Mapping and Spatial Distribution of Post Primary Schools in Yola North Local Government Area of Adamawa State, Nigeria

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Author(s) Aliyu A | Shahidah M.A | Aliyu R.M
Pages 405-422
Volume 2
Issue 5
Date May, 2013
Keywords Mapping, Global Positioning System, MATLAB, GIS.
Abstract

Observed Global positioning system coordinates of all post-primary schools in Yola North local Government Area were obtained These coordinates were used to create a digital map showing the location of post-primary schools within the study area. These coordinates were used to determine the distances from one point to its Nearest Neighbors in a particular unit area. The distances were computed using a computer program written in MATLAB 2009a programming language. The distances obtained were then used in determining the distribution pattern of these schools using Nearest Neighbor Analysis statistical tool, where the value of Nearest Neighbor index (Rn) was computed and was found to be Rn=1.1124. This result obtained indicates that random distribution pattern exists in the study area. The test of significance on the value of Rn was then computed using Z-distribution and from the value of Z obtained, it shows that the value of Rn is significant. A database was created using the attributes of the schools and different queries were generated from the geo-spatial database created as shown in figures 4.3 - 4.8. The analysis indicates that Nearest Neighbor analysis can favorably be used in determining the spatial distribution pattern of the post-primary schools and other facilities for a meaningful development. The study clearly depicts the process of using Nearest Neighbor analysis in determining the spatial distribution pattern of the post-primary schools. The study reveals how the schools were located on a digital map and the value of Rn shows that random pattern of distribution exists within the study area. The scale used for the unit area (A) exposes two schools without any Neighbor. Nearest Neighbor Analysis is recommended for determination of spatial distribution pattern of schools, since it shows clearly how these schools are distributed. Writing a computer program should be encouraged in calculating distances from coordinates using a programming language especially MATLAB.

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