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Many cities of various types are distributed in the large area of mountainous regions in China. In these cities, there are acute contradictions between man and earth. Considering that the space growth mode of mountainous cities is widely different from that of flatland cities, the fractal method was adopted in the research aimed at demarcating the urban growth boundary of mountainous cities. The fractal features of the investigated mountainous cities in space were figured out via inference from their function, dimension, region, grade, and environment, and the fractal mode and conceptual framework of urban growth boundary of Qin-Ba mountainous region were constructed according to some concepts and methods such as fractal dimension, fractal network, and fractal order. In the research, the traditional urban growth boundary form-was decomposed into scattered points (point form), paths (linear form), and patches (plane form) to form the fractal theory units for the research of urban growth boundary, and the leading idea, procedure, and control method for “fractal demarcation of urban growth boundary” were established to provide strategies for demarcation of urban space growth boundary of Qin-Ba mountainous region.

This study applies theoretical perspectives from urban, environmental, and organization studies to examine if “smart growth” represents an ecological restructuring of the political economy of conventional urban development, long theorized as a “growth machine” (Molotch, H. (1976) The city as growth machine: Toward a political economy of place. American Journal of Sociology, 82, 309–332; Logan & Molotch, 2007); the purpose is to determine if there is a “smart growth machine.”

Nine smart growth projects (SGPs) in four cities in California and Oregon were identified and semistructured interviews were held with the respective developers, architects, and civic officials involved in their implementation process. Comparative, descriptive, and grounded approaches were used to generate themes from interviews and other data sources.

The findings suggest that an ecological modernization of urban political economy occurs through the coordination of entrepreneurial action, technical expertise, and “smart” regulation. Individual and institutional entrepreneurs shift the organizational field of urban development. Technical expertise is needed to make projects sustainable and financially feasible. Finally, a “smart” regulatory framework that balances regulations and incentives is needed to forge cooperative relationships between local governments and developers. This constellation of actors and institutions represents a smart growth machine.

The author questions whether urban growth can become “smart” using an original study of nine SGPs in four cities across California and Oregon.

This paper discusses the urban management challenges in the Greater Kuala Lumpur area. Before examining Greater Kuala Lumpur's economic and social environment, we will look at the factors that make it a competitive and fiscally sound entity. When considering urban development and redevelopment, we consider how proposed and ongoing projects, as well as plans, hierarchical links, and road networks, contributed to the increase. Because there is no urban growth boundary, land use change and rural encroachment, as well as environmental degradation and the impact of national economic projects on urban expansion, are both rapid and linear in the analysis. This paper also considers how to manage linear development that results in the creation of new suburbs. Finally, we propose strategies for achieving sustainable urban expansion and management by balancing the financial and governance capacities of Greater Kuala Lumpur local governments.

The purpose of this paper is to examine the relationship between industrial sector growth, inequalities and urban poverty reduction

The paper used static panel data analysis. However, the tests suggest that there are no state-specific effects; hence, the pooled panel regression techniques are used for the analysis.

The findings of the paper suggest that the industrial sector growth exert no significance on urban poverty while the urban wholesale and retail services growth is found to be substantially strong in reducing urban poverty. The results also indicate that there is no statistically significant evidence to conclude that higher incidence of urban poverty was due to the high degree of inequalities.

This paper has provided some helpful results in understanding the heterogeneous effects of sectoral components of growth of urban poverty in the presence of high income inequalities, but the limitation of this study is that there is no disaggregated poverty and growth data on different occupational activity.

There is a need to expand investment in the production and export manufacturing labor-intensive sectors; this will help increase the labor absorption rate of the industry and, thus, reduce poverty in the urban areas.

The paper improves on previous research on poverty in Nigeria by explicitly recognizing the effects of location and inequality.

Given the importance of growth-oriented entrepreneurship in the context of economic development and the need to understand how rural communities can be developed, the purpose of this research paper is to determine how the drivers of growth expectations differ between urban and rural settings.

The methodology is threefold: firstly, a descriptive analysis with non-parametric testing is conducted; then pooled regression model is used to analyse the predictors of growth expectations in both contexts, and finally, coarsened exact matching is used to identify possible self-selection bias.

In contrast to mainstream entrepreneurship theory, it is found that entrepreneurs’ intrinsic knowledge, skills and abilities are not significant in the rural-specific model. The only exception is entrepreneurs’ educational level, the importance of which is emphasised as a pivotal factor in increasing high-growth ventures in rural communities. Additionally, when self-selection is eliminated, rurality worsens growth intentions.

There is evidence that some growth-oriented entrepreneurs self-select into rural communities. Because the high-growth entrepreneurial dynamics in rural areas are unique, public policies should target purpose-driven entrepreneurial education. This includes encouraging “lifestyle entrepreneurship” (e.g. retirees returning to rural areas to become entrepreneurs), preventing entrepreneurial brain drain in rural areas and attracting highly educated urban entrepreneurs to exploit opportunities in rural areas.

This research attempts to contribute to the ongoing debate regarding the factors that drive high-growth entrepreneurs in rural areas by analysing rural entrepreneurs in the high-growth context of a developing economy. The focus is on Chile – a country that is rarely investigated compared to the USA or Europe – to extend the literature on high-growth ventures and entrepreneurial ecosystems.

Despite the enormous need to succeed in the urban model, scientists and policymakers should work consistently to create blueprints to regulate urbanization. The absence of coordination between the crucial requirements and the regional strategies of the local authorities leads to a lack of conformance in urban development. The purpose of this paper is to address this issue.

This study intends to manage future urban growth patterns using integrated methods and then employ the results in the genetic algorithm (GA) model to considerably improve growth behavior. Multi-temporal land-use datasets have been derived from remotely sensed images for the years 1990, 2000, 2010 and 2020. Urban growth patterns and processes were then analyzed with land-use-and-land-cover dynamics. Results were examined for simulation and utilization of the GA.

Model parameters were derived and evaluated, and a preliminary assessment of the effective coefficient in the formation of urbanization is analyzed, showing the city's urbanization pattern has followed along with the transportation infrastructure and outward growth, and the scattering rates are high, with an increase of 5.64% in building area associated with a decrease in agricultural lands and rangelands.

The research achieved a considerable improvement over the growth behavior. The conducted research design was the first of its type in that field to be executed to any specific growth pattern parameters in terms of regulating and policymaking. The method has integrated various artificial intelligence models to monitor, measure and optimize the projected growth by applying this design. Other research on the area was limited to projecting the future of Amman as it is an urbanized distressed city.

Over the last 30 years, despite immense and increasing expenditures by the federal government for disaster preparedness and relief, both catastrophic and chronic losses from natural hazards have continued to increase at an alarming pace. Although earthquakes, floods, tornadoes, and hurricanes account for the largest portion of these natural hazard losses, wildfire increasingly represents significant disaster losses of well over a billion dollars annually. There is considerable concern that losses from wildfires will only increase in the U.S. as some of the highest growth rates in the nation, both metropolitan and nonmetropolitan types of growth, are projected to continue in states with extensive wildland fire hazard areas. The land development patterns associated with that growth are problematic because so much of the development in the last 30 years (and that is still occurring) is not being steered away from the highest wildfire hazard settings, nor are adequate steps being taken to ensure that when development occurs in high wildfire hazard zones appropriate mitigation is used to reduce the vulnerability of people and property to loss. Fortunately, those anticipated future wildfire losses have a great potential to be reduced provided state and local governments take the initiative to create partnerships to ensure “safer” and “smarter” patterns of land development occur in and near wildland–urban interface areas. This chapter explores wildfire mitigation planning as an integral component of “safe smart growth” for wildland–urban interface communities.