Journal of Urban Planning and Development

Modeling urban growth has the ability to play an important role in the planning process—if not in aiding in policy decisions, then in processes such as visioning and scenario evaluation. Spatial urban models passed through many developed phases to define the responsible urbanization factors. As a result, many simulation applications and planning tools have been developed and successfully used in universities and research institutions to simulate the spread of planned settlements in developed nations.. This paper will use SLEUTH to assess the model capacity to generate realistic simulation and prediction of informal settlements in the context of unplanned areas, such as the greater Cairo region (GCR), Egypt. The results show that the successful application of a model in one particular geographical area does not necessarily imply its successful use in another setting where local characteristics, regional constraints, social habits, and situation properties of economic base ensure that different development trends have been followed.

Urban influential hinterland reflects the relationships between urban centers and their peripheral regions. However, existing urban influence hinterland delimitation models are inadequate to explain and analyze the complexities of urban systems in China because of their lack of maneuverability. This paper presents an optimized field-model method to study the urban influence hinterlands of all major cities in China in 1991 and 2010. This method achieved a better delineation of urban hinterland through a comprehensive index of urban influence and a new measure of regional accessibility. Based on the improved delineation of urban influential hinterland, a detailed analysis has been performed of hierarchical changes in urban hinterland areas and the dynamic evolution of spatial patterns, including the effect of different urban hinterland patterns on the scale of a city and the relationships between urban centers and their peripheral cities, using geographical information system (GIS) technology. The similarities and differences between hinterland areas and administrative divisions were also studied by overlaying these areas with provincial boundaries to provide a scientific basis for adjustment of administrative divisions and delimitation of urban economic regions. In this study, urban economic regions were delineated by grades in accordance with their core region and their influential hinterland at different hierarchical levels. Compared with previous studies, the method proposed in this paper could reveal the spatial components and structure of various urban agglomerations, thus providing a new perspective from which to study urban agglomerations.

Despite much enthusiasm among practitioners to spur rates of bicycle commuting via promotional measures such as community rides or commuter incentive programs, there is little research regarding their impact. Using data from one such event, Bike-to-Work Day (BTWD), this paper aims to understand the following: (1) who attends BTWD; (2) the impacts of these event-based promotional strategies across different groups; and (3) lessons for increasing commuter cycling in general. The authors assess these research questions by examining motives to participate, behavior change, and influences of the event using over 1,000 surveys collected in the Denver region. Using an ordered logit model, the authors then identify significant factors for grouping cyclists’ by behavior category. The results suggest that event attendees vary widely, from those who only bicycle on BTWD to those who report year-round bicycling, while reasons for participation and impacts of participation vary across bicycling behavior groups. This research also identifies specific barriers to increased commuter cycling. While the long-term impact of such events remains uncertain, this research illustrates that BTWD has the unique ability to capture a wide range of bicyclists and provide insights into barriers impacting diverse cycling populations.

This paper proposes the dynamic simulation analysis on the basis of summarizing the international theories and methods of urban agglomeration spatial analysis, and uses this analysis on the Changsha–Zhuzhou–Xiangtan urban agglomeration as an example. The dynamic simulation analysis aims to grasp the thread of historical development of an urban agglomeration, predict its future development trend, simulate its expansion condition, and find its advantages and disadvantages. In the analysis process, a grid system of 6,808 cells measuring $5\times 5\mathrm{km}$ was established on the base maps of the urban built-up areas of the Changsha–Zhuzhou–Xiangtan urban agglomeration during 1980 to 2010. In every grid cell, the proportions of built-up areas were measured by MAPGIS. All grid cells were colored with different shades according to the density of the built-up area. Then the authors drew up three-dimensional curves using the centrifugal model, which quantified the distribution and change of grid cells. After that, the authors built rose maps which dynamically simulated the historical expansion trend of those cities. Through the above research, the past and future development trend and characteristics of the urban agglomeration were summarized completely. This analysis method is significantly different from the previous methods. It can not only grasp the current and historical development situations, but also forecast future development trends and simulate expansion degrees in various directions of the urban agglomeration.

The aim of this paper is to contribute to describe the simultaneous choice of travel mode and departure time by making use of a cross-nested logit structure that allows for the joint representation of interalternative correlation along the both choice dimensions. Traditional multinomial logit model and nested logit model are formulated respectively. The analysis uses the revealed preference data collected from Maryland-Washington, DC, regional household travel survey during 2007–2008 for commuting trips, considering more work-related characteristics than previous studies. A comparison of the different model results shows that the presented cross-nested logit structure offers significant improvements over multinomial logit and nested logit models. The empirical results of the analysis reveal significant influences on commuter joint choice behavior of travel mode and departure time. Moreover, a Monte Carlo simulation for two groups of scenarios arising from transportation policies, congestion pricing, and improvements to transit service during peak period is undertaken respectively to examine the impact of a change in car travel cost and transit travel time on the travel mode and departure time switching. The simulation results show that US$5 increase in car travel cost during peak period has a similar effect on reducing drive alone in peak hours as 30% saving in transit travel time but only half of the latter policy in the transit ridership increase.

Housing affordability and sustainable development are not polarized ideologies as both are necessary with increasing urbanization. Researchers must bridge the gap between current median house pricing and target affordable house pricing while pursuing sustainability. This paper examines the potential of initial construction cost and ongoing utilities and transport cost reduction, through the integration of sustainable housing design and transit oriented development principles in a commuter energy and building utilities system (CEBUS). It also introduces current research on the development of a dynamic simulation model for CEBUS applications in the Australian property development and construction industry.

This article reports an investigation on the importance of various transfer facility attributes in and around metro stations and their derived ranking with reference to a case study in the city of Kolkata, India. A paper-based survey instrument was designed and responses in terms of rating on a five-point Likert-type ordinal scale were collected from metro commuters in Kolkata. The data were analyzed using three established methods, namely, technique for order preference by similarity to ideal solution (TOPSIS), RIDIT analysis, and gray relation analysis (GRA), in order to understand the variation, if any, in the derived rankings of attributes obtained from these methods. A comparison of rankings obtained from these methods using Spearman’s rank order correlation coefficients indicates a positive rank order relationship among all the three methods. The results consistently indicate commuters’ priority on qualitative attributes of transfer facility and contradict the common belief that the metro fare is the major concern for commuters in emerging countries such as India. The findings justify the need for improving transfer facilities in and around metro stations, and enhancing the road safety awareness among metro commuters in Kolkata.

Transportation investments have profound indirect effects on urban development. Improving transportation infrastructure reduces travel times, and thus, enhances accessibility of the population to employment and vice versa. In this procedure, the cities whose accessibilities mostly benefit from the transportation improvements would attract more population and capital. This paper attempts to quantify these impacts in the megaregions, and to prioritize the transportation investments according to their potential effects on the sustainability of the future development in these regions. For this purpose, the problem is formulated as a bilevel programming model. At the upper level, subject to a budget and environmental constraints, the optimal subset of projects is chosen from the candidate set. The objective is to maximize the total production of the megaregion at the end of the planning horizon. The final product of each city is determined according to its resultant population and physical capital. Under the network investment decisions of the upper level problem, the lower level represents the route choice behavior of users. Because the focus of the study is interurban road networks, which have sparse connectivity, a simple all-or-nothing trip assignment technique is employed at this level. To illustrate the application of the proposed model, the Northeast Megaregion of the United States is used as the case study. The exact solution is obtained for this example and compared to the regional development without improving the transportation network.

Land-use structure variables derived from landscape ecology theory are introduced into traditional employment density models based on the distance to the major central business district in the monocentric framework or on distances to multiple employment centers in the polycentric framework. Four groups of land use indexes related to size, complexity, diversity, and neighborhood are computed for the Columbus, Ohio, metropolitan area. Models are first constructed for each of its seven counties separately and then combined to form a complete metropolitan-level model. The spatial error model (SEM) is used to account for the spatial autocorrelation that characterizes the data. The results show that distances to both Columbus and county central business districts (CBDs) are strong employment density determinants but also show that land-use structure, measured by the dominance index and the mean edge contrast index, is an important employment density factor. The predictive capability of the model is validated by estimating it over six counties and using it to estimate the density pattern in the omitted county.

Modeling housing search behavior is a crucial component of land use modeling. Land use modeling from a specific point of view shares close ties with the transport system. As a result, housing search behavior has become an attractive research topic to travel demand modelers and continues to be a topic of interest to urban planners, geographers, and economists. This paper presents a conceptual framework for long-term decisions of household members with a specific focus on residential relocation-related decisions. The reasons for movement and timing of movement are modeled in this paper using two approaches: (1) a competing hazard formulation, and (2) a conditional hazard and discrete choice model. Australian longitudinal data are used to develop the econometric models in which income change, property value, unemployment rate change, and demographic dynamics are available.

Participatory landscape has become a strategic concern for achieving sustainable environments and in enhancing the social awareness within the external context of residential neighborhoods. However, few studies have explored the right methodologies for implementing such approaches, and none of them have presented a detailed model that can guide decision makers during its application, especially in the Egyptian communities with their different income and social levels. The paper thus presents a statistical approach for the measurement of the residents’ willingness to participate in such processes in comparison with the degree of involvement proposed by practitioners in three neighborhoods of different income and social levels in 6th of October City, as a remarkable example of one of the new Egyptian cities. It deduces statistical correlations between each of the variables representing the degree of residents’ participation once according to their willing and another according to practitioners’ recommendation for their degree of involvement as compared to the other stakeholders, with the functional, environmental, aesthetical, economic, maintainability, and sociability quality aspects of the landscape that would be achieved upon participation processes. Results highlighted the fact that levels of participation and significance of the roles of other stakeholders vary from one neighborhood to another and also vary according to their impact on the different functional, environmental, aesthetical, economic, maintainability, and sociability landscape qualities. Accordingly, it is necessary to conduct such action-oriented research before applying any participatory landscape approaches as there is no single unique model for successful participatory landscape approaches, which should be rather viewed as a dynamic transformation sustained by the local identity of the community, to overcome the contradiction between the recognition of the diversity of cultural practices and the problematic selection criteria of “outstanding universal value.”

This work presents a contribution to the decision support method for planning and administration of land use, with the concept of a soft decision tree. The results are interactive maps of suggestion for land use. The source data are obtained from field surveys and from thematic maps, combined in a geographical information system environment. The data are stored in a geodatabase, and operated by fuzzy logic. The information contained in the geodatabase is managed by a developed interface software that aggregates and analyzes the variables by a soft decision tree, using commercial software. The resulting data are then processed to generate an interactive map of suggestion for land use. The proposed method is validated with the example of an interactive map of suggestion for land use on the island of São Francisco do Sul, southern Brazil.

Four-stage travel demand modeling comprises of trip generation, trip distribution, mode choice, and traffic assignment. Limitations of conventional four-stage models are that they do not take into account subjectivity, imprecision, ambiguity, and vagueness involved in human decisions. In this direction, fuzzy logic is found to be the most suitable technique because it considers linguistic variables and expressions. Keeping this in view, the present study proposes to develop a methodology to consider fuzzy logic technique at different stages to develop travel demand models. The fuzzy logic–based travel demand models are developed in MATLAB software considering subtractive clustering technique. Four-stage conventional models are also developed to compare the efficiency of fuzzy logic models. The modeling results in terms $R^2$, root-mean-square error (RMSE), and average error from both conventional and fuzzy logic models show that fuzzy logic models yield improved results in comparison to the conventional models. Further, to demonstrate the suitability of the developed fuzzy logic travel demand model, selected public transport policies are simulated considering appropriate parameters.

This paper extends the previous LandSys I to introduce artificial neural networks (ANNs) into the framework of cellular automata (CA), multiagents, and geographic information system (GIS) to forecast land-use change at the grid cell level ($50\times 50\mathrm{m}$). In the model, the temporal and spatial interactions of land-use change are described by CA where transition rules are defined by ANNs to reduce the tedious work of parameter calibration in LandSys I. Compared with LandSys I, an improved multiagent model in LandSys II captures both zoning policies and human decision-making behaviors. The effect of multiple human decision-making behaviors (e.g., governments, households, developers) on land-use change has been quantified. Based on the historical GIS data for Orange County, Florida, the model has a higher predictive ability (87.7%, compared to 85.7% in LandSys I) for land-use change from Year 1990 to 2000. It is also found that either increasing hidden layers in ANNs or the use of multiagent models improves prediction accuracy. A comparison between LandSys I and II indicates that both models are viable; however, LandSys II is freely transferable and is more suitable for land-use forecasting, whereas LandSys I is more appropriate for evaluating the interconnections between land use and its affecting variables.

The induced traffic model is an essential component of travel demand analysis, which has been primarily researched with elasticity models in the United States and U.K. This paper aims to find the most suitable elasticity model based on the set of panel data regarding annual observations of 30 cities and provinces across China (except Chongqing city) for the years 1990 to 2010. To derive the ideal elasticity model, several basic elasticity models are included; among them are the elasticity-based model, distributed lag model, growth model, and fixed-effect model. Advanced elasticity models, such as the three stages of least squares (3SLS) are also discussed. According to relative researches and data collection, any increase of passenger kilometers of transport (PKT) with the growth of lane kilometers is considered induced traffic and is routinely used as such in this paper. Lane kilometers in China are found to have a statistically significant relationship with PKT measurements of approximately 0.026–0.274 in the short term and 0.367–0.773 in the long term. Population and gross regional product (GRP) numbers are also considered in basic elasticity models. Based on the detailed analysis of empirical results, the 3SLS is judged as the best suitable model for China. It can reflect the time effect, consider endogenous variables (including congestion and vehicle stock), and eliminate the simultaneity bias.

The concept of urban resilience has taken a leading edge by incorporating the multiscalar interactions within an urban system, revealing the short- and long-term impacts, spatial dependencies, and inequalities. The issue now is to enable local authorities and urban stakeholders to grasp and apply the resilience approach. Technical networks and urban services supporting urban development (drinking water supply, public transportation, etc.) are an interesting case study to apply the resilience concept. The urban resilience approach, tested with the managers of service provision in the City of Paris, demonstrates the effectiveness of integration and collaboration. First, an autodiagnosis realized with each manager identifies the service dependencies and its capacity for continuous operation in case of disturbance. Then workshops raise manager awareness of their interdependencies and feed the discussion toward technical and organizational solutions in an integrated approach. This macroscopic analysis is then completed by a territorial assessment of urban service resilience. In doing so, the spatial and temporal dimensions emphasize gaps but also margins of manoeuver in managing resilient urban services. Our results show that manager strategies can be focused on protection, adaptation, or recovery of their service. However, these are sometimes contradictory and threaten the resilience of the whole system. Indeed, in highlighting the different strategies set up by managers, the region’s resilience can be discussed at different scales: the urban service, the system of urban services, the City of Paris, and the Parisian metropolis. Then we emphasize the difficulties in applying the resilience concept and suggest solutions to improve the conditions for urban resilience and sustainability.

The primary objective of the study is to examine the interplay between unregulated urban growth and residential land market pricing. This interplay is examined in the context of Bangalore, which is the one of the fasted growing cities in Asia through a few key research questions. (1) What are the factors contributing to the exponential growth and sprawl of Bangalore? (2) What are the structural factors determining residential land market prices? (3) How does the regulated and unregulated land development processes affect land market prices in growing urban systems such as Bangalore? And (4) what are the institutional challenges and opportunities for improving the land market efficiency in the city? Beside the use extensive secondary data, including spatial data generated through satellite imageries and land conversion data collected from the District Land Registration Office, the study has used 720 actual land transaction price data over 2005–2010 periods from 9 fast-growing land market locations in Bangalore. The data set is treated as unbalanced panel data. The structure of residential land price is examined by developing a hedonic price model, using random effects multivariate regression. The model estimated that nearly 61% of the residential land price in Bangalore is determined by structural factors such as distance from the city business district, level of infrastructure, intervention of development agency, etc. One of the important findings from the analyses is that these structural factors could be used to bridge the gap between registered and market land prices and to address distortions in the land market efficiency. The paper concludes that the scarcity effects of regulated planning practices and speculation effects of unregulated land markets have contributed to the significant growth in land prices in Bangalore, although, the supply effects of unregulated land market activities have moderated the price increase and improved the land access. The paper suggests that unless the state and local governments implement efficient land management and urban fringe development policies, the city will soon experience the diseconomies of urban sprawl.

Public resources such as transportation, hospitals, parks, and schools are important factors in housing prices. However, studies on property value have mainly concentrated on transportation, and few studies have focused on the effect that green space has on property values. Researchers have mainly focused on specific parks within different communities rather than parks (on a larger scale) to study the average impact of green space on housing prices. Therefore, the objective of this research is to quantify the effect of public resources on property value, especially green space, using the hedonic pricing method (HPM). This paper focuses on 71 parks within Shenzhen to make results universal. Transaction price data and the structural attributes of 6,473 dwelling units were collected. This paper looks at HPM from three dimensions: structural attributes, location variables, and environmental variables. The results showed that (1) proximity to a central business district (CBD) produced the greatest effect on housing prices, followed by distance to park, distance to school, distance to arterial road, and distance to subway; (2) proximity to a park noticeably contributes to housing prices at 0.041%, and housing prices decline at a rate of 20,920  CNY  $(\mathrm{US}\$\mathrm{3,356})/\mathrm{km}$ depending on distance to the nearest park; and (3) the average influence radius of Shenzhen parks was 1.73 km, and the 71 parks could promote an increase in value across ${412.14\mathrm{km}}^2$ of land. This research will be helpful in residential housing purchase decision-making, for reasonable estate development layouts (for developers), and for governments (in terms of increasing environmental tax to promote green space preservation).

Supplying affordable housing for urban lower- and medium-income classes has always been considered an important planning objective. The policies of Iran’s fourth and fifth development plan (referred to as Maskan-e-Mehr or Kindness Housing Project) is intended to supply more affordable housing for the urban low-income classes. For this purpose, the state sector has strove to reduce the average house price as much as possible through cession of land in cities and new towns surrounding metropolises. In turn, families just have to pay the housing construction. Unfortunately, the lack of suitable services and facilities in these areas has resulted in an increase in household transportation costs. Therefore, the present research work deals with evaluating the affordability level of these houses through a new index of housing affordability, which simultaneously considers housing and transportation costs. The study revealed that high transportation costs that result from inadequate accessibility to public transportation and neighborhood services, and high payback of the monthly installments of the housing loan from the other side has resulted in spending more than 45.2% of the family income on housing construction and more than 25.8% on commuting. This means, in general, about 71% of the families’ income is spent on housing and transportation combined; these figures show lack of affordability of these houses for target groups (low-income classes).

As an effective approach to sustainable urban planning, integrated urban land-use zoning can contribute to fully understanding the integrated characteristics of urban land-use system, indicating the trend and possibility of land-use transformation, and thus mapping the spatial direction of urban development. However, compared with various case studies on land-use intensity, few land-use zoning is conducted with a special concern on land-use transformation. This paper used Shenzhen City in China as a case study to establish a systematic indicators model for integrated urban land-use zoning with a focus on both current intensity and structure of land-use system and transformation potential derived from socioeconomic system, and then to direct associated spatial development of urban growth in the future. The results show the following: (1) compared with traditional land-use degree index, the revised one through impervious surface area is more suitable in highly-urbanized area for its effectiveness in characterizing small differences among various assessing units; (2) according to current status and transformation potential of urban land-use system, four land-use zones are clustered with the application of self-organizing feature map method and aggregation index, i.e., transfer development zone, moderate development zone, prior development zone, and restrict development zone; and (3) five spatial axes of urban development associated with the zoning scheme are in high accordance with urban comprehensive plan of Shenzhen City. Therefore, the proposed integrated land-use zoning model is effective to characterize current land-use system, and its transformation potential exerted by socioeconomic system, and thus to make certain the primary landscape functions of various land-use zones and provide practical guidance for urban planning.

Rapid urbanization has generated great pressure on natural resources. This research paper illustrates the utility of linking socioeconomic and remotely sensed imagery in order to investigate the interaction between ecological and socioeconomic processes within the context of urban growth. The approach focuses on the vegetation degradation index (VDI) developed from time series SPOT-VGT NDVI, the normalized difference vegetation index based on vegetation data provided by the vegetation sensor onboard the SPOT satellites. The VDI value of each square kilometer pixel has been calculated to depict spatial pattern of vegetation degradation, which are then aggregated into the city level. In terms of urbanization, 13 factors have been chosen and valued from statistics books and vector digital maps. With the sample set of 50 cities in the Yangtze River Delta region of China, spearman correlation analysis and multiple regression analysis have been adopted to investigate the causal relationships between urbanization and vegetation degradation. The findings are as follows: First, three hot-spot areas in vegetation degradation have been identified, which are spatially correlated with urban land expansion. The composite index of VDI has been manifested as an effective tool for assessing vegetation degradation. Second, economic and demographic variables, rather than the urban land expansion variables, have been verified to be the determinant factors for vegetation degradation. The rise of GDP growth rate, population growth or GDP per capita has significantly deepened regional vegetation degradation. Third and finally, the distinctively local findings that incomplete urbanization and idling cropland have probably increased vegetation degradation rates are worth noting. Although further studies are required for probing into detailed mechanisms and universality, the specific findings may provide a reference to similar studies, and should be quite useful for policy makers.

Urban green spaces play a key role in the improvement of environmental quality, livability, and sustainability of towns and cities. The aim of this paper is to elicit the willingness of the population of Passo Fundo, a town in southern Brazil, to pay for improvements, maintenance, and conservation of a park situated in the Cidade Universitária (University Campus) subdivision. After the preliminary description of the current situation of the park, a scenario was defined for environmental valuation offered by proposed improvements according to different experts in urban and environmental planning. A total of 338 households in the urban area of Passo Fundo were surveyed through the application of a questionnaire and by the contingent valuation method. An economic value between R$964,560.00 (US$550,547.94) and R$2,531,970.00 (US$1,445,188.35) was obtained for the improvement, maintenance, and conservation of the park. Also, a relationship was observed between the socioeconomic characteristics of the population and willingness to pay. The analysis of economic viability for the investments in this park showed a positive net present value.

This paper aims to investigate the impacts of housing affordability, which can be denoted as the ratio of housing price (HP) and monthly expense per person (EXP), travel time to the city center, distance to a subway station, and schooling on residents’ apartments purchasing behavior in Dalian, China. The paper employed a logit model based on stated preference (SP) data. Results show that travel time to the city center (by subway) and housing affordability have negative effects on individual utility. This reveals that residents tend to buy apartments near the city center based on their income. Considering a series of negative external factors, distance to a subway station is positive to utility. Moreover, the willingness for residents to pay for different attributes varies according to their levels of EXP. At last the elasticity of different variables is analyzed and 180 additional data points are used to test the model. The testing result shows that the model can satisfy the basic requirement.

Urbanization has substantially altered the landscape throughout the world, and most previous studies have concentrated in areas with fast urbanization. Urbanization with moderate rates has received relatively less attention. Here, the urban patterns and dynamics in two moderately developed Chinese cities (i.e., Nanjing and Xi’an) are analyzed and compared using multitemporal Landsat Multispectral Scanner (MSS), Thematic Mapper (TM), and Enhanced Thematic Mapper Plus ($\mathrm{ETM}+$) images of circa 1980, 1985, 1990, 1995, 2000, 2005, and 2010 integrated with landscape metrics and urban growth type analysis. Results showed that both cities experienced a rapid expansion of urban land from 1980 to 2010, with a 7.2 and 8.5 times increase for Nanjing and Xi’an, respectively. The urbanization process of both cities can be divided into two stages (the diffusion phase and the transition period from diffusion to coalescence) that were roughly consistent with the phase oscillation theory of urban development. The first phase was during 1980–1995 for Nanjing and 1980–1990 for Xi’an, characterized by scattered development of new urban areas, an increase of the number of patches (NP), a decrease of mean patch size (MPS) and mean Euclidean nearest-neighbor distance (ENN_MN) for urban land, and high proportion of outlying urban growth type, resulting in increasing landscape fragmentation. The second phase was from 1995 to 2010 for Nanjing and from 1990 to 2010 for Xi’an when the newly developed urban areas became aggregated and compact, NP increased slowly, MPS increased, ENN_MN generally remained stable, and edge-expansion became the dominant urban growth type. The detailed quantitative analysis on the general trends of urbanization and urban growth patterns in Nanjing and Xi’an provide insights for future efforts on a comprehensive understanding of urbanization in China.

The balance between overall economic growth and protection of the environment is an important research topic of urban sustainable development. In 2005, Shenzhen promulgated the regulations, Administrative Regulations of Shenzhen Municipality on the Essential Area for Protecting Ecology [abbreviated as essential area policy (EAP)], which limited development to protect ecology. In order to evaluate the effects of this policy, a computer model was used to simulate land-use change based on a land-use change survey dataset of Shenzhen, a typical rapid urbanization area, under four scenarios. The writers aimed at developing a clear understanding of not only the effects of land protection policies for urban ecosystems but of a well-grounded prospect for regionally coordinated development as well. Five landscape structure metrics were chosen to describe the landscape pattern, including (1) number of patches, (2) mean patch area, (3) landscape shape index, (4) aggregation index, and (5) contagion index. In calculating and comparing these landscape metrics, the results support the conclusion that facing pressure from urban sprawl, agroecological land, water, and other nature-dominated areas shrink to high-altitude regions, and many small landscape patches disappear altogether, especially in the mixed periurban region in each scenario. The rapid growth of construction zones causes landscape fragmentation and renders the shape of the urban landscape more regular and smooth. However, EAP can keep small land patches from being developed into built-up areas; improve the percentage of agroecological land, water, and other nature-dominated areas within protected zones; and impel the relocation of these kinds of land-use from outside to inside the zone. The EAP affects the landscape pattern by increasing the mean area of each patch and the number of patches. If EAP were implemented in 2008, the number of patches and the landscape shape index would be relatively higher, whereas the aggregation and contagion indices would be lower than those resulting from nonimplementation. If EAP were implemented in 2008 but abolished in 2013, the number of patches and the landscape shape index would decrease, while the aggregation and contagion indices would increase. In contrast, if EAP were implemented in 2013, the number of patches and the landscape shape index would increase, while the aggregation and contagion indices would decrease. Delimitation of the boundary of an essential area is a critical factor in designing an effective policy. This paper enables land planners to understand the effects of EAP and highlights its importance as a tool for policymakers and stakeholders.

Urbanization in India is neither unique nor exclusive, but is similar to a worldwide phenomenon and has led to the development of urban sprawl, as it has elsewhere in the world. In the context of rapidly evolving policy frameworks in India, this article assesses the extent to which urban planning policies address sprawl. Local development plans of 53 cities across India are analyzed using content analysis and grounded theory. The study reveals that cities in India are not completely embracing smart-growth strategies in their development plans, and the use of smart-growth strategies differs among highly populated metropolitan cities versus less-populated cities. The study identified that four barriers—conventional urban planning mindset, lack of incentive-based practices and resources, ad-hoc planning, and lack of integrated land use transportation and environmental planning—impede smart-growth strategies in India. Furthermore, the results reveal a theory of planning action, which urban planners may tend to incorporate in their early stages of planning steps to address sprawl before they move toward more complex political policies.

Urban rehabilitation has long been a major concern for academics, practitioners, and public authorities. The decline cycle of city centers in many countries, particularly in Europe and the United States, involves deteriorating conditions in housing, which lead to a decrease in the population, moving toward suburban areas in the well-known phenomenon called urban sprawl. Rehabilitation has difficulties in succeeding within a fully liberalized market, and usually requires public intervention at different levels to stimulate the renewal of housing, particularly in historical city centers. This paper reflects on the roles of public administration at different levels. It leverages the main conclusions on the Portuguese experience, whose lessons may be valuable to other countries.