and the changedetection technique with Geographical Information Systems were used. The overall accuracy of theland cover derived from satellite images was from 80 to 95%. The land cover maps showed thatbetween 1975 and 2010 the amount of urban or developed land increased from 50 km2to 332 km2 of the total area, while vegetation, including Margalla Hills National Park decreased from 465 km2to 145 km2. The results quantified the land cover change pattern in the city and showed a potential of multitemporal Landsat data to provide an accurate, cost-effective means to map and analyze changes in land cover over time

Transport policies in polycentric cities

This paper studies how transit lines should be developed in polycentric cities. In several growing metropolitan areas, local authorities have to decide whether to rely on existing radial lines connecting suburban areas to the city-center, or to develop new circular lines directly connecting suburban areas. An efficient transit system aims at reducing external costs of transport (congestion and pollution) by attracting private car users. We study the effect of two types of policies on the modal split. First, we compare the effect of three administration regimes (public, semi-public and private) on the external costs of transport. Second, we consider the opening of a new transit line directly linking the suburbs. We find that it reduces aggregate user cost but is not Pareto-improving unless crowding is high on existing transit lines. Our analysis is complemented by a numerical illustration based on an open source Fortran program. This tool needs a relatively small set of data and can be used by policy makers wishing to investigate the pricing reforms or the possibility of opening a new transit line for a specific case study.

Multitemporal Analysis of Urban Expansion in the Municipality of Madrid, Cundinamarca, between 1977 and 2020

Context: Given the increasing population concentration, both the proximity of the town of Madrid to the city of Bogotá and the growing metropolitan area around the latter have a significant influence on the increased urbanization and the change in land use in the town of Madrid, Cundinamarca. Objective: The objective of this study was to carry out a multitemporal analysis of the change in coverage and land use caused by urban expansion in the municipality of Madrid between 1977 and 2020. Methodology: Satellite images were observed through supervised classification, following the Corine Land Cover methodology, which was adapted for the Colombian context, and utilizing geographic information systems. Area variation analyses were performed for each classification in each of the evaluated years. Results: The data obtained show that the forest cover area and seminatural zones have been reduced by 86% in a period of 43 years, and that artificial territories have progressively become predominant in each of the years, even reaching a coverage greater than 50% of the municipality area. The agricultural territories have maintained 66,95% of the surface of the municipality, and they correspond the land use with the largest occupied area for the evaluated period, which shows the importance of the soil for the economic development of the population. Conclusions: This situation shows that population growth and urban expansion cause variations in coverage and land uses. Their valuation is an aspect that must be considered when elaborating development plans for municipal entities.

Modelling the spatial impact of regional planning and climate change prevention strategies on land consumption in the Rhine-Ruhr Metropolitan Area 2017–2030

Urban sprawl is a ubiquitous with a complex network of driving forces and human and natural impacts on various scales of the coupled human-environment urban system. In Germany, a land consumption of 30 ha per day is envisaged. In that regard, the effect of growing metropolitan areas on the climate of local neighborhoods becomes more and more a topic in regional planning. Accordingly, the objectives of the study are a) to contribute to the climate change related land cover simulation efforts in Germany in a spatially explicit manner with a resolution of 30 m, b) to investigate future land consumption rates and population growth rates having a view on goal 11 of UN’s SDG, and c) analyze the spatial impact of planning policies in regard to land use planning and official climate change prevention strategies using Rhine-Ruhr Metropolitan Area (RRMA) in Western Germany as a study area. The study makes use of land use and land cover classification of multispectral satellite data and the derivation of land surface temperature based on Landsat satellite in order to calibrate and validate the urban growth model SUSM (scenario-based urban growth simulation model). Two scenarios for future land consumption 2030 are implemented and the future impacts of urban growth with the projection of land consumption rate (LCR), population growth rate (PGR), and LCRPGR index on municipality level, as well as the impact on regions vulnerable to climate change evaluated. The comparison of simulated urban growth to observed urban growth from 2005 to 2017 shows that the PA of SUSM for historic scenario is 68.06% with an overall accuracy of 97.15%, a Matthews correlation coefficient of 0.66, a figure of merit of 0.51 and area under curve of 0.84. The total quantity of new urban areas of our SUSM simulation 2030 were approximately 283 km2. While the difference in the simulated total quantity is nearly zero, the simulated allocation of new urban areas across the districts can differ by up to 25 km2 in the two scenarios. The number of municipalities with efficient urban land development rates increases in the SUSM scenario where no regional land development plan has been incorporated. This holds true for the number of municipalities with inefficient land use where even an increase from no plan to plan can be observed. LCRPGR is negative in most municipalities reflecting opposing trends of population and land consumption development. Most of new urban areas are distributed in open spaces important for the regional climate change prevention strategy. 32.98 % of new urban areas in our region of interest can be found in these zones in the planning scenario and 25.76 % in the scenario without planning information in SUSM model. It can be concluded that regional planning in RRMA region has no positive effect on the interregional development of future land consumption in terms of quantity, allocation, and impact on climate change prevention.

Incorporation of post-earthquake fire (PEF) and subsequent aftershock for performance analysis of steel buildings

The advancements in analysis and design approaches considering the seismic loads have helped safeguard buildings against structural failure and collapse. However, design objectives should also consider the associated effects and performance evaluation incorporating the sequential effects. Improving the performance of buildings at both the asset and community levels is now of major interest in the field of structural engineering. This research addresses the advancement toward this goal by incorporating post-earthquake fire and aftershock to multi-hazard design methodology. A set of mid-rise buildings – 3-, 9-, and 20-story moment resisting steel frames, characteristic of those found in rapidly growing metropolitan areas of US, are selected for the study considering the relative vulnerability to post-earthquake fire. The analyses of the responses are based on advanced finite element simulation methods/techniques and corresponding approaches. ABAQUS/CAE is primarily employed for the simulation and analysis. The effects of fire are thoroughly studied from the literature and considered explicitly, and the analysis is performed for a complete cycle of main shock (full-intensity) –fire- aftershock (reduced intensity) earthquake. The research commences with the investigation of the effects of modeling approach-- using beam element and using solid element with slab, on Post Earthquake Fire (PEF) study of a single room model. At the end of a complete sequence, the model developed using 3D solid elements are found to underestimate the stiffness loss by around 15% compared to those developed using 2D beam elements. The behaviors of selected steel moment resisting frame buildings then simulated with PEF are investigated to quantify the overall performance behavior of the building system. Inter-story Drift Ratio (IDR) and Stiffness Degradation over the complete sequence of events are chosen as the damage measures. The same approach is applied to a real building in California and the performance behavior is studied. All the building systems studied show the significant damages and change in behavior after incorporating the fire and aftershock. In all building sets, the stiffness loss (global) due to mainshock alone (2% to 10% in the cases studied) is very less as compared to the stiffness loss due to fire alone (6% to 15%) and aftershock (10% to 25%) alone.

Urban signatures of sub-daily extreme precipitation events over a metropolitan region

Previous research on the relationship between urbanization and extreme precipitation has shown that regional and global anthropogenic changes have made extreme precipitation events more frequent. The purpose of this research was to explore changes in the variability of extreme precipitation in urban areas that underwent different degrees of urbanization intensity, and to explore the possible reasons using data from 7 meteorological stations in Shenzhen, China with hourly precipitation records dating back to the 60's. Shenzhen is one of the fastest growing metropolitan areas on earth with heavy urbanization occurring since 1979. We used k-means clustering to categorize areas of the city into steadily urbanized regions (SUR) or rapidly urbanized regions (RUR). Next, the variations in the linear trends of annual maximum precipitation (AMP) were analyzed, followed by water vapor analysis and the random forest algorithm to analyze the causes of the variation. The results showed that the severity of the urbanization process had a large and significant impact on extreme precipitation. The AMP analysis showed that at the higher temporal resolutions (< 6 h) extreme precipitation was only significant at RUR stations, while at low temporal resolutions precipitation did not significantly change at any station. An analysis of the diurnal patterns of precipitation and the water vapor analysis over Shenzhen showed that the increase in short-duration extreme precipitation events may be related to atmospheric instability caused by heat emitted as a byproduct of the urbanization process. Furthermore, the differences between the variations in the precipitation trends of SUR and RUR may be related to differences in thermal contrast between high and low altitudes. The results of the random forest analysis supported the correlations between the severity of urban development and changes in precipitation variability. Our findings have highlighted the need for a better understanding of the local and regional anthropogenic effects on the climate and the intensification of extreme climate events due to urbanization.

Zoning and affordability: A reply to Rodríguez-Pose and Storper.

Would increasing allowable housing densities in expensive cities generate more housing construction and make housing more affordable? In a provocative article, Andrés Rodríguez-Pose and Michael Storper survey the evidence and answer no. Restrictions on housing density, they contend, do not substantially influence housing production or price. They further argue that allowing more density in growing metropolitan areas would only improve housing outcomes for the affluent, and most likely harm the poor. We take issue with both of these contentions. While uncertainties remain in the study of housing prices and land use regulation, neither theory nor evidence warrant dispensing with zoning reform, or concluding that it could only be regressive. Viewed in full, the evidence suggests that increasing allowable housing densities is an important part of housing affordability in expensive regions.

Neural Network Based Traffic Monitoring using UAVs

In large and growing metropolitan areas, the rise in traffic congestion is becoming an inescapable problem. It is estimated that the traffic congestion in metro cities costs the nation approximately 1.5 lakh crore rupees every year. With the increase in congestion, accident rate increases proportionally. The reckless driving and increased speed are the root cause of road accidents. We propose a speed detection algorithm to detect and monitor the speed of vehicles crossing a certain threshold speed limit. On national highways, the long queues at toll booths lead to loss of time and money. We propose image processing and convolutional neural network based algorithm to address the problem of traffic congestion, ease the flow of traffic, anomalies detection and ultimately reduce pollution and fuel consumption.

Spatial-temporal Heterogeneity of Green Development Efficiency and Its Influencing Factors in Growing Metropolitan Area: A Case Study for the Xuzhou Metropolitan Area

This study analyzed the spatial-temporal heterogeneity of green development efficiency and its influencing factors in the growing Xuzhou Metropolitan Area for the period 2000-2015. The slacks-based measure (SBM) model, spatial autocorrelation, and the geographically weighted regression (GWR) model were used to conduct the analysis. The conclusions were as follows: first, the overall efficiency of green development of the Xuzhou Metropolitan Area decreased, the regional differences and spatial agglomeration shrunk and differences within the region were the main contributors to the regional differences of green development efficiency. Second, the counties with high-efficiency green development were distributed along the coast, and along the routes of the Beijing-Shanghai and the Eastern Longhai railways. A developing axis of the high-efficiency counties was the main feature of the spatial pattern for green development efficiency. Third, regarding spatial correlation and green development efficiency, the High-High type counties in the Xuzhou Metropolitan Area formed a centralized distribution corridor along the inter-provincial border areas of Henan and Jiangsu, whereas the Low-Low type counties were concentrated in the external, marginal parts of the metropolitan area. Fourth, the major factors (ranked in decreasing order of impact) influencing green development efficiency were innovation, government regulations, the economic development level, energy consumption, and industrial structure. These factors exerted their influence to varying extents; the influence of the same factor had different effects in different regions and obvious spatial differences were observed for the different regions.

A theory of heterogeneous city growth

AbstractWe consider an economy with three cities producing different outputs. Two cities produce intermediate goods, a type 1 city producing an intermediate “agricultural” good with capital and labor only, and a type 2 city producing an intermediate “industrial” good with capital, labor, and human capital. A type 3 city produces the final good which is obtained from the two intermediate goods and labor. The asymmetric introduction of human capital allows us to prove that the three cities experience, at equilibrium, heterogeneous endogenous growth rates which are proportional to the growth rate of human capital. We show that the “industrial” type 2 city is characterized by the larger growth rate while the “agricultural” type 1 city experiences the lower growth rate, and thus the type 3 city is characterized by a growth rate which is a convex combination of the two former growth rates. This implies that the relative size in terms of output of the “agricultural” city decreases over time. This property allows us to recover the empirical fact that most non‐agricultural production occurs in growing metropolitan areas. But, simultaneously, as we prove that total labor employed in each city is proportional to the total population, the relative population size distribution of cities is constant over time, as shown in empirical studies.

Embodied Life Cycle Assessment (LCA) comparison of residential building retrofit measures in Atlanta

Studies showed that up to 30% of a building's life cycle energy and emissions are associated with the embodied phase and this number could increase to 50% for energy efficient passive houses. The residential housing market alone has a significant impact on US emissions. This research targeted Atlanta as one of the growing metropolitan areas in the US and conducted an embodied Life Cycle Assessment (LCA) comparison of single-family residential retrofit measures considering the original construction year of the buildings. At first, the paper investigated the potential retrofit measurements to improve the operational energy consumption of the different building categories. The paper then calculated the embodied impacts associated with the retrofit measures and compared them against each other to find the most energy and environmentally efficient options in terms of the embodied impacts. The paper finally conducted a trade-off analysis to investigate the payback period of the retrofit options regarding their impact on the operational energy savings throughout the second phase of the building's life span. The main findings of this research showed that the highest environmental impacts are associated with the attic/knee insulation and heating, ventilation and air conditioning (HVAC) unit's replacement through retrofitting residential buildings. The findings also demonstrated the significant environmental impacts for foundation wall insulation and window upgrading through retrofitting dwellings built before the 1970s. The trade-off results revealed that the embodied energy payback period is generally around 3–5 years for before 1970s and 1.6–3.2 years for after 1970s buildings.

Lone Star Suburbs: Life on the Texas Metropolitan Frontier ed. by Paul J.P. Sandul and M. Scott Sosebee

Reviewed by: Lone Star Suburbs: Life on the Texas Metropolitan Frontier ed. by Paul J.P. Sandul and M. Scott Sosebee Yu Han Lone Star Suburbs: Life on the Texas Metropolitan Frontier. Edited by Paul J. P. Sandul and M. Scott Sosebee. (Norman: University of Oklahoma Press, 2019. Pp. xii, 250. $24.95, ISBN 978-0-8061-6447-2.) Texas is a state I have been very interested in and have kept a close eye on for many years, simply because, for more than half a century, it has been a shining star in the Sun Belt, and even in the whole nation, in terms of solid and rapid economic and metropolitan growth. However, the metropolitan areas of Texas do not seem to be popular subjects for historians, for whom the focus has been on the "'Texas Myth,'" one "dominated by cowboys, the frontier, Texas Rangers, and above all the Alamo and the Texas Revolution" (p. 4). Obviously, Texas metropolitan areas, especially the booming suburbs, have not gotten the attention they deserve. This volume, edited by Paul J. P. Sandul and M. Scott Sosebee, is the first book featuring the comprehensive story of suburban Texas, which includes essays on planning, politics, governing, ethno-racial diversity, transportation, religion, and environmentalism. The first essay, by Sandul, serves as the introduction to this volume, and it explores the historiography of the Lone Star State, especially suburban Texas and the suburban demographic situation, in detail. The historiographical section is successful and informative, but other parts are not. Some readers might not be satisfied with the census population data as the only material used to describe the rise of Texas suburbs after World War II. Other essays are uneven in quality. The best one is the second essay, by Robert B. Fairbanks, an established urban historian, who examines suburban planning in the Dallas–Fort Worth metropolitan area in detail. He challenges, with concrete evidence, the conventional view that suburban cities are accidental or not well [End Page 760] planned. The suburbs examined are "intentional communities nurtured by their energetic civic leadership, shaped by their location within a growing metropolitan area, and formatted by professional urban planners hired by local booster governments to create what became a new urban form—suburban cities" (p. 62). The third essay, by Andrew C. Baker, presents readers with a struggle between city and suburb in Chateau Woods, a small rural subdivision north of Houston. This struggle was a response to the issues of incorporation and annexation, which have been raised by Kenneth T. Jackson in Crabgrass Frontier: The Suburbanization of the United States (New York, 1985) but have been neglected by historians for many years. In Baker's view, "the story of Chateau Woods serves as a case study in the perils of hyper-local, amateur-led democracy," and "incorporation was not always an answer to suburban problems on the metropolitan fringe" (pp. 87, 88). Three essays discuss the suburbanization of two ethnic groups in Texas. Chapters 4 and 9 focus on the migration of African Americans to the suburbs of Dallas and San Antonio, respectively. These two essays are narratives detailing African American migration patterns but lack analysis of the effects of migration on the employment and education of African Americans in suburbs, which is often a significant part of black suburbanization; chapter 4 does mention the influence of black poverty in the city. Compared with the suburbanization of African Americans, the suburbanization of Asian Americans is a fairly new phenomenon. Chapter 10 tells the story of the formation of an "ethnoburb," a new Asian community in Texas, with an emphasis on the Vietnamese in Houston. Son Mai argues that the development of this neighborhood was for economic activity and cultural preservation, rather than protection against racial discrimination. This essay, without any firsthand resources, is quite weak in terms of originality. Chapter 5, by Tom McKinney, provides a detailed account of the development of transportation facilities in Texas, including the background, process, and effects of construction of urban freeway systems during the suburbanization of the Lone Star State. As the title of this chapter, "The Czars of Concrete: The Texas Highway Department's Engineer-Manager Program and the Development...

Delineating early warning zones in rapidly growing metropolitan areas by integrating a multiscale urban growth model with biogeography-based optimization

Urban agglomerations have become the core areas of new urbanization in China, leading to major structural adjustments in regional development patterns and thus threatening the ecosystem. Predicting future urban growth and delineating early warning zones can provide scientific guidance for land use planning and ecological protection. However, limited research has targeted fast-urbanizing metropolitan areas, which can be particularly difficult compared with existing approaches conducted in a single city. Another concern is that the adjustable demand of urban land in the future can invalidate simple and rigid zoning schemes. This study proposed a framework of delineating hierarchical early warning zones to represent different probabilities of potential development in vulnerable areas. Specifically, a multiscale urban growth model and biogeography-based optimization (BBO) were integrated for calibrating transition rules and simulating historical urban evolution (2005–2015) in the rapidly growing Yangtze River middle reaches megalopolis (YRMRM) in China. Then, the future urban land demand in 2025 was predicted under different economic development strategies, and multiple urban growth scenarios were simulated by coupling urban demand and spatial planning policies. Finally, simulation results of different scenarios were overlaid in a GIS environment to provide three levels of zones for the early warning of illegal development in the protected areas. Results indicate that BBO performed better in calibrating parameters of the urban growth model than did particle swarm optimization and genetic algorithm. The prediction of future urban dynamics suggests that urbanization will continue in this region until 2025, and these early warning areas should be given attention for farmland protection and ecological security in the YRMRM.