Vacant residential buildings as potential reserves: a geographical and statistical study

Huuhka, Satu

doi:10.1080/09613218.2016.1107316

Cited by 26 publications

(23 citation statements)

References 33 publications

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“…This approach raises the following questions: (i) What could this threshold actually be? Is 5% of the stock really the upper limit for a "normal mobility reserve" (Glock & Häussermann, 2004;Huuhka, 2016)? (ii) How is this threshold to be accurately calculated?…”

Section: Notesmentioning

confidence: 99%

Unused private and public buildings: Re-discussing merely empty and truly abandoned situations, with particular reference to the case of Italy and the city of Milan

Moroni

Franco

Bellè

2020

Journal of Urban Affairs

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There is much debate today over the problem of unused buildings. This debate is often conducted in alarmed and concerned tones. Our idea is that it is indispensable to reconsider the issue with greater critical reflection and some necessary distinctions: in particular, between situations and aspects relating to public buildings and situations and aspects relating to private buildings; and, within the latter category, between totally natural and legitimate situations and truly problematic ones. To this end, we shall focus on definitory issues, quantitative issues, ethical issues and policy issues. We shall do so with particular attention to the Italian situation, which we believe is especially challenging, and to a specific case study, the city of Milan. However, part of what we shall say also applies to other contexts.

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Section: Notesmentioning

confidence: 99%

Unused private and public buildings: Re-discussing merely empty and truly abandoned situations, with particular reference to the case of Italy and the city of Milan

Moroni

Franco

Bellè

2020

Journal of Urban Affairs

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“…Fewer houses in this community are likely to be abandoned and left vacant. From another perspective, deindustrialization and industrial and residential suburbanization made industrial and commercial areas decline in downtown Buffalo [9]. Thousands of manufacturing jobs were lost, and thousands of people left, as industry moved out.…”

Section: Significant Variable Analysis Of the Regression Modelsmentioning

confidence: 99%

“…The traditional industrial cities in this region suffered a rapid decline in industry and population, leaving behind thousands of abandoned residential houses [5][6][7][8]. As estimated by the American Community Survey (ACS), 16,842,710 vacant properties existed in the United States in 2016 [9]. In this study, we only focus on the vacant residential buildings, also called vacant houses.…”

Section: Introductionmentioning

confidence: 99%

“…As a typical central city in the US, Buffalo lost more than 70% of manufacturing jobs and more than 50% of the population since industry declined around the mid-1970s. As a result [10], such a large amount of abandonment properties brought serious social security and economic problems [9]. These vacant houses act as a neighborhood safety threat by creating conditions for crime.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al [26] measured the relationship between vacancy rate and central business district (CBD), then used a logit regression model to predict the vacancy rate, and reached the maximum value of R 2 , 81.5%. Huuhka et al [9] used both geographical and statistical methods, which showed that several characteristics help in our understanding of vacancy. Silverman et al [8] estimated the vacancy and abandonment in Buffalo, NY, using a linear regression model with various socioeconomic characteristics, and reached a maximum R 2 56.8%.…”

Section: Introductionmentioning

confidence: 99%

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Modeling the Census Tract Level Housing Vacancy Rate with the Jilin1-03 Satellite and Other Geospatial Data

Wang

Zou

et al. 2018

Remote Sensing

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The vacant house is an essential phenomenon of urban decay and population loss. Exploration of the correlations between housing vacancy and some socio-environmental factors is conducive to understanding the mechanism of urban shrinking and revitalization. In recent years, rapidly developing night-time remote sensing, which has the ability to detect artificial lights, has been widely applied in applications associated with human activities. Current night-time remote sensing studies on housing vacancy rates are limited by the coarse spatial resolution of data. The launch of the Jilin1-03 satellite, which carried a high spatial resolution (HSR) night-time imaging camera, provides a new supportive data source. In this paper, we examined this new high spatial resolution night-time light dataset in housing vacancy rate estimation. Specifically, a stepwise multivariable linear regression model was engaged to estimate the housing vacancy rate at a very fine scale, the census tract level. Three types of variables derived from geospatial data and night-time image represent the physical environment, landuse (LU) structure, and human activities, respectively. The linear regression models were constructed and analyzed. The analysis results show that (1) the HVRs estimating model using the Jilin1-03 satellite and other ancillary geospatial data fits well with the Census statistical data (adjusted R2 = 0.656, predicted R2 = 0.603, RMSE = 0.046) and thus is a valid estimation model; (2) the Jilin1-03 satellite night-time data contributed a 28% (from 0.510 to 0.656) fitting accuracy increase and a 68% (from 0.359 to 0.603) predicting accuracy increase in the estimate model of the housing vacancy rate. Reflecting socio-economic conditions, the luminous intensity of commercial areas derived from the Jilin1-03 satellite is the most influential variable to housing vacancy. Land use structure indirectly and partially demonstrated that the social environment factors in the community have strong correlations with residential vacancy. Moreover, the physical environment factor, which depicts vegetation conditions in the residential areas, is also a significant indicator of housing vacancy. In conclusion, the emergence of HSR night light data opens a new door to future microscopic scale study within cities.

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Vacant Buildings. Distinguishing Heterogeneous Cases: Public Items Versus Private Items; Empty Properties Versus Abandoned Properties

Moroni

Franco

Bellè

2020

Abandoned Buildings in Contemporary Cities: Smart Conditions for Actions

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Vacant residential buildings as potential reserves: a geographical and statistical study

Cited by 26 publications

References 33 publications

Unused private and public buildings: Re-discussing merely empty and truly abandoned situations, with particular reference to the case of Italy and the city of Milan

Unused private and public buildings: Re-discussing merely empty and truly abandoned situations, with particular reference to the case of Italy and the city of Milan

Modeling the Census Tract Level Housing Vacancy Rate with the Jilin1-03 Satellite and Other Geospatial Data

Vacant Buildings. Distinguishing Heterogeneous Cases: Public Items Versus Private Items; Empty Properties Versus Abandoned Properties

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