Use of multi-criteria decision analysis integrated with GIS and air pollution model inputs for schools site selection.

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Schools site selection is an essential process which needs knowledge of different fields. The process involves scientific justification, judgment and a finding of suitable land, which consider financial, social, ecological and political perspectives, that limit conflicts and supports agreement among the decision makers. Lack of scientific analysis may negatively impact on the economy, health, and safety of the public. However, reports revealed that finding of school location managed without utilization of scientific analysis thus prompted the development of schools in unsuitable areas and caused pupils to face several problems such as long walking distance, heavy traffic, presentation to sound and air pollution (Bukhari et al., 2010). Addis Ababa is the largest city in Ethiopia, and the city needs additional schools to meet the minimum pupil section ratio as per the national standard to improve education excellence (CGAAEB, 2018). Currently, most of the existing schools placed in the central part of the city; thus such scientific analysis is vital to give insight for the decision makers and planners to improve the site selection process for new schools, to provide a fair distribution of education access and utilizing a limited available resource. Nowadays, the application of GIS and Remote sensing datasets widely used to support the site selection process. In this study GIS integrated with MCDA and Remote Sensing, techniques have been used to select suitable school locations. MCDA is a tool that devoted to improving the decision-making process using various qualitative and quantitative criteria goals or objectives of a contradictory nature. This study attempts to use an air pollution model integrated with Remote Sensing, Geographical Information System (GIS) for Multi-Criteria Decision Analysis (MCDA) to identify optimal sites for new schools. The MCDA was done using Analytical hierarchy process (AHP), which classify criterions in hierarchical level and assigns a relative weight to each criteria using pairwise comparison. The selected criteria in this study decompose into three main groups, namely Economy, Accessibility, and Environmental Safety. Besides, Landsat 8 OLI/TRIS satellite image was used to quantify the annual mean concentration of Particulate matter with diameter 10 μm (PM10) for Environmental safety criteria. Subsequently, using Weight overlay tool, the criteria maps combined based on their relative influence, which is obtained from AHP to produce the final map, and the map reclassified as not suitable, less suitable, suitable and most suitable, using Arc GIS 10.4 reclassify tool. The resulting map of the annual mean concentration of PM10 shows that the concentration amounts on airports, factories, and road structures are high. The criteria weights obtained are 54%, 30% and 16% for Economy, Environmental Safety, and Accessibility respectively. The ultimate suitability map shows that 3.89% of the study area is most suitable, 57.47% is suitable, 38.48% is less suitable, and 0.08% is unsuitable, the most suitable areas laid on the city’s north-east and south-east part, which are away from existing schools. Therefore, this study successfully suitability model has been used to allocate an optimal place for new schools to be built in Addis Ababa capital using GIS integrated MCDA with Air pollution model input.


Masters Degrees (Civil Engineering). University of KwaZulu-Natal. Durban, 2019.