ANALYSIS OF SPATIAL DISTRIBUTION OF SELECTED SOCIAL INFRASTRUCTURE IN ZURU LOCAL GOVERNMENT, KEBBI STATE
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- Recommended for : Student Researchers
- NGN 5000
ABSTRACT
Social infrastructure includes public primary schools (PPSs) and primary health care facilities (PHCs) which are essential in fostering community wellbeing, cohesion and development. For efficiency in the distribution of social infrastructure, population or travel distance can be used as a criterion for allocating social infrastructures. This study assessed the inadequacy and spatial inequality in the distribution of social infrastructure in Zuru local government of Kebbi State using both primary and secondary data. Six wards were sampled during this study namely; Bedi, Tadurga, Dabai, Rikoto, Rafin Zuru, Manga Ushe wards. Graphical analysis and spatial analysis were adopted for this research using ArcGIS 10.1 and Qgis. Firstly, PHCs and PPSs were identified and their locations were established using geographical positioning system (GPS). This study identified 14 primary health centres and 26 public primary schools existing within the sampled area. Nearest neighbour analysis revealed that both PPSs and PHCs exhibited a dispersed spatial distribution pattern with a neighbour ratio of 1.199216 and 1.284260 respectively. Hence, suggesting the likelihood of each facility being allocated far away from another not necessarily by a predetermined distance. Furthermore, service areas for each facility were established using both Euclidean and road network methods in G.I.S to determine areas that were adequately and also not adequately serviced by these facilities. Some households within Bedi, Tadurga and Manga Ushe are outside the catchment areas of PHCs and/or PPSs. More so, non-spatial data such as ward population, land area and count of PPSs and PHCs were also used to determine the spatial inequality and inadequacy using the Local Quotient. Result showed that Tadurga ward has an L.Q less than 1.0 and it is the most deprived ward in the allocated existing social infrastructures. Multiple model regression showed that there is no statically significant relationship between the population of wards and the number of existing social infrastructure. Thus, suggesting that a spatial criterion is used to allocate social infrastructure in the area. There is the need provide new facilities in deprived wards at strategic positions in other to ensure the adequacy of social infrastructure within Zuru local government area
