Re-reuse of regenerated brownfields: Lessons from an Eastern European post-industrial city

Martinát, Stanislav; Navratil, Joseph; Hollander, Justin B.; Trojan, Jakub; Klapka, Pavel; Klusáček, Petr; Kalok, David

doi:10.1016/j.jclepro.2018.03.313

Cited by 64 publications

(43 citation statements)

References 58 publications

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“…Lange & McNeil (2004) found that the regeneration of brownfields that are located near airports, near the city centres or rail stations is developing faster. Martinat et al (2018) warn that brownfield regeneration is closely interconnected with their perception by future users of particular sites and found out that the perception of regeneration significantly differs according to gender. Navratil et al (2018) in their study documented that heritage preservation of sites is one of the factors of key importance when planning the regeneration project.…”

Section: The Theoretical Framework Of the Studymentioning

confidence: 99%

Categorization of Impact of the Selected Variables for Potential Brownfield Regeneration in the Czech Republic by Means of Correspondence Analysis

Turečková¹,

Nevima²,

Škrabal³

et al. 2019

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Brownfields are undesirable urbanistic heritage and their occurrence is associated with a number of negative effects, which our society tries to minimize repeatedly, both successfully and unsuccessfully. Especially in the context of the multi-perspective concept of sustainable development, the issue of brownfields is accentuated with the intention to reuse abandoned areas that have lost their original use and regenerate them in a way that enriches not only individual stakeholders but generally the whole society. Although each brownfield is unique within its set of partial characteristics, it is possible to determine by means of mathematical-statistical methods the key patterns that are important for brownfields in terms of their overall nature. The identification of these common patterns across a selected set of brownfields is important for establishing of general recommendations for their potential regeneration. In our paper, we proceeded from the analysis of 460 non-regenerated brownfields located in the Czech Republic, and by means of correspondence analysis we determined which categories most influence the potential brownfield regeneration from the perspective of a two-dimensional (stage) approach. Information on brownfields was taken from the publicly available database of the state-funded company the CzechInvest for 2018 and supplemented by authors with other relevant variables. The analysis of the data revealed factors that may have a major impact in the initial phase of the decision on potential brownfield regeneration, and at the same time factors that do not seem to be substantial for regeneration. The applicability of the results of our analyses creates space for better-targeted brownfield regeneration policies, especially in the area of specifications for calls for brownfield regeneration projects, their financial support, implementation of process innovations, etc.

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Section: The Theoretical Framework Of the Studymentioning

confidence: 99%

Categorization of Impact of the Selected Variables for Potential Brownfield Regeneration in the Czech Republic by Means of Correspondence Analysis

Turečková¹,

Nevima²,

Škrabal³

et al. 2019

View full text Add to dashboard Cite

show abstract

“…It was also detected in the study by Longo and Campbell [3] that the more prosperous the region is, the more likely it is to be regenerated. Martinat et al [4] warn that brownfield regeneration is closely interconnected with the perception by future users of particular sites and found out that the perception of regeneration significantly differs according to gender. Navratil et al [5] in their study documented that heritage preservation of sites is one of the factors of key importance when planning a regeneration project.…”

Section: Literature Reviewmentioning

confidence: 99%

Uncovering Patterns of Location of Brownfields to Facilitate Their Regeneration: Some Remarks from the Czech Republic

et al. 2018

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Abstract:The issue of brownfield regeneration is closely connected to balanced and sustainable development of regions, towns, and cities as it endeavors to reuse buildings and sites that have already lost their original use, but at the same time offers a possibility to generate new beneficial activities for the whole society that exceed just material or physical changes of the brownfield sites. The regeneration of every brownfield is usually a highly site-specific issue and individual and unique impacts of regeneration on the particular locality are obvious. Yet, several patterns in sets of non-regenerated brownfields can be identified. By finding and defining such patterns, a framework of indicators to facilitate brownfield regeneration can be created and the importance and strength of a particular indicator can be defined. By means of the analyses, we are able to recommend various relevant and most suitable approaches with regards to brownfield regeneration in individual regions. We have employed Factor Analysis (FA) for the identification of key factors of brownfield regeneration. In particular, Principal Component Analysis (PCA) was applied to conduct analyses of 1304 non-regenerated brownfields located in seven regions of the Czech Republic (NUTS 3 level). Data were obtained from publicly available brownfield databases of individual regional administrations. By means of Factor Analysis, it was ascertained that the most frequent factor that is typical for the surveyed non-regenerated brownfields is the ownership. The second most frequent factor is the size of the brownfields. As the third factor according to importance, the distance between the location of the individual brownfield and the municipality of extended powers (the so-called small district) was identified. By taking into account the results of the conducted analyses, brownfield regeneration policies of individual regions might be adapted to be more suitably targeted.

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“…Combination of lower rents, morphological, functional and social diver-sity, attractive industrial premises (Hutton, T.A. 2004;Martinát, S. et al 2018) and presence of universities can foster clustering of creative firms and workers in inner cities of COIR. To sum up, we expect smaller presence of CI in COIR, more concentrated firm structure and higher share of technically related CI -NACE 18 and 71.…”

Section: Metropolitan Hinterlandsmentioning

confidence: 99%

How do various types of regions attract creative industries? Comparison of metropolitan, old industrial and rural regions in Czechia

Ženka

Slach

2018

HunGeoBull

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In this paper we aim to describe and explain current spatial distribution of creative industries in Czechia. We ask to what extent are localisation patterns of creative industries influenced by specific local contexts. Therefore, we employed a typology of regions (close to local labour areas) that may explain spatial distribution of creative industries: metropolitan cores, metropolitan hinterlands, old industrial regions, urban and rural regions. We use general linear models combining the regional typology as a fixed factor and four covariates -employment density, density of cultural industries, mean firm size in creative industries and diversity of economic activities. We employed horizontal localisation quotient of regional employment in creative industries for the year 2014 as a dependent variable. Our main finding is that the regional typology explains a higher share of variability of the dependent variable (relative specialisation in creative industries) than any other explanatory variable. However, after exclusion of metropolitan cores, the model lost a significant amount of its explanatory power. Urban size/density and position in urban hierarchy are the key explanatory variables. We found only limited empirical evidence that regional contexts affect localisation of CI -regions of similar population/economic size do not differ significantly in spatial concentration of CI.

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Re-reuse of regenerated brownfields: Lessons from an Eastern European post-industrial city

Abstract: The manuscript did undergo copyediting, typesetting, and review of the resulting proof before it was published in its final form.

Cited by 64 publications

References 58 publications

Categorization of Impact of the Selected Variables for Potential Brownfield Regeneration in the Czech Republic by Means of Correspondence Analysis

Categorization of Impact of the Selected Variables for Potential Brownfield Regeneration in the Czech Republic by Means of Correspondence Analysis

Uncovering Patterns of Location of Brownfields to Facilitate Their Regeneration: Some Remarks from the Czech Republic

How do various types of regions attract creative industries? Comparison of metropolitan, old industrial and rural regions in Czechia

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