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The San Francisco Peninsula’s Great Estates: Part II

Streatfield, David C. (2012). The San Francisco Peninsula’s Great Estates: Part II. Eden, 15(2), 1 – 17.

Abstract

This article discusses the landscaping of American country estates built in late 19th century in San Francisco Peninsula. These estates are mentioned to have been influenced by the growing popularity of gardening in Europe. Andrew Jackson, America's first landscape architecture practitioner, is cited for promoting garden styles derived from English precedents. Some of the noteworthy estates built during the first three decades of 20th century are also described like New Place and Green Gables.

Keywords

Landscape Gardening; Country Homes; Gardening; Landscape Architecture; Europe; Jackson, Andrew

Understanding the Motivations of Coastal Residents to Voluntarily Purchase Federal Flood Insurance

Brody, Samuel D.; Highfield, Wesley E.; Wilson, Morgan; Lindell, Michael K.; Blessing, Russell. (2017). Understanding the Motivations of Coastal Residents to Voluntarily Purchase Federal Flood Insurance. Journal Of Risk Research, 20(6), 760 – 775.

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Abstract

Federally-backed flood insurance is the primary mechanism by which residents in the United States (US) prepare for and recover from floods. While there is a growing literature on the general uptake of flood insurance, little work has been done to address the factors motivating residents to voluntarily buy and maintain federally-based insurance policies. We address this issue by conducting a survey of coastal residents in four localities in Texas and Florida. Based on survey responses, we quantitatively examine the factors influencing whether residents located outside of the 100-year floodplain obtain insurance policies when it is not required. Using two-sample t-tests and binary logistic regression analysis to control for multiple contextual and psychological variables, we statistically isolate the factors contributing most to the decision to purchase insurance. Our findings indicate that a resident located outside the 100-year floodplain who has voluntarily purchased federal flood insurance can be characterized, on average, as more highly educated, living in relatively expensive homes, and a long-time resident who thinks about flood hazard relatively infrequently but who, nonetheless, thinks flood insurance is relatively affordable. Unexpectedly, the physical proximity of a respondent to flood hazard areas makes little or no discernible difference in the decision to obtain flood insurance.

Keywords

Action Decision-model; Hazard Adjustments; Risk; Perceptions; Adoption; Florida; Losses; Determinants; Preferences; Responses; Insurance; Floodplain; Purchase Decision; Texas

Low-income Housing and Crime: The Influence of Housing Development and Neighborhood Characteristics

Tillyer, Marie Skubak; Walter, Rebecca J. (2019). Low-income Housing And Crime: The Influence Of Housing Development And Neighborhood Characteristics. Crime & Delinquency, 65(7), 969 – 993.

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Abstract

This study examines the distribution of crime across various types of low-income housing developments and estimates the main and interactive effects of housing development and neighborhood characteristics on crime. Negative binomial regression models were estimated to observe the influence of security and design features, neighborhood concentrated disadvantage, residential stability, and nearby nonresidential land use on crime at the housing developments. The findings suggest that low-income housing developments are not uniformly criminogenic, and both development characteristics and neighborhood conditions are relevant for understanding crime in low-income housing developments. Implications for prevention are discussed.

Keywords

Violent Crime; Micro Places; Guardianship; Criminology; Multilevel; Proximity; Patterns; Context; Trends; Impact; Low-income Housing; Criminal Opportunity; Concentrated Disadvantage

Exploring Post-Incarceration Residential Trajectories: Indicators of Housing Stability During the Re-entry Process

Walter, Rebecca J.; Caudy, Michael; Galvan Salcido, Christine; Ray, James; Viglione, Jill. (2021). Exploring Post-Incarceration Residential Trajectories: Indicators of Housing Stability During the Re-entry Process. Housing, Theory & Society, 38(3), 300 – 319.

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Abstract

Extant research on housing instability focuses on external housing barriers but limited research exists on individual-level indicators of housing stability for individuals returning to society from incarceration. This study addresses this gap with data collected from 70 individuals recently released from incarceration who returned to Bexar County (San Antonio, Texas) that were not placed in specific housing programmes, leaving them to seek housing independently. The study explores residential trajectories and the utility of individual-level characteristics, specifically readiness for change, in relation to housing stability. The findings reveal the importance of assessing the dynamics of each individual living situation since many of the participants are housed but not in stable housing situations. Furthermore, readiness for change (specifically action, self-sufficiency, and human agency) is found to be a significant indicator of housing stability and may represent an important intervention target for re-entry and reintegration programmes. [ABSTRACT FROM AUTHOR]; Copyright of Housing, Theory & Society is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Keywords

Housing Discrimination; Housing; Self-reliant Living; Housing Instability; Housing Stability; Re-entry; Readiness For Change; Residential Trajectories

Transport Impacts of Clustered Development in Beijing: Compact Development Versus Overconcentration

Yang, Jiawen; Shen, Qing; Shen, Jinzhen; He, Canfei. (2012). Transport Impacts of Clustered Development in Beijing: Compact Development Versus Overconcentration. Urban Studies, 49(6), 1315 – 1331.

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Abstract

This research aims to inform the compact city discussion with a case study of Beijing, where urban planning has emphasised clustered suburban development in the past half-century. It uses three decades of census data to describe Beijing's spatial development trajectory and a household survey to assess its transport impacts. The research reveals an overconcentration of urban activities as a result of the featureless expansion of the central built-up area and the absorption of the suburban clusters; and, a lengthened commuting time stemming from the observed spatial development pattern. Beijing's experience adds to the existing literature by informing the search for good city forms in urban areas of high density. It is essential to differentiate compact development from overconcentration when combating sprawling development. Developing and maintaining suburban nodal characteristics around public transit can reduce travel in high-density urban areas.

Keywords

Jobs-housing Balance; Commuting Patterns; Urban; Growth; City; Towns

The Residential Effect Fallacy in Neighborhood and Health Studies Formal Definition, Empirical Identification, and Correction

Chaix, Basile; Duncan, Dustin; Vallee, Julie; Vernez-moudon, Anne; Benmarhnia, Tarik; Kestens, Yan. (2017). The Residential Effect Fallacy in Neighborhood and Health Studies Formal Definition, Empirical Identification, and Correction. Epidemiology, 28(6), 789 – 797.

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Abstract

Background: Because of confounding from the urban/rural and socioeconomic organizations of territories and resulting correlation between residential and nonresidential exposures, classically estimated residential neighborhood-outcome associations capture nonresidential environment effects, overestimating residential intervention effects. Our study diagnosed and corrected this residential effect fallacy bias applicable to a large fraction of neighborhood and health studies. Methods: Our empirical application investigated the effect that hypothetical interventions raising the residential number of services would have on the probability that a trip is walked. Using global positioning systems tracking and mobility surveys over 7 days (227 participants and 7440 trips), we employed a multilevel linear probability model to estimate the trip-level association between residential number of services and walking to derive a naive intervention effect estimate and a corrected model accounting for numbers of services at the residence, trip origin, and trip destination to determine a corrected intervention effect estimate (true effect conditional on assumptions). Results: There was a strong correlation in service densities between the residential neighborhood and nonresidential places. From the naive model, hypothetical interventions raising the residential number of services to 200, 500, and 1000 were associated with an increase by 0.020, 0.055, and 0.109 of the probability of walking in the intervention groups. Corrected estimates were of 0.007, 0.019, and 0.039. Thus, naive estimates were overestimated by multiplicative factors of 3.0, 2.9, and 2.8. Conclusions: Commonly estimated residential intervention-outcome associations substantially overestimate true effects. Our somewhat paradoxical conclusion is that to estimate residential effects, investigators critically need information on nonresidential places visited.

Keywords

Self-rated Health; Record Cohort; Physical-activity; Transportation Modes; Built Environment; Activity Spaces; Research Agenda; Risk-factors; Associations; Exposure

The Geographic and Sociodemographic Transformation of Multifamily Rental Housing in the Texas Triangle.

Walter, Rebecca J.; Caine, Ian. (2019). The Geographic And Sociodemographic Transformation Of Multifamily Rental Housing In The Texas Triangle. Housing Studies, 34(5), 804 – 826.

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Abstract

This study catalogues the location, clustering and sociodemographic distribution of the development of multifamily rental housing over the last five decades in the Texas Triangle, one of the fastest growing megaregions in the United States. The research reveals prior to the 1970s, apartments clustered in downtown areas; throughout the 1980s and 1990s, the development of apartments expanded to the suburbs and along major interstates; and in the 2000s, apartment growth continued in the peripheral areas while returning downtown. During this time period, apartments were developed most often in majority white, high-income and low-poverty neighbourhoods. These geographic and sociodemographic characteristics challenge widespread conceptions that equate multifamily rental housing with central city locations and low-income populations. The findings suggest that multifamily rental housing offers a powerful tool to increase residential density in downtown and suburban locations, while also accommodating a sociodemographically diverse population.

Keywords

Sociodemographic Factors; Rental Housing; Neighborhoods; Home Ownership; Housing Development; Apartments; Locational Patterns; Multifamily Rental Housing; Sociodemographics; Suburban Infill; Texas Triangle; City Centres; Central Business Districts; Housing; Poverty; Suburban Areas; Residential Density; Suburbs; Transformation; Catalogues; Density; Clustering; Income; Multiple Dwellings; Low Income Groups; Rentals; Catalogs; Texas; United States--us

What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic

Wang, Lan; Zhang, Surong; Yang, Zilin; Zhao, Ziyu; Moudon, Anne Vernez; Feng, Huasen; Liang, Junhao; Sun, Wenyao; Cao, Buyang. (2021). What County-level Factors Influence Covid-19 Incidence in the United States? Findings from the First Wave of the Pandemic. Cities, 118.

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Abstract

Effective control of the COVID-19 pandemic via appropriate management of the built environment is an urgent issue. This study develops a research framework to explore the relationship between COVID-19 incidence and influential factors related to protection of vulnerable populations, intervention in transmission pathways, and provision of healthcare resources. Relevant data for regression analysis and structural equation modeling is collected during the first wave of the pandemic in the United States, from counties with over 100 confirmed cases. In addition to confirming certain factors found in the existing literature, we uncover six new factors significantly associated with COVID-19 incidence. Furthermore, incidence during the lockdown is found to significantly affect incidence after the reopening, highlighting that timely quarantining and treating of patients is essential to avoid the snowballing transmission over time. These findings suggest ways to mitigate the negative effects of subsequent waves of the pandemic, such as special attention of infection prevention in neighborhoods with unsanitary and overcrowded housing, minimization of social activities organized by neighborhood associations, and contactless home delivery service of healthy food. Also worth noting is the need to provide support to people less capable of complying with the stay-at-home order because of their occupations or socio-economic disadvantage.

Keywords

Pandemics; Covid-19; Covid-19 Pandemic; Infection Prevention; Stay-at-home Orders; Structural Equation Modeling; United States; Communicable Disease Prevention; Influential Factors; Lockdown; Structural Equation Modeling (sem); Prevalence; Disease; Healthy Food; Social Activities; Counties; Neighborhoods; Housing; Built Environment; Prevention; Minimization; Socioeconomic Factors; Intervention; Health Care; Vulnerability; Occupations; Coronaviruses; Food Service; Disease Transmission; United States--us

Advancing Optimization of Hybrid Housing Development Plans Following Disasters: Achieving Computational Robustness, Effectiveness, and Efficiency

El-Anwar, Omar. (2013). Advancing Optimization of Hybrid Housing Development Plans Following Disasters: Achieving Computational Robustness, Effectiveness, and Efficiency. Journal Of Computing In Civil Engineering, 27(4), 358 – 369.

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Abstract

Following disasters, displaced families often face significant challenges to move from temporary to permanent housing. The Federal Emergency Management Agency is exploring alternative housing pilot programs to evaluate the possibility of providing quickly deployable, affordable housing that can serve both as temporary and permanent housing. Because of the complexities and costs associated with these programs, it is impractical to assume that accelerated permanent housing can fully replace the need for traditional temporary housing, especially in cases of large-scale displacements. A novel methodology was developed to evaluate the socioeconomic benefits of candidate configurations of hybrid housing plans, which incorporates both temporary and accelerated permanent housing developments. This paper presents the computational implementation and performance analysis of this novel methodology to offer a practical decision-support tool to emergency planners. To this end, genetic algorithms and integer-programming optimization models are formulated, and their performances are analyzed based on their effectiveness, efficiency, and robustness. In lieu of developing the integer-programming model, the paper also presents a linear formulation that overcomes the need to use logical operations to model fixed and variable cost components for developing housing projects. Results show the superior performance of integer programming, whereas genetic algorithms offer higher modeling flexibility.

Keywords

Decision Support Systems; Emergency Management; Genetic Algorithms; Integer Programming; Advancing Optimization; Hybrid Housing Development Plans Following Disasters; Achieving Computational Robustness; Achieving Computational Effectiveness; Achieving Computational Efficiency; Federal Emergency Management Agency; Housing Pilot Programs; Temporary Housing; Permanent Housing Developments; Decision-support Tool; Emergency Planners; Integer-programming Optimization Models; Logical Operations; Optimization; Disasters; Housing; Social Factors; Economic Factors; Computation; Hybrid Methods; Disaster Recovery; Accelerated Permanent Housing; Socioeconomic Welfare; Robustness; Effectiveness; Computational Efficiency; 0

The Residential Segregation of San Antonio, Texas in 1910: An Analysis of Ethno-racial and Occupational Spatial Patterns with the Colocation Quotient

Cordoba, Hilton A.; Walter, Rebecca J.; Foote, Nathan S. (2018). The Residential Segregation of San Antonio, Texas in 1910: An Analysis Of Ethno-racial and Occupational Spatial Patterns with the Colocation Quotient. Urban Geography, 39(7), 988 – 1017.

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Abstract

The segregation of cities can be traced to a time when the compartmentalization of space and people was based on factors other than race. In segregation research, one of the limiting factors has always been the geographic scale of the data, and the limited knowledge that exists of segregation patterns when the household is the unit of analysis. Historical census data provides the opportunity to analyze the disaggregated information, and this paper does so with San Antonio during 1910. A spatial analysis of residential segregation based on race, ethnicity, and occupations is carried out with the colocation quotient to map and measure the attraction of residents. Results reveal the presence of residential segregation patterns on different sectors of the city based on households' ethno-racial and occupational attributes; therefore, providing evidence of the existence of residential segregation prior to the commonly cited determinants of segregation of the 20th century.

Keywords

Housing Tax Credit; Local Indicators; New York; Association; Indexes; Cities; Scale; City; Differentiation; Environment; Residential Segregation; Colocation Quotient; San Antonio; Spatial Analysis