Summary:

Apparent diversification of the malopolskie province area in respect of its topography and unequal financial resources at the disposal of individual communes and districts may determine the level of their infrastructure development. At present, when Poland became the European Union member state and entered its financing structures, spatial development of the infrastructural potential is affected by the activities of local self governments. Intensive development and modernization of infrastructure favour local concentration of communes with high values of the indicator. Technical infrastructure is an element strictly connected with space and its level is affected by social, financial and human factors, which provides a basis for an analysis of the influence of local spaces on its development or lack of it. In the article local diversification of communes was made using Local Moran’s Ii statistics. Local statistics my verify whether a commune is surrounded by neighbouring objects (communes) with similar or various values of analyzed variable in relation to random distribution of these values in space. It allows for identification of spatial effects of an agglomeration. Such analysis of local indicators of spatial association LISA was suggested by Anselin [Anselin 1995]. The article aims at presentation of local indicators of spatial dependencies of administrative units on the level of communes in the malopolskie province considering one indicator of technical infrastructure, i.e. the length of water mains per the object area. Presented possibilities of Local Moran’s I_i application for an analysis of individual phenomena spreading in space and automatic searching for spatial standards and poor objects. Such analysis may be helpful for making decision concerning financial assistance or allocating assistance funds in such a way that the communes which constitute low value clusters would be able to reach the nearest future the upper limit of spatial standards. Statistics of spatial autocorrelation inform about the kind and the strength of spatial dependence, make possible a determination of associations among objects and establishing spatial structure better than using the traditional methods.