Zastosowanie metody krigingu Poissona w badaniach rozkładu przestrzennego problemów społecznych na przykładzie Poznania
Streszczenie
Analiza przestrzenna danych społecznych wymaga niejednokrotnie odfiltrowania
wpływu nierealnych, odstających danych. Celem pracy jest omówienie podstaw teoretycznych
bardzo efektywnej, a mało znanej metody do tego służącej ‒ krigingu Poissona.
Ilustrację praktyczną jej zalet przedstawiono na przykładzie identyfikacji obszarów
występowania różnych kategorii problemów społecznych na obszarze Poznania. Planning of social policy it is complicated and multidimensional issue, especially in
complex urban structures characteristic for big cities. However econometric indicators of
spatial dependence provide us some information about spatial autocorrelation, their do
not show the differences in local variability. Geostatistics is an answer for this challenge.
This method is not only helpful in more accurate determination of the most important
problems but it also enables identification of their location, scale and possible reasons.
This paper presents possibilities given by Poisson Kriging for analysis of social
problems in urban space. Its was applied in Poznań for identification of neighbourhoods
or local communities (related to the basic administrative units called „osiedla”) in which
concentration of people needing social help is bigger than population distribution might
it suggest.
The data used in the analysis was taken from urban centre helping families in
difficult social situation (MOPR). They concerns people who received financial support
in 2008. The basic information taken into account was their place of residence and the
reason for which they received financial aid. MOPR distinguish 13 categories of social
problems needing support, including poverty, chronic diseases, alcoholism and domestic
violence. 9 473 persons received financial aid in the analysed period of time. Taking into
account their families it give us at least 18 264 people struggling with social problems –
3,3% of the city population (545 000 inhabitants).
In order to receive comparable measure of issues analysed in urban space, the
number of people needing social support must be compared with the population distribution.
Thus, information about place of residence of people who receives financial aid
was aggregated to bigger areas – 731 regular polygons for which the number of city
inhabitants was know. Side length of single polygon was 500 meters. In each polygon
data needed also to be age-adjusted. It is very sophisticated task, therefore special script
dedicated for ArcGIS was created. The age-adjusted data aggregated in the polygons
were bases for main spatial analysis.
Application of Poisson Kriging resulted in more precise identification of areas
affected by the major social problems in Poznań. Presence of autocorrelation was
noticeable in case of majority of analysed social problems. The most common ranges of
autocorrelation were 1‒1,2 km (which is similar to the spatial range of single local
communities) and 6–6,5 km (the range of single neighbourhoods). Analysis showed that
there are some neighbourhoods in Poznań where occurrence of social problems is
significantly higher than mean occurrence for the whole city. Presented method enabled
smoothing of unreliable, extremely high relative risks values but without loss of the local
variability.