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How to measure susceptibility to degradation in large post-socialist housing estates?

100%

Warchalska-Troll A.

Prace Geograficzne

2012

issue 130

55-71

In this paper methods for measuring susceptibility to social and landscape degradation in large post-socialist housing estates (L H Es ) are proposed. This type of housing was especially popular in post-war Central and Eastern Europe run by communist regimes. As a result, L H Es today constitute a significant part of this region’s housing stock, therefore, their eventual decline would affect millions of people as well as considerable urban areas. This paper is designed to have an applied dimension. The research included a survey of the residents of six housing estates in Katowice (Poland), fieldwork, and statistical analysis using the chi-squared test. On this basis, several factors are evaluated according to their ‘degradation potential’. This leads to the creation of a model illustrating degradation processes taking place at L H Es . The decline in the quality of life is used as an analytical starting point. Research has shown that the large size of a given estate appears to be the most significant factor stimulating its decline. Other key factors are: low aesthetic qualities, poor maintenance of public spaces, weak social bonds, relative lack of public safety, and insufficient social infrastructure. In contrast, issues such as pollution, noise, undesirable surroundings and general management of the area appeared to have the least importance. The final result of the research procedure is a rating of the six studied estates on the basis of their susceptibility to degradation.

The selection of areas for case study research in socio-economic geography with the application of k-means clustering

63%

Warchalska-Troll A., Warchalski T.

Wiadomości Statystyczne. The Polish Statistician

2022

vol. 67

issue 2

1-20

Znane w statystyce techniki grupowania są rzadko wykorzystywane przez geografów do wyboru obszaru badań. Celem analiz opisanych w artykule było sprawdzenie możliwości zastosowania metody podziału k-średnich do wyboru jednostek przestrzennych (w tym przypadku gmin) do studiów przypadku. Dokonano tego poprzez rozwiązanie problemu metodycznego polegającego na optymalnym wyznaczeniu gmin do pogłębionych badań nad relacją między ochroną przyrody a rozwojem lokalnym i regionalnym w polskich Karpatach. Szczególną uwagę zwrócono na określenie odpowiedniej liczby skupień za pomocą metody łokcia (ang. elbow method) oraz statystyki pseudo-F (wskaźnika Calińskiego-Harabasza). Dane wykorzystane w analizach pochodziły z Głównego Urzędu Statystycznego i obejmowały okres 1999–2012. W rezultacie kilkustopniowej procedury wytypowano gminy: Cisna, Lipinki, Ochotnica Dolna, Sękowa, Szczawnica i Zawoja. Opisany w artykule przykład pokazuje, że metoda k-średnich, pomimo pewnych słabości, może być przydatna do tworzenia klasyfikacji i typologii prowadzących do wyboru obszarów do studiów przypadku ze względu na jej użyteczność oraz dostępność w oprogramowaniu typu open source. Zarazem jednak – z uwagi na stopień złożoności społeczno-ekonomicznych cech obszarów – zastosowanie tej metody w geografii społeczno-ekonomicznej może wymagać wsparcia interpretacji jej wyników analizą dodatkowych źródeł informacji oraz wiedzą ekspercką.

The grouping techniques which are known in statistics are rarely used by geographers to select a research area. The aim of the paper is to examine the potential use of the k-means clustering (partitioning) method for the selection of spatial units (here: gminas, i.e. the lowest administrative units in Poland) for case studies in socio-economic geography. We explored this topic by solving a practical problem consisting in the optimal designation of gminas for in-depth research on the interaction between nature protection and local and regional development in the Polish Carpathians. Particular attention was devoted to defining an appropriate number of clusters by means of the elbow method as well as the pseudo-F statistic (the Calinski-Harabasz index). The data for the analysis were mostly provided by Statistics Poland and covered the period of 1999–2012. The multi-stage procedure resulted in the selection of the following gminas: Cisna, Lipinki, Ochotnica Dolna, Sękowa, Szczawnica and Zawoja. The example described in the paper demonstrates that the k-means technique, despite its certain deficiencies, may prove useful for creating classifications and typologies leading to the selection of case study sites, as it is relatively time-effective, intuitive and available in opensource software. At the same time, due to the complexity of the socio-economic characteristics of the areas, the application of this method in socio-economic geography may require support in terms of the interpretation of the results through the analysis of additional data sources and expert knowledge.

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1 Prace Geograficzne

1 Wiadomości Statystyczne. The Polish Statistician

2 Warchalska-Troll A.

1 Warchalski T.

1 2022

1 2012

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How to measure susceptibility to degradation in large post-socialist housing estates?

The selection of areas for case study research in socio-economic geography with the application of k-means clustering