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Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City

Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City (IJACSA) International Journal of Advanced Computer Science and Applications, Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City 1 2 3 Abdulkader A. Murad , Abdulmuakhir I. Dalhat , Ammar A Naji Faculty of Architecture and Planning Department of Urban and Regional Planning King Abdulaziz University, Jeddah, 80210, Saudi Arabia Abstract—Geographical Information System (GIS) remains a Consequently, public authority's investment determines the unique tool use for school mapping for a clear understanding of pattern of distribution of educational facilities. Also, school the nature, planning, and distribution of educational facilities. mapping is a strategic planning process that tries to address the The study carried out a GIS analysis for male primary and deficiency in conscious effort to locate educational facilities in secondary schools’ distribution in Jeddah city, Saudi Arabia, to a place for maximum utilisation by a targeted population to show the significance of using GIS tools to assist the educational their advantage [6]. It is, therefore, a dynamic vision of how planning authorities. To understand, re-plan and address the the current and future education services look like to aid the location, distribution and availability challenges of the schools in implementation of policies and to help authorities to achieve Jeddah city. A Geodatabase for the study area was created, better decision-making regarding location and distribution of which incorporates education and population data collected from schools across different geographical areas to ensure optimum authorities. Spatial and network analyses are utilised to utilisation. According to [7], school mapping is essential in understand the location distribution, students’ density, and the promoting accessibility and equity in the distribution to avoid accessibility of the schools in the study region. The analyses over-localisation or over-concentration of schools in certain results identified the services and students’; density, directional areas while other areas are lacking. Another importance of growth of the schools, drive-time service areas and served and school mapping is to create a conducive condition for un-served populace for the authorities in Saudi Arabia to make achieving universal education [8]. Likewise, it is a means for better planning decisions, address present and future challenges research, gaging accessibility and aiding good decision-making in the provision of primary schools to residents and most importantly to improve educational services. The findings in school for better policies [9]. revealed that shorter travel distances found in the denser II. BACKGROUND (central) part of the city and some regions that need more schools. The Kingdom of Saudi Arabia (KSA) is said to be the second-largest Arab state with an estimated total area of Keywords—GIS; school mapping; educational facilities; 2,250,000 Km and a population of 34.2 million in 2019, geodatabase; spatial and network analysis according to the General Authority for Statistics [10]. Positioned somewhere between 16' and 32' S and 35' and 55'N, I. INTRODUCTION Saudi Arabia bordering Iraq, Jordan and Kuwait in the North, Both urban and rural areas are witnessing considerable Yemen in the South, the United Arab Emirates, o Oman, Qatar growth in all aspects, including the education sector. The and the Arabian Gulf to the East and the Red Sea to the West change requires proper planning and distribution of educational [10]. Besides, the cities of KSA are centres of commerce and facilities by Authorities to achieve equity and demand. culture. Riyadh is the most prominent, central and Educational facilities planning is a unique method of planning administrative capital with an estimated population of 4.21 schools' and facilities distribution, size, and spacing for best million. While, Jeddah is a commercial city, a gateway to Holy utilisation [1] at all levels to accelerate progress and prosperity Makkah and Medina with an estimated population of 3.43 in political, economic, social and cultural sectors [2]. It million. The third biggest city is the Holy Makkah city, with an includes a broad range of planning and management related to estimated population of 1.32 million. The total gross the resources' allocation, location, and distribution of enrollment ratio of school students, according to the Ministry educational services [3]. Planning of schools involves of education report is 98.1%, with an estimated total of 3.8 mapping, the planning of schools' location to guarantee million students [11]. Table I compares the population of the competent and impartial distribution, mainly when extensive three major cities kingdom, the area, students' enrollment and reforms or considerable growth of educational system take schools. Data obtained from the Ministry of Education shows place [4]. School mapping involves the creation of relational that Riyadh city with the highest population, area, number of geospatial databases for demographic, educational, social and students and schools then Jeddah and Makkah cities followed economic information for educational authorities to help respectively (Table I). decision-makers and planners [5]. It is an essential tool to understand the inequalities from the public authority's investment. 82 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, with a similar study in Kuwait presented the distribution of TABLE I. DATA COMPARISON OF MAJOR CITIES IN KSA [11]. educational facilities by categorising parts of the city with no Primary schools and failing to meet the least of students' needs using Secondary Schools Schools Population Area only spatial analysis. City (Million) (Km ) No. of No. of No. of No. of Similarly, Aschale [19] presented a study on the assessment Schools Students Schools Students of schools' spatial distribution in Debre Markos town of North- Riyadh 4.21 1,913 1,896 612,437 711 188,433 Western Ethiopia using GIS to explain the spatial appropriation Jeddah 3.43 1,765 1060 558,626 438 100,334 example of schools and the suitable future areas for the location of schools using various spatial analyses. Another Makkah 1.32 1,200 666 213,896 222 71,534 study carried out in Kano, Nigeria by Olubadewo, Abdulkarim, In KSA, challenges particularly in students' enrolment and & Ahmed [20] analysed the spatial distribution of primary accessibility due to accelerated urban expansion, population schools using spatial analysis functions and concluded that growth, traffic congestion and lack of use of justifiable and most of the schools concentrate where the density of students is suitable planning tool and scientific methods in the distribution high, just like the case of Jeddah. Also, a study carried out by planning of schools are currently the main issues in achieving Lagrab and Aknin [3] on the suitability analysis for elementary equitable distribution and access to educational facilities in schools in Mukalla districts of Yemen using spatial analyses; some parts of Jeddah city [12]. Equitable distribution means multiple ring buffer, then straight line distance measured, and fairness in the distribution and planning of schools. Lagrab & map algebra of classified raster(s), applied to select suitable Aknin [3] stated that the mapping and distribution of the locations for the establishment of new schools. services could provide proper planning and considering a The estimated driving time of students depends on age, spatial multicriteria (based on geographic information system) mode of transportation, school choice policy, and a long drive which can assist in planning, management, and policymaking. to school may influence student's capacity to get to class on In Educational facilities planning, GIS tools can offer time [21]; thus, standard travel-time recommended by innovative evaluation tools and complete information packages education authorities. A study carried out by Urban Institute for evaluating facilities and service area distribution [12]. reported that the average standard travel time to schools in Therefore, the information can aid policymakers, for example, most of the USA cities to be 10 minutes' drive [22]. In the case understanding the spatial distribution of existing educational of Saudi Arabia, the spatial distribution of primary and facilities and their catchment areas, both the density schools secondary schools requires the use of the minimum and and students, identifying and selecting schools' locations. GIS maximum criteria and standards of planning of schools as a specialised computer program collects, stores, approved standard catchment area for primary and secondary manipulates, retrieves and analyses spatial information that can schools' location in Jeddah city is 500 and 2500 meters, assist in understanding the distribution of educational facilities respectively [23]. Moreover, similar previous studies carried [13]. It is a computer-based data framework fit for out by wang et al. [24] and Sayed-Ahmad et al. [25] stated the incorporating information from different sources to give the international acceptable distance travel time standard to both data needed for effective decision-making [14]. It has become primary and secondary schools as presented in Table II. The a useful tool that offers critical understanding, depicts criteria are relative, not constant but depend on several relationships and aids the visualisation of data in significant planning variables. This study applies spatial analysis to hotspots within a spatial environment [15]. Environmental classify schools, and network analysis to identify the travel Systems Research Institute (ESRI) stated that GIS technology time catchment area to schools in Jeddah city. The study also exploits two kinds of data (spatial and attributes data). Spatial classifies the population that falls inside and outside the data is the information which defines the absolute and relative resulted travel time catchment area. position of geographic features [16]. At the same time, attribute data known as tabular data describes the quantitative and TABLE II. STANDARD CRITERIA FOR PLANNING SCHOOLS [23] qualitative characteristics of the spatial features. Criterion Primary Schools Secondary Schools According to Musa and Mohammed [17], several measures are available for evaluating spatial accessibility to educational Catchment Area (Meters) 500m 2500m facilities which include; imposing standards (i.e. travel time Distance from residence to 0.5-1km 0.5-2.5 km and catchment area distance) to schools. Point and kernel school (Kilometers) density, ring buffer and overlay analyses can be employed to Distance from residence to 10-15mins. 25-30mins. present the distribution and accessibility of schools. school (Minutes) Additionally, network analysis calculates the schools' Number of proximity access and adequate travel time to various schools' 12-24 classes 18-30 classes classrooms/School (Class) locations within the neighbourhood or study area. However, Number of student/Class similar studies carried out applied only spatial analyses like the 20-30 students 20-30 students (Students) case of Al-Enazi, Mesbah, & Anwar [12] that applied overlay Area for each student/Area and buffer analysis in assessing the schools' spatial distribution 2 2 15-25m 25-30m (Square meters) in Jeddah city. The outcomes provided substantial evidence on the distribution of schools spatially with population density in different districts of Jeddah. Al-Rasheed & El-Gamily [18] 83 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, III. MATERIAL AND METHODS student assessment, expanding the utilisation of technology and education subsidy [28]. Similarly, King Abdullah bin Abdul- A. Study Area Aziz Project for Public Education Development established in Jeddah city is the second biggest city in the KSA after the 2007 [31] to transform the kingdom educational framework capital city, Riyadh. It is a commercial city with the largest was to improve the education standard. The project initially set Seaport, located in Makkah Province on the Arabian Red Sea. up 25 each of boys' and girls' secondary schools (Tatweer Murad [26] stated that the Jeddah urban boundary and the total Schools) in 25 regions in Saudi Arabia, including Jeddah under area of 1765 km and 5460 km2, respectively. The city Makkah province. population estimated at around 3.43 Million in 2017. B. The Database According to the UNESCO report, the total school enrollment percentage in Saudi Arabia by 2016 is 116.24%, and the male For this study, both analogue and digital data were enrollment percentage is 117.26% compared to 115.19% collected, developed and updated into GIS format to form the female [27]. Based on the report, the school enrollment database for this application (Fig. 2). Firstly, point data defining the schools-based locations converted to point features exceeded 100% in Saudi Arabia because of the inclusion of with the city district resolution in ArcGIS 10.2.1 by ESRI, over-aged and under-aged pupils on account of the early or late Red- lands, CA, USA to present the location of schools in each school admission and grade repetition. district. Secondly, polygon and line data showing the city The first Saudi educational system was set up in 1924, at district boundaries/parcels and road network linked with point first, with barely any western schools [28]. Moreover, the data and all the GIS converted attributes using ArcGIS Education Ministry in 1953 was established, explicitly to application. Therefore, both the non-spatial and spatial data improve the educational system for male students to meet identified and characterised (Table III) which are linked international standards [29]. Ministry of Education represents together with detailed features of the study area (population, the government in providing and supervising free general land use and school data) for different analysis. ArcGIS is then education for all residents that consist of the advancement of used to carry out various spatial and network analysis that the national educational plan, issuing strategies, providing presented the spatial spread of primary and secondary schools training programs and assessing the educational performance in the city Jeddah. of teachers, students and schools at numerous stages [30]. With this, more schools constructed, and public education began to develop in the Kingdom and with an overall principle that the framework offers an equivalent prospect to all students notwithstanding their background. With regards to school management in KSA, the system is highly standardised, centralised and schools' leadership is gendered, where the boys' schools are managed by males and the females for girls' schools [31] due to the Islamic culture of Saudi Arabia. Additionally, data obtained from the Ministry of Education was analysed using ArcGIS to show schools' categorisation and location of male public schools in Jeddah city (Fig. 1). All public schools are managed and funded by the government, while, the private schools are funded solely or partly by students' tuition and managed by the private body but regulated by the government [11]. Children attend primary schools for six years, a 3-year intermediate and a 3-year secondary cycle with a separate higher education program as stated by the Saudi Arabian Cultural Mission report in the USA [32]. Furthermore, public schools are separated into male and female schools in Saudi Arabia. In KSA, the Ministry of Education sets benchmarks, creates educational plans, and structures course books for all schools everywhere throughout the Kingdom. Consequently, all schools must actualise similar principles, educational plans, and course readings. The Kingdom authorities are improving to address apparent shortcomings in their international standing; it has allowed a multiplicity of schools (private and international) to increase, normally charging dues, while following the authorities educational program [33]. Accordingly, the authorities continue refining rules and benchmarks by offering quality Fig. 1. Male Primary and Secondary Schools Location in Jeddah. training programs for teachers, improving guidelines for 84 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, the distribution in each district. Fig. 3 and Fig. 4 GIS analyses clearly show the classification and variation in the number of Defining the Application students in primary and secondary schools, respectively. Both Issues figures indicated an unequal distribution of students, with the central city districts having the highest number and it is Analyses on (Population, Creating and Building the justifiably because of the population concentration compared to Schools, Roads and Application Geodatabase the outer North and South of the city. Districts) Furthermore, kernel density analysis carried out shows the concentration and relationship between the density of students Network Spatial Analysis Data Layers existing in the study area. It describes the features (students) Analysis within each district of the city. A similar study carried out in 2018 on health care centres by Murad [26] stated that kernel Overlay Analysis on Drive density calculates the density of features in a neighbourhood Time and Population Data around those features, it can calculate for both point and line features and he further presented, as shown below, the algorithm used to determine the default Kernel search radius Fig. 2. Methodology Chart. (bandwidth) by Murad [26] is: TABLE III. CHARACTERISATION OF DATA LAYER 1) Calculate the mean centre of the input points. If a Layer Name Layer Description Feature Type Attribute Population field other than None were selected, this, and the values would weight all the following calculations in that field. Districts/Neighborhood NameArea, Land Use Vector/Polygon Boundaries Population 2) Calculate the distance from the (weighted) mean centre Supply, for all points. Schools School Types Vector/Point demand 3) Calculate the (weighted) median of these distances, D . Roads Road Networks Vector/Line Length, Time 4) Calculate the (weighted) Standard Distance, SD. 5) Apply the following formula to calculate the bandwidth: C. Spatial and Network Analysis −0.2 Search Radius = 0.9 ∗ min ( ,1 ∗ D𝑚 ) ∗ 𝑛 Spatial analysis can solve multipart location-oriented 1𝑛 (2) problems and offer new perspectives to decision making. where: Overlay spatial analysis that includes schools' accessibility and population information, kernel density, and network analyses SD is the standard distance carried out using by this paper to provide an insight into the D is the median distance spatial access and distribution of schools in Jeddah. Firstly, Kernel density shows the quantity of the population for every n is the number of points if no population field used, or if a point based on a quadratic formula with the maximum value at population field supplies, n is the sum of the population field the point location and decreasing to zero at the search radius value (number of students and classes). distance [16] (bandwidth) to obtain the density of features in the city districts. Secondly, network analysis gives network-based spatial analysis tools for explaining complex routing issues via a configurable transportation network data model to represent unique network requirements [16] accurately. It calculates drive-times and locates facilities with poor accessibility. In many GIS software, the network analysis module comprises of a few modelling functions that include finding the shortest path, service area model and allocate model [26]. This paper utilised the Allocate and service area functions in ArcGIS Network Analyst for assessing schools' accessibility. Thus, it defines access to schools within the study area by estimating distances and solving other network problems using network connectivity. The distance along the definite travel direction is measured with the travel impedance between the source and destination and represented based on distance and time. IV. RESULTS A. Distribution of Schools in Jeddah Define This study classifies schools based on the number of students using the 500m standard catchment area stated in Table I; in each school specifically to have an explicit nature of Fig. 3. Classification of Primary Schools based on the Number of Students. 85 | P a g e www.ijacsa.thesai.org 𝑆𝐷 (IJACSA) International Journal of Advanced Computer Science and Applications, Fig. 4. Classification of Secondary Schools based on the Number of Students. The presented algorithm calculated the schools' bandwidth based on the number of students in districts. Fig. 5 and Fig. 6 present the kernel density of both primary and secondary schools' students in the districts of Jeddah city and the darker Fig. 6. Kernel Density of Students in Secondary Schools. the colour, the higher the density. Both analyses presented, indicated virtually similar results showing that concentration is Additionally, GIS analysis can give a sense of direction by drawing highlights on a map, figuring the standard deviational more abundant in the central part of the city with a lower ellipse and clarifies the directional growth of primary schools concentration in the less populated outer part (North, South, (Fig. 7) and secondary schools (Fig. 8) in Jeddah city. The tool and East of Jeddah). analyse and clarifies the trend, utilising either the region of the feature or the region impacted by an attribute value related to the features. The latter is labeled as weighted standard deviation. Both analyses indicated that the directional growth is mainly in the concentrated city centre towards the western part where higher number of students are observed. The result could help authorities and planners have an objective understanding of the existing concentration and distribution of students and services in various districts of the city for better decision making and services improvement. B. Accessibility to Schools in Jeddah Accessibility to services, according to Murad [26] is a multidimensional concept that defines the connection between features of facilities and the features of the facility distribution framework. He further pointed out four main ways of measuring accessibility to health location, and the same way is applied for this paper but in this case, for public schools. So, network distance that calculates the length of the shortest route along the transportation network used considering its actual index accuracy, which produces accessibility regions, road network and travel time among the roads of the city. It gives the actual service areas when the connecting routes are clearly defined. Defining and estimating the adequate travel time to schools in Jeddah city, the 10-15 minutes (primary schools) and 30 minutes (secondary school) acceptable distance travel time standard to school given by the Saudi Arabia Ministry of Fig. 5. Kernel Density of Students in Primary Schools. Municipal and Rural Affairs is applied. Hence, this paper 86 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, adopted 15 minutes' and 30 minutes' maximum drive time as Accessibility analysis carried out utilising the ArcGIS the acceptable value for students to travel to primary and Network Analyst extension and created network service areas secondary schools respectively, taking into consideration the for existing male public schools' location in the study area. The average speeds and speed restrictions on various street types resultant service zone is a zone which covers altogether the and other physical hindrances to travel. available path which is within 15mins and 30mins travel time to primary and secondary schools respectively. The resulting outcome of the drive-time service areas shown in Fig. 9 and 10 indicated the areas of the city that are well served and regions with low accessibility within the 15 minutes' (primary schools) and 30 minutes (secondary school) standard drive-time. Both the primary and secondary analyses show a similar pattern with the city centre, the north-western and northern part of Jeddah mostly covered. Therefore, most districts are well served (60% of the city population), while the city parts that fall outside the standard drive time service area are within the outer part of the city where most are new districts with less population or parts industrial zones. From the results outcomes, it is apparent that the accessibility to schools in Jeddah city is to a more considerable extent commendable. However, the results give more insight into where the planners and authorities should focus on within the city. C. The Population within Access to Public Schools The population of students that falls within the access zones is obtained provided the service areas are well defined. Therefore, the drive-time analysis carried out in 3.2 presented a chance to define the served and unserved population. Fig. 9 and 10 presented correspondingly the results of the overlay analyses of the 15 minutes' and 30 minutes' drive-time of the population classification served and un-served population within access to the schools in districts of Jeddah (Fig. 13 and 14). The blue areas from both Fig. 11 and 12 indicated parts of Fig. 7. Directional Growth of Primary Schools. the city with a high and served population. However, the red coloured areas in Fig. 13 and 14, respectively indicated the areas of the city with a high un-served population that require additional schools and these areas in the case of primary schools is higher if compared to secondary school that is very insignificant. Hence, the need for planners and authorities to consider increasing the number of schools around the red zones in the city centre to cover the un-served population. Legend 15 Minues Road 2.5 1.25 0 2.5 Kilometers Ouside 15 Minutes Fig. 8. Directional Growth of Secondary Schools. Fig. 9. 15 Minutes' Drive-Time Service Area for Primary Schools. 87 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Fig. 12. Classification of the Population Inside 30 minutes' Drive Time Fig. 10. 30 Minutes' Drive-Time Service Area for Secondary Schools. Service area for Secondary Schools. Fig. 11. Classification of the Population inside 15 Minutes' Drivetime Service Area for Primary Schools. Fig. 13. Classification of Un-Served Population for Primary Schools. 88 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, This study could be useful to authorities to address issues, for example, development of micro and macro plan of public schools particularly with the focus on access and dispersion by understudy's distribution by students. The research provided information for policymakers in Saudi Arabia to plan for both short and long term to build the effectiveness of schools' service management and for evaluating the performance of school services. Additionally, it is to note that studies in spatial distribution using GIS technologies have heaved in a brought thought. Unlike this paper that applied both spatial and network analysis for school distribution, most of the comparable studies utilised either spatial or network analysis to present their analyses, not both. For example, a previous study carried out in Jeddah city by Al-Enazi et al. used overlay and buffer analyses to only define the inequalities in school's distribution [12]. Moreover, two studies in Mukalla district in Yemen both used GIS technology also to assess the educational facilities distribution but the analyses did not go further to cover network analysis to assess the population within access to those education facilities [3, 35]. Another similar and recent study carried out in Debre Markos Town in North-Western Ethiopia [19] unlike the presented cases only assess school spatial distribution and identify appropriate zones for the creation of new school sites according to schools' standards but not defining the service areas and drive-time that present a chance to define the served and unserved population. So, this paper combined spatial and network analyses in Fig. 14. Classification of Un-Served Population for Secondary Schools. analysing male public schools in Jeddah city to help in making meaningful choices, for example, selecting school's best V. DISCUSSION locations and recognising best new schools' locations by The distribution of educational facilities needs to be a authorities. Additionally, the paper found out that the old continuous process, and according to Department of Education districts have more population within the standard drive if report [2], functional and practical educational facilities could compared to the new and outer city districts that have low be planned and distributed based on a comprehensive plan of population and fewer services. Students in the old (central) action to check possible shortages. For this study, there is an districts have shorter travel distances to schools. This finding is attempt to achieve spatial balance in the spreading of the male supported by the works of Al-Enazi, Mesbah, and Anwar [12] primary and secondary schools in the districts of Jeddah. While who argued that the city centres are the areas with the most this appears to be achieved in some districts, the result of this served population. Additionally, most of the previous studies study shows that GIS was not used to plan such facilities. on educational facilities just found out school distributions However, the use of GIS technology identified the areas with using GIS [4, 12, 18, 19, 20] and a study that applied drive- shortages and access problems within the standard drive-time time to classify the served and un-served population in Saudi to schools. Meanwhile, the identification of the school Arabia is not being reported until this study. locations (Fig. 1), the classifications of schools and students' VI. CONCLUSION population data (Fig. 3, 4, 5 and 6), show imbalances between the districts with high concentration and shorter travel This paper explained that the use of GIS tools in distances in the central part of the city compared to the outer understanding the distribution of educational facilities is one of and less populated areas. A previous study carried out by the best methods as it gives a better understanding of spatial Belarem et al. in 2018 mapped and analysed the school and network situations upon which schools' planning decisions distribution and network in Makkah also shown a significant are based. It provided information on the various spatial imbalance in the distribution of schools between the districts, classification of schools carried-out about students' density and lack of accelerated networks and public transport services to distance travel-time in the districts of Jeddah city. The result schools for ease of accessibility [9], therefore, it shows similar identified the imbalances in the planning of male public disparities with this study where the city centre has high schools in Jeddah city to help Authorities address the current schools' density compared to peripheral areas. Also, the results and future challenges, and most importantly to make the best of a similar research carried out in Riyadh city [34], shows that improvements to raise the level of efficiency in the distribution. the spatial distribution of schools in Oraija, Riyadh is adequate, Also, the findings indicated the zones of the city with long however, the need to establish more schools to avoid travel distances. 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Available online: th http://www.data.gov.sa/en/general-authority-statistics (accessed on 9 [30] Algarni, F. and Male, T. Leadership in Saudi Arabian Public Schools: November 2019). Time for Devolution? ISEA 2014, Volume 42(3), pp. 45-59. [11] Ministry of Education. 2018. Available online: http://www.data.gov. [31] Alyami, R. H. Educational Reform in the Kingdom of Saudi Arabia: th sa/en/ministry-education-0 (accessed on 9 November 2018). Tatweer Schools as a Unit of Development. Literacy Information and Computer Education Journal (LICEJ) 2014, volume 5(2), pp. 1515- [12] Al-Enazi, M.; Mesbah, S.; Anwar, A. Schools Distribution Planning using GIS in Jeddah City. International Journal of Computer Applications 2016, Volume 138 (1), pp. 33–36. http://www.ijcaonline [32] Saudi Arabian Cultural Mission. Educational System in Saudi Arabia. .org/research/volume138/number1/alenazi-2016-ijca-908693.pdf SACM: Washington D.C, USA, 2006. [13] Steinberg, S. L.; Steinberg, S.J. 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Public Journal of Scientific & Technology Research 2015, volume 3. pp. 113- health reports 2011, Volume 126(2), pp. 298-303. 90 | P a g e www.ijacsa.thesai.org http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Advanced Computer Science and Applications Unpaywall

Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City

International Journal of Advanced Computer Science and ApplicationsJan 1, 2020

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(IJACSA) International Journal of Advanced Computer Science and Applications, Using Geographical Information System for Mapping Public Schools Distribution in Jeddah City 1 2 3 Abdulkader A. Murad , Abdulmuakhir I. Dalhat , Ammar A Naji Faculty of Architecture and Planning Department of Urban and Regional Planning King Abdulaziz University, Jeddah, 80210, Saudi Arabia Abstract—Geographical Information System (GIS) remains a Consequently, public authority's investment determines the unique tool use for school mapping for a clear understanding of pattern of distribution of educational facilities. Also, school the nature, planning, and distribution of educational facilities. mapping is a strategic planning process that tries to address the The study carried out a GIS analysis for male primary and deficiency in conscious effort to locate educational facilities in secondary schools’ distribution in Jeddah city, Saudi Arabia, to a place for maximum utilisation by a targeted population to show the significance of using GIS tools to assist the educational their advantage [6]. It is, therefore, a dynamic vision of how planning authorities. To understand, re-plan and address the the current and future education services look like to aid the location, distribution and availability challenges of the schools in implementation of policies and to help authorities to achieve Jeddah city. A Geodatabase for the study area was created, better decision-making regarding location and distribution of which incorporates education and population data collected from schools across different geographical areas to ensure optimum authorities. Spatial and network analyses are utilised to utilisation. According to [7], school mapping is essential in understand the location distribution, students’ density, and the promoting accessibility and equity in the distribution to avoid accessibility of the schools in the study region. The analyses over-localisation or over-concentration of schools in certain results identified the services and students’; density, directional areas while other areas are lacking. Another importance of growth of the schools, drive-time service areas and served and school mapping is to create a conducive condition for un-served populace for the authorities in Saudi Arabia to make achieving universal education [8]. Likewise, it is a means for better planning decisions, address present and future challenges research, gaging accessibility and aiding good decision-making in the provision of primary schools to residents and most importantly to improve educational services. The findings in school for better policies [9]. revealed that shorter travel distances found in the denser II. BACKGROUND (central) part of the city and some regions that need more schools. The Kingdom of Saudi Arabia (KSA) is said to be the second-largest Arab state with an estimated total area of Keywords—GIS; school mapping; educational facilities; 2,250,000 Km and a population of 34.2 million in 2019, geodatabase; spatial and network analysis according to the General Authority for Statistics [10]. Positioned somewhere between 16' and 32' S and 35' and 55'N, I. INTRODUCTION Saudi Arabia bordering Iraq, Jordan and Kuwait in the North, Both urban and rural areas are witnessing considerable Yemen in the South, the United Arab Emirates, o Oman, Qatar growth in all aspects, including the education sector. The and the Arabian Gulf to the East and the Red Sea to the West change requires proper planning and distribution of educational [10]. Besides, the cities of KSA are centres of commerce and facilities by Authorities to achieve equity and demand. culture. Riyadh is the most prominent, central and Educational facilities planning is a unique method of planning administrative capital with an estimated population of 4.21 schools' and facilities distribution, size, and spacing for best million. While, Jeddah is a commercial city, a gateway to Holy utilisation [1] at all levels to accelerate progress and prosperity Makkah and Medina with an estimated population of 3.43 in political, economic, social and cultural sectors [2]. It million. The third biggest city is the Holy Makkah city, with an includes a broad range of planning and management related to estimated population of 1.32 million. The total gross the resources' allocation, location, and distribution of enrollment ratio of school students, according to the Ministry educational services [3]. Planning of schools involves of education report is 98.1%, with an estimated total of 3.8 mapping, the planning of schools' location to guarantee million students [11]. Table I compares the population of the competent and impartial distribution, mainly when extensive three major cities kingdom, the area, students' enrollment and reforms or considerable growth of educational system take schools. Data obtained from the Ministry of Education shows place [4]. School mapping involves the creation of relational that Riyadh city with the highest population, area, number of geospatial databases for demographic, educational, social and students and schools then Jeddah and Makkah cities followed economic information for educational authorities to help respectively (Table I). decision-makers and planners [5]. It is an essential tool to understand the inequalities from the public authority's investment. 82 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, with a similar study in Kuwait presented the distribution of TABLE I. DATA COMPARISON OF MAJOR CITIES IN KSA [11]. educational facilities by categorising parts of the city with no Primary schools and failing to meet the least of students' needs using Secondary Schools Schools Population Area only spatial analysis. City (Million) (Km ) No. of No. of No. of No. of Similarly, Aschale [19] presented a study on the assessment Schools Students Schools Students of schools' spatial distribution in Debre Markos town of North- Riyadh 4.21 1,913 1,896 612,437 711 188,433 Western Ethiopia using GIS to explain the spatial appropriation Jeddah 3.43 1,765 1060 558,626 438 100,334 example of schools and the suitable future areas for the location of schools using various spatial analyses. Another Makkah 1.32 1,200 666 213,896 222 71,534 study carried out in Kano, Nigeria by Olubadewo, Abdulkarim, In KSA, challenges particularly in students' enrolment and & Ahmed [20] analysed the spatial distribution of primary accessibility due to accelerated urban expansion, population schools using spatial analysis functions and concluded that growth, traffic congestion and lack of use of justifiable and most of the schools concentrate where the density of students is suitable planning tool and scientific methods in the distribution high, just like the case of Jeddah. Also, a study carried out by planning of schools are currently the main issues in achieving Lagrab and Aknin [3] on the suitability analysis for elementary equitable distribution and access to educational facilities in schools in Mukalla districts of Yemen using spatial analyses; some parts of Jeddah city [12]. Equitable distribution means multiple ring buffer, then straight line distance measured, and fairness in the distribution and planning of schools. Lagrab & map algebra of classified raster(s), applied to select suitable Aknin [3] stated that the mapping and distribution of the locations for the establishment of new schools. services could provide proper planning and considering a The estimated driving time of students depends on age, spatial multicriteria (based on geographic information system) mode of transportation, school choice policy, and a long drive which can assist in planning, management, and policymaking. to school may influence student's capacity to get to class on In Educational facilities planning, GIS tools can offer time [21]; thus, standard travel-time recommended by innovative evaluation tools and complete information packages education authorities. A study carried out by Urban Institute for evaluating facilities and service area distribution [12]. reported that the average standard travel time to schools in Therefore, the information can aid policymakers, for example, most of the USA cities to be 10 minutes' drive [22]. In the case understanding the spatial distribution of existing educational of Saudi Arabia, the spatial distribution of primary and facilities and their catchment areas, both the density schools secondary schools requires the use of the minimum and and students, identifying and selecting schools' locations. GIS maximum criteria and standards of planning of schools as a specialised computer program collects, stores, approved standard catchment area for primary and secondary manipulates, retrieves and analyses spatial information that can schools' location in Jeddah city is 500 and 2500 meters, assist in understanding the distribution of educational facilities respectively [23]. Moreover, similar previous studies carried [13]. It is a computer-based data framework fit for out by wang et al. [24] and Sayed-Ahmad et al. [25] stated the incorporating information from different sources to give the international acceptable distance travel time standard to both data needed for effective decision-making [14]. It has become primary and secondary schools as presented in Table II. The a useful tool that offers critical understanding, depicts criteria are relative, not constant but depend on several relationships and aids the visualisation of data in significant planning variables. This study applies spatial analysis to hotspots within a spatial environment [15]. Environmental classify schools, and network analysis to identify the travel Systems Research Institute (ESRI) stated that GIS technology time catchment area to schools in Jeddah city. The study also exploits two kinds of data (spatial and attributes data). Spatial classifies the population that falls inside and outside the data is the information which defines the absolute and relative resulted travel time catchment area. position of geographic features [16]. At the same time, attribute data known as tabular data describes the quantitative and TABLE II. STANDARD CRITERIA FOR PLANNING SCHOOLS [23] qualitative characteristics of the spatial features. Criterion Primary Schools Secondary Schools According to Musa and Mohammed [17], several measures are available for evaluating spatial accessibility to educational Catchment Area (Meters) 500m 2500m facilities which include; imposing standards (i.e. travel time Distance from residence to 0.5-1km 0.5-2.5 km and catchment area distance) to schools. Point and kernel school (Kilometers) density, ring buffer and overlay analyses can be employed to Distance from residence to 10-15mins. 25-30mins. present the distribution and accessibility of schools. school (Minutes) Additionally, network analysis calculates the schools' Number of proximity access and adequate travel time to various schools' 12-24 classes 18-30 classes classrooms/School (Class) locations within the neighbourhood or study area. However, Number of student/Class similar studies carried out applied only spatial analyses like the 20-30 students 20-30 students (Students) case of Al-Enazi, Mesbah, & Anwar [12] that applied overlay Area for each student/Area and buffer analysis in assessing the schools' spatial distribution 2 2 15-25m 25-30m (Square meters) in Jeddah city. The outcomes provided substantial evidence on the distribution of schools spatially with population density in different districts of Jeddah. Al-Rasheed & El-Gamily [18] 83 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, III. MATERIAL AND METHODS student assessment, expanding the utilisation of technology and education subsidy [28]. Similarly, King Abdullah bin Abdul- A. Study Area Aziz Project for Public Education Development established in Jeddah city is the second biggest city in the KSA after the 2007 [31] to transform the kingdom educational framework capital city, Riyadh. It is a commercial city with the largest was to improve the education standard. The project initially set Seaport, located in Makkah Province on the Arabian Red Sea. up 25 each of boys' and girls' secondary schools (Tatweer Murad [26] stated that the Jeddah urban boundary and the total Schools) in 25 regions in Saudi Arabia, including Jeddah under area of 1765 km and 5460 km2, respectively. The city Makkah province. population estimated at around 3.43 Million in 2017. B. The Database According to the UNESCO report, the total school enrollment percentage in Saudi Arabia by 2016 is 116.24%, and the male For this study, both analogue and digital data were enrollment percentage is 117.26% compared to 115.19% collected, developed and updated into GIS format to form the female [27]. Based on the report, the school enrollment database for this application (Fig. 2). Firstly, point data defining the schools-based locations converted to point features exceeded 100% in Saudi Arabia because of the inclusion of with the city district resolution in ArcGIS 10.2.1 by ESRI, over-aged and under-aged pupils on account of the early or late Red- lands, CA, USA to present the location of schools in each school admission and grade repetition. district. Secondly, polygon and line data showing the city The first Saudi educational system was set up in 1924, at district boundaries/parcels and road network linked with point first, with barely any western schools [28]. Moreover, the data and all the GIS converted attributes using ArcGIS Education Ministry in 1953 was established, explicitly to application. Therefore, both the non-spatial and spatial data improve the educational system for male students to meet identified and characterised (Table III) which are linked international standards [29]. Ministry of Education represents together with detailed features of the study area (population, the government in providing and supervising free general land use and school data) for different analysis. ArcGIS is then education for all residents that consist of the advancement of used to carry out various spatial and network analysis that the national educational plan, issuing strategies, providing presented the spatial spread of primary and secondary schools training programs and assessing the educational performance in the city Jeddah. of teachers, students and schools at numerous stages [30]. With this, more schools constructed, and public education began to develop in the Kingdom and with an overall principle that the framework offers an equivalent prospect to all students notwithstanding their background. With regards to school management in KSA, the system is highly standardised, centralised and schools' leadership is gendered, where the boys' schools are managed by males and the females for girls' schools [31] due to the Islamic culture of Saudi Arabia. Additionally, data obtained from the Ministry of Education was analysed using ArcGIS to show schools' categorisation and location of male public schools in Jeddah city (Fig. 1). All public schools are managed and funded by the government, while, the private schools are funded solely or partly by students' tuition and managed by the private body but regulated by the government [11]. Children attend primary schools for six years, a 3-year intermediate and a 3-year secondary cycle with a separate higher education program as stated by the Saudi Arabian Cultural Mission report in the USA [32]. Furthermore, public schools are separated into male and female schools in Saudi Arabia. In KSA, the Ministry of Education sets benchmarks, creates educational plans, and structures course books for all schools everywhere throughout the Kingdom. Consequently, all schools must actualise similar principles, educational plans, and course readings. The Kingdom authorities are improving to address apparent shortcomings in their international standing; it has allowed a multiplicity of schools (private and international) to increase, normally charging dues, while following the authorities educational program [33]. Accordingly, the authorities continue refining rules and benchmarks by offering quality Fig. 1. Male Primary and Secondary Schools Location in Jeddah. training programs for teachers, improving guidelines for 84 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, the distribution in each district. Fig. 3 and Fig. 4 GIS analyses clearly show the classification and variation in the number of Defining the Application students in primary and secondary schools, respectively. Both Issues figures indicated an unequal distribution of students, with the central city districts having the highest number and it is Analyses on (Population, Creating and Building the justifiably because of the population concentration compared to Schools, Roads and Application Geodatabase the outer North and South of the city. Districts) Furthermore, kernel density analysis carried out shows the concentration and relationship between the density of students Network Spatial Analysis Data Layers existing in the study area. It describes the features (students) Analysis within each district of the city. A similar study carried out in 2018 on health care centres by Murad [26] stated that kernel Overlay Analysis on Drive density calculates the density of features in a neighbourhood Time and Population Data around those features, it can calculate for both point and line features and he further presented, as shown below, the algorithm used to determine the default Kernel search radius Fig. 2. Methodology Chart. (bandwidth) by Murad [26] is: TABLE III. CHARACTERISATION OF DATA LAYER 1) Calculate the mean centre of the input points. If a Layer Name Layer Description Feature Type Attribute Population field other than None were selected, this, and the values would weight all the following calculations in that field. Districts/Neighborhood NameArea, Land Use Vector/Polygon Boundaries Population 2) Calculate the distance from the (weighted) mean centre Supply, for all points. Schools School Types Vector/Point demand 3) Calculate the (weighted) median of these distances, D . Roads Road Networks Vector/Line Length, Time 4) Calculate the (weighted) Standard Distance, SD. 5) Apply the following formula to calculate the bandwidth: C. Spatial and Network Analysis −0.2 Search Radius = 0.9 ∗ min ( ,1 ∗ D𝑚 ) ∗ 𝑛 Spatial analysis can solve multipart location-oriented 1𝑛 (2) problems and offer new perspectives to decision making. where: Overlay spatial analysis that includes schools' accessibility and population information, kernel density, and network analyses SD is the standard distance carried out using by this paper to provide an insight into the D is the median distance spatial access and distribution of schools in Jeddah. Firstly, Kernel density shows the quantity of the population for every n is the number of points if no population field used, or if a point based on a quadratic formula with the maximum value at population field supplies, n is the sum of the population field the point location and decreasing to zero at the search radius value (number of students and classes). distance [16] (bandwidth) to obtain the density of features in the city districts. Secondly, network analysis gives network-based spatial analysis tools for explaining complex routing issues via a configurable transportation network data model to represent unique network requirements [16] accurately. It calculates drive-times and locates facilities with poor accessibility. In many GIS software, the network analysis module comprises of a few modelling functions that include finding the shortest path, service area model and allocate model [26]. This paper utilised the Allocate and service area functions in ArcGIS Network Analyst for assessing schools' accessibility. Thus, it defines access to schools within the study area by estimating distances and solving other network problems using network connectivity. The distance along the definite travel direction is measured with the travel impedance between the source and destination and represented based on distance and time. IV. RESULTS A. Distribution of Schools in Jeddah Define This study classifies schools based on the number of students using the 500m standard catchment area stated in Table I; in each school specifically to have an explicit nature of Fig. 3. Classification of Primary Schools based on the Number of Students. 85 | P a g e www.ijacsa.thesai.org 𝑆𝐷 (IJACSA) International Journal of Advanced Computer Science and Applications, Fig. 4. Classification of Secondary Schools based on the Number of Students. The presented algorithm calculated the schools' bandwidth based on the number of students in districts. Fig. 5 and Fig. 6 present the kernel density of both primary and secondary schools' students in the districts of Jeddah city and the darker Fig. 6. Kernel Density of Students in Secondary Schools. the colour, the higher the density. Both analyses presented, indicated virtually similar results showing that concentration is Additionally, GIS analysis can give a sense of direction by drawing highlights on a map, figuring the standard deviational more abundant in the central part of the city with a lower ellipse and clarifies the directional growth of primary schools concentration in the less populated outer part (North, South, (Fig. 7) and secondary schools (Fig. 8) in Jeddah city. The tool and East of Jeddah). analyse and clarifies the trend, utilising either the region of the feature or the region impacted by an attribute value related to the features. The latter is labeled as weighted standard deviation. Both analyses indicated that the directional growth is mainly in the concentrated city centre towards the western part where higher number of students are observed. The result could help authorities and planners have an objective understanding of the existing concentration and distribution of students and services in various districts of the city for better decision making and services improvement. B. Accessibility to Schools in Jeddah Accessibility to services, according to Murad [26] is a multidimensional concept that defines the connection between features of facilities and the features of the facility distribution framework. He further pointed out four main ways of measuring accessibility to health location, and the same way is applied for this paper but in this case, for public schools. So, network distance that calculates the length of the shortest route along the transportation network used considering its actual index accuracy, which produces accessibility regions, road network and travel time among the roads of the city. It gives the actual service areas when the connecting routes are clearly defined. Defining and estimating the adequate travel time to schools in Jeddah city, the 10-15 minutes (primary schools) and 30 minutes (secondary school) acceptable distance travel time standard to school given by the Saudi Arabia Ministry of Fig. 5. Kernel Density of Students in Primary Schools. Municipal and Rural Affairs is applied. Hence, this paper 86 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, adopted 15 minutes' and 30 minutes' maximum drive time as Accessibility analysis carried out utilising the ArcGIS the acceptable value for students to travel to primary and Network Analyst extension and created network service areas secondary schools respectively, taking into consideration the for existing male public schools' location in the study area. The average speeds and speed restrictions on various street types resultant service zone is a zone which covers altogether the and other physical hindrances to travel. available path which is within 15mins and 30mins travel time to primary and secondary schools respectively. The resulting outcome of the drive-time service areas shown in Fig. 9 and 10 indicated the areas of the city that are well served and regions with low accessibility within the 15 minutes' (primary schools) and 30 minutes (secondary school) standard drive-time. Both the primary and secondary analyses show a similar pattern with the city centre, the north-western and northern part of Jeddah mostly covered. Therefore, most districts are well served (60% of the city population), while the city parts that fall outside the standard drive time service area are within the outer part of the city where most are new districts with less population or parts industrial zones. From the results outcomes, it is apparent that the accessibility to schools in Jeddah city is to a more considerable extent commendable. However, the results give more insight into where the planners and authorities should focus on within the city. C. The Population within Access to Public Schools The population of students that falls within the access zones is obtained provided the service areas are well defined. Therefore, the drive-time analysis carried out in 3.2 presented a chance to define the served and unserved population. Fig. 9 and 10 presented correspondingly the results of the overlay analyses of the 15 minutes' and 30 minutes' drive-time of the population classification served and un-served population within access to the schools in districts of Jeddah (Fig. 13 and 14). The blue areas from both Fig. 11 and 12 indicated parts of Fig. 7. Directional Growth of Primary Schools. the city with a high and served population. However, the red coloured areas in Fig. 13 and 14, respectively indicated the areas of the city with a high un-served population that require additional schools and these areas in the case of primary schools is higher if compared to secondary school that is very insignificant. Hence, the need for planners and authorities to consider increasing the number of schools around the red zones in the city centre to cover the un-served population. Legend 15 Minues Road 2.5 1.25 0 2.5 Kilometers Ouside 15 Minutes Fig. 8. Directional Growth of Secondary Schools. Fig. 9. 15 Minutes' Drive-Time Service Area for Primary Schools. 87 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, Fig. 12. Classification of the Population Inside 30 minutes' Drive Time Fig. 10. 30 Minutes' Drive-Time Service Area for Secondary Schools. Service area for Secondary Schools. Fig. 11. Classification of the Population inside 15 Minutes' Drivetime Service Area for Primary Schools. Fig. 13. Classification of Un-Served Population for Primary Schools. 88 | P a g e www.ijacsa.thesai.org (IJACSA) International Journal of Advanced Computer Science and Applications, This study could be useful to authorities to address issues, for example, development of micro and macro plan of public schools particularly with the focus on access and dispersion by understudy's distribution by students. The research provided information for policymakers in Saudi Arabia to plan for both short and long term to build the effectiveness of schools' service management and for evaluating the performance of school services. Additionally, it is to note that studies in spatial distribution using GIS technologies have heaved in a brought thought. Unlike this paper that applied both spatial and network analysis for school distribution, most of the comparable studies utilised either spatial or network analysis to present their analyses, not both. For example, a previous study carried out in Jeddah city by Al-Enazi et al. used overlay and buffer analyses to only define the inequalities in school's distribution [12]. Moreover, two studies in Mukalla district in Yemen both used GIS technology also to assess the educational facilities distribution but the analyses did not go further to cover network analysis to assess the population within access to those education facilities [3, 35]. Another similar and recent study carried out in Debre Markos Town in North-Western Ethiopia [19] unlike the presented cases only assess school spatial distribution and identify appropriate zones for the creation of new school sites according to schools' standards but not defining the service areas and drive-time that present a chance to define the served and unserved population. So, this paper combined spatial and network analyses in Fig. 14. Classification of Un-Served Population for Secondary Schools. analysing male public schools in Jeddah city to help in making meaningful choices, for example, selecting school's best V. DISCUSSION locations and recognising best new schools' locations by The distribution of educational facilities needs to be a authorities. Additionally, the paper found out that the old continuous process, and according to Department of Education districts have more population within the standard drive if report [2], functional and practical educational facilities could compared to the new and outer city districts that have low be planned and distributed based on a comprehensive plan of population and fewer services. Students in the old (central) action to check possible shortages. For this study, there is an districts have shorter travel distances to schools. This finding is attempt to achieve spatial balance in the spreading of the male supported by the works of Al-Enazi, Mesbah, and Anwar [12] primary and secondary schools in the districts of Jeddah. While who argued that the city centres are the areas with the most this appears to be achieved in some districts, the result of this served population. Additionally, most of the previous studies study shows that GIS was not used to plan such facilities. on educational facilities just found out school distributions However, the use of GIS technology identified the areas with using GIS [4, 12, 18, 19, 20] and a study that applied drive- shortages and access problems within the standard drive-time time to classify the served and un-served population in Saudi to schools. Meanwhile, the identification of the school Arabia is not being reported until this study. locations (Fig. 1), the classifications of schools and students' VI. CONCLUSION population data (Fig. 3, 4, 5 and 6), show imbalances between the districts with high concentration and shorter travel This paper explained that the use of GIS tools in distances in the central part of the city compared to the outer understanding the distribution of educational facilities is one of and less populated areas. A previous study carried out by the best methods as it gives a better understanding of spatial Belarem et al. in 2018 mapped and analysed the school and network situations upon which schools' planning decisions distribution and network in Makkah also shown a significant are based. It provided information on the various spatial imbalance in the distribution of schools between the districts, classification of schools carried-out about students' density and lack of accelerated networks and public transport services to distance travel-time in the districts of Jeddah city. The result schools for ease of accessibility [9], therefore, it shows similar identified the imbalances in the planning of male public disparities with this study where the city centre has high schools in Jeddah city to help Authorities address the current schools' density compared to peripheral areas. Also, the results and future challenges, and most importantly to make the best of a similar research carried out in Riyadh city [34], shows that improvements to raise the level of efficiency in the distribution. the spatial distribution of schools in Oraija, Riyadh is adequate, Also, the findings indicated the zones of the city with long however, the need to establish more schools to avoid travel distances. 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Public Journal of Scientific & Technology Research 2015, volume 3. pp. 113- health reports 2011, Volume 126(2), pp. 298-303. 90 | P a g e www.ijacsa.thesai.org

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