Application of multi-criteria decision analysis integrated with GIS and air pollution model inputs for schools site selection.
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Date
2019
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Abstract
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.
Description
Master’s Degree. University of KwaZulu-Natal, Durban.